From a146fd6d4ccdf051d4f5dcd87308996e86bf8cec Mon Sep 17 00:00:00 2001 From: jvfe Date: Mon, 26 Sep 2022 16:03:35 -0300 Subject: [PATCH 01/24] Add script to get biotypes for DGE/DTE --- .gitignore | 3 +- scripts/summarise_biotypes.R | 82 ++++++++++++++++++++++++++++++++++++ 2 files changed, 84 insertions(+), 1 deletion(-) create mode 100644 scripts/summarise_biotypes.R diff --git a/.gitignore b/.gitignore index dbe2dcc..4ccc2ae 100644 --- a/.gitignore +++ b/.gitignore @@ -19,4 +19,5 @@ renv/* slurm* run* -data/* \ No newline at end of file +data/* +results/diff_exp/* diff --git a/scripts/summarise_biotypes.R b/scripts/summarise_biotypes.R new file mode 100644 index 0000000..28cf2f9 --- /dev/null +++ b/scripts/summarise_biotypes.R @@ -0,0 +1,82 @@ +library(dplyr) +library(purrr) +library(ggplot2) +library(rtracklayer) +library(GenomicFeatures) + +# 1. Carregando GTF --------------------------------------- +gtf <- "./data/Homo_sapiens.GRCh38.97.chr_patch_hapl_scaff.gtf.gz" + +gtf_data <- import(gtf) + +# 2. Lendo DGE/DTE e pegando os biotipos --------------------------------------- +load("./results/diff_exp/diff_df.rda") + +dge_genes <- diff_df %>% + filter(type == "DGE") + +# 2.1. Pegando biotipo dos DGE --------------------------------------- +dge_w_biotype <- gtf_data[, c("gene_id", "gene_biotype")] %>% + as.data.frame() %>% + filter(gene_id %in% dge_genes$gene) %>% + dplyr::select(gene_id, gene_biotype) %>% + right_join(dge_genes, by = c("gene_id" = "gene")) %>% + distinct() %>% + dplyr::select(gene_id, gene_biotype, group) + +readr::write_csv(dge_w_biotype, "results/diff_exp/dge_w_biotype.csv") + +# 2.2. Pegando biotipo dos DTE --------------------------------------- +load("./results/diff_exp/diff_tx_corrected.rda") + +dte_genes <- df_res_padj_tx %>% + dplyr::select(txID, transcript, group) %>% + filter(transcript < 0.01) + +dte_w_biotype <- + gtf_data[, c("transcript_id", "transcript_biotype")] %>% + as.data.frame() %>% + filter(transcript_id %in% dte_genes$txID) %>% + dplyr::select(transcript_id, transcript_biotype) %>% + right_join(dte_genes, by = c("transcript_id" = "txID")) %>% + distinct() %>% + dplyr::select(transcript_id, transcript_biotype, group) + +readr::write_csv(dte_w_biotype, "results/diff_exp/dte_w_biotype.csv") + +# 2.3. Pegando biotipo dos DTU --------------------------------------- + + + +# 3. Plotando as porcentagens --------------------------------------- +plot_biotype_bar <- function(data, id_col, n_col) { + + id_col <- enquo(id_col) + n_col <- enquo(n_col) + + data %>% + ggplot(aes(x = reorder(!!id_col, dplyr::desc(!!n_col)), y = !!n_col)) + + geom_col() + + scale_y_continuous(labels = scales::percent_format(scale = 1)) + + coord_flip() + + labs( + y = "Porcentagem de Genes", + x = "Biotipo", + ) + +} + +dge_plot <- dge_w_biotype %>% + group_by(gene_biotype) %>% + summarise(biotype_n = n() / length(unique(dge_w_biotype$gene_id)) * 100) %>% + ungroup() %>% + plot_biotype_bar(. , id_col = gene_biotype, n_col = biotype_n) + +dte_plot <- dte_w_biotype %>% + group_by(transcript_biotype) %>% + summarise(biotype_n = n() / length(unique(dte_w_biotype$transcript_id))* 100) %>% + ungroup() %>% + plot_biotype_bar(., id_col = transcript_biotype, n_col = biotype_n) + +ggsave(dge_plot, filename = "results/diff_exp/dge_biotypes.pdf") +ggsave(dte_plot, filename = "results/diff_exp/dte_biotypes.pdf") \ No newline at end of file From c206ad95ea0af16eedef8cd0b18a7845f80bedec Mon Sep 17 00:00:00 2001 From: jvfe Date: Mon, 26 Sep 2022 16:26:17 -0300 Subject: [PATCH 02/24] Add script to compile all results from DTU --- .gitignore | 1 + scripts/compile_DTU.R | 42 ++++++++++++++++++++++++++++++++++++++++++ 2 files changed, 43 insertions(+) create mode 100644 scripts/compile_DTU.R diff --git a/.gitignore b/.gitignore index 4ccc2ae..1aaeee8 100644 --- a/.gitignore +++ b/.gitignore @@ -21,3 +21,4 @@ slurm* run* data/* results/diff_exp/* +results/ISA/ diff --git a/scripts/compile_DTU.R b/scripts/compile_DTU.R new file mode 100644 index 0000000..1240f5c --- /dev/null +++ b/scripts/compile_DTU.R @@ -0,0 +1,42 @@ +library(dplyr) +library(purrr) +library(IsoformSwitchAnalyzeR) + +# 1. Get all results from ISA ------ + +files <- + list.files( + "results/ISA/", + pattern = "pass2", + recursive = T, + full.names = T + ) +isa_df <- map_dfr(files, ~ { + load(.x) + SwitchList_2$isoformFeatures +}) + +# 2. Filter results by conditions and save full result ----- + +condition_1_male <- grepl("CTRL_male", isa_df$condition_1) +condition_2_male <- grepl("MDD_male", isa_df$condition_2) +condition_1_female <- grepl("CTRL_female", isa_df$condition_1) +condition_2_female <- grepl("MDD_female", isa_df$condition_2) + +isa_df <- isa_df[(condition_1_male & condition_2_male) | + (condition_1_female & condition_2_female), ] + +save(isa_df, file = "results/ISA/DTU_df.rda") + +# 3. Get dataframe with biotypes ---- + +dtu_w_biotypes <- isa_df %>% + mutate( + gene_id = gsub("\\.\\d+", "", gene_id), + isoform_id = gsub("\\.\\d+", "", isoform_id) + ) %>% + filter(isoform_switch_q_value <= 0.05) %>% + mutate(group = gsub("_CTRL", "", condition_1)) %>% + dplyr::select(isoform_id, iso_biotype, group) + +readr::write_csv(dtu_w_biotypes, file = "results/ISA/dtu_w_biotype.csv") From db5d36381fb22b6292c3854c7dfbcc24935faec4 Mon Sep 17 00:00:00 2001 From: jvfe Date: Mon, 26 Sep 2022 16:33:58 -0300 Subject: [PATCH 03/24] Add DTU results to summarise biotypes script --- scripts/summarise_biotypes.R | 11 +++++++++-- 1 file changed, 9 insertions(+), 2 deletions(-) diff --git a/scripts/summarise_biotypes.R b/scripts/summarise_biotypes.R index 28cf2f9..fc025a1 100644 --- a/scripts/summarise_biotypes.R +++ b/scripts/summarise_biotypes.R @@ -46,7 +46,7 @@ readr::write_csv(dte_w_biotype, "results/diff_exp/dte_w_biotype.csv") # 2.3. Pegando biotipo dos DTU --------------------------------------- - +dtu_w_biotype <- readr::read_csv("results/ISA/dtu_w_biotype.csv") # 3. Plotando as porcentagens --------------------------------------- plot_biotype_bar <- function(data, id_col, n_col) { @@ -78,5 +78,12 @@ dte_plot <- dte_w_biotype %>% ungroup() %>% plot_biotype_bar(., id_col = transcript_biotype, n_col = biotype_n) +dtu_plot <- dtu_w_biotype %>% + group_by(iso_biotype) %>% + summarise(biotype_n = n() / length(unique(dtu_w_biotype$isoform_id))* 100) %>% + ungroup() %>% + plot_biotype_bar(., id_col = iso_biotype, n_col = biotype_n) + ggsave(dge_plot, filename = "results/diff_exp/dge_biotypes.pdf") -ggsave(dte_plot, filename = "results/diff_exp/dte_biotypes.pdf") \ No newline at end of file +ggsave(dte_plot, filename = "results/diff_exp/dte_biotypes.pdf") +ggsave(dtu_plot, filename = "results/diff_exp/dtu_biotypes.pdf") From c9c468ae1b1a62d181629473b936a54c7867e6de Mon Sep 17 00:00:00 2001 From: Iara Souza Date: Sat, 15 Apr 2023 15:34:00 -0300 Subject: [PATCH 04/24] Add adjustments to scripts (libraries missing); added edgeR counts normalization --- scripts/edger_diff_gene.R | 27 ++++++++++++++++++++++----- scripts/impute_meta.R | 8 ++++---- scripts/metadata.R | 8 ++++++-- scripts/robust_pca.R | 6 +++--- scripts/tx_tx.R | 3 +++ 5 files changed, 38 insertions(+), 14 deletions(-) diff --git a/scripts/edger_diff_gene.R b/scripts/edger_diff_gene.R index c7c2ea9..529a3db 100644 --- a/scripts/edger_diff_gene.R +++ b/scripts/edger_diff_gene.R @@ -2,6 +2,8 @@ # GENE library(edgeR) +library(dplyr) +library(purrr) # Load metadata ----------------------------------------------------------- load("results/important_variables/ann.rda") @@ -14,9 +16,19 @@ load("results/txi/txi_gene.rda") # Differential expression ------------------------------------------------- -# Creating dds object with design matrix including the selected covariate ('rin' and 'ph') -y <- DGEList(counts = txi$counts, - group = ann$group) +# Creating DGElist object with design matrix including selected covariates ('rin' and 'ph'). +# See https://bioconductor.org/packages/release/bioc/vignettes/tximport/inst/doc/tximport.html#edgeR +counts <- txi$counts +norm_mat <- txi$length +norm_mat <- norm_mat/exp(rowMeans(log(norm_mat))) +norm_counts <- counts / norm_mat +eff_library_size <- calcNormFactors(norm_counts, method = "TMM") * colSums(norm_counts) +norm_mat <- sweep(norm_mat, 2, eff_library_size, "*") +norm_mat <- log(norm_mat) + +# Creating a DGEList object for use in edgeR. +y <- DGEList(counts, group = ann$group) +y <- scaleOffset(y, norm_mat) # Design matrix design <- model.matrix(~ 0 + ph + rin + group, data = ann) @@ -40,7 +52,7 @@ ct <- makeContrasts( # Filter low expression genes keep <- filterByExpr(y, group = y$samples$group) -y <- y[keep, , keep.lib.sizes = FALSE] +y <- y[keep,] # TMM normalization y <- calcNormFactors(y) @@ -74,4 +86,9 @@ map(comp, function(c) { }) -> lrt_comp names(lrt_comp) <- comp -save(df_edger_ph_rin_group_gene, lrt_comp, file = "results/diff_exp/edger_gene_rin_ph_diff.rda") \ No newline at end of file +if(!dir.exists("results/diff_exp/")) { + dir.create("results/diff_exp/") +} + +save(df_edger_ph_rin_group_gene, lrt_comp, file = "results/diff_exp/edger_gene_rin_ph_diff.rda") + diff --git a/scripts/impute_meta.R b/scripts/impute_meta.R index 2be92e5..955b9c2 100644 --- a/scripts/impute_meta.R +++ b/scripts/impute_meta.R @@ -60,10 +60,10 @@ ann_complete <- ann_complete %>% sum(sapply(ann_complete, function(i) sum(is.na(i)) )) == 0 # Scale continuos variables -ann_complete$age <- scale(ann_complete$age) -ann_complete$pmi <- scale(ann_complete$pmi) -ann_complete$rin <- scale(ann_complete$rin) -ann_complete$ph <- scale(ann_complete$ph) +ann_complete$age <- scale(ann_complete$age)[,1] +ann_complete$pmi <- scale(ann_complete$pmi)[,1] +ann_complete$rin <- scale(ann_complete$rin)[,1] +ann_complete$ph <- scale(ann_complete$ph)[,1] # Transform categorical data ann_complete$gender <- as.numeric(as.factor(ann_complete$gender)) diff --git a/scripts/metadata.R b/scripts/metadata.R index 2793e2c..3a672e1 100644 --- a/scripts/metadata.R +++ b/scripts/metadata.R @@ -22,11 +22,15 @@ ann <- ann %>% dplyr::select(sample_id, ph, rin, phenotype, gender, region, group) # Scale ph and rin -ann$ph <- scale(ann$ph) -ann$rin <- scale(ann$rin) +ann$ph <- scale(ann$ph)[,1] +ann$rin <- scale(ann$rin)[,1] rownames(ann) <- ann$sample_id ann$sample_id <- NULL +# Remove samples "SRR5961961" and "SRR5961809" that appeared as outliers on robust pca analysis +ann <- ann %>% + filter(!(rownames(ann) %in% c("SRR5961961", "SRR5961809"))) + # Save (this metadata will be used in all future models) save(ann, file = "results/important_variables/ann.rda") diff --git a/scripts/robust_pca.R b/scripts/robust_pca.R index 6d6edf4..4d867d8 100644 --- a/scripts/robust_pca.R +++ b/scripts/robust_pca.R @@ -9,11 +9,11 @@ library(DESeq2) # Load count table and annotation data load("results/txi/txi_gene.rda") -load("results/important_variables/ann.rda") +load("results/important_variables/ann_complete.rda") # DESeq2 object dds <- DESeqDataSetFromTximport(txi, - colData = ann, + colData = ann_complete, design = ~ group) v <- vst(dds, blind = F) @@ -25,7 +25,7 @@ pdf("results/plots_paper/robust_pca.pdf") plot(pc1) dev.off() -# The SRR5961961 sample is identified as divergent from others, and for this reason is excluded from +# The SRR5961961 and the SRR5961809 samples were considered outliers and removed from # downstream analyses. # plot(pc1$scores[,1], pc1$od) diff --git a/scripts/tx_tx.R b/scripts/tx_tx.R index 049e46a..01c3803 100644 --- a/scripts/tx_tx.R +++ b/scripts/tx_tx.R @@ -11,6 +11,9 @@ load("results/important_variables/ann.rda") # Read files files <- list.files(path = "data/kallisto/", pattern="tsv", recursive = TRUE, full.names = TRUE) files <- files[sapply(rownames(ann), function(x) grep(x, files))] + +# Samples to remove + names(files) <- rownames(ann) txi <- tximport(files = files, type = "kallisto", txOut = T) From 1ad3ef1e15b541a9b80ffa3c158aec6152269816 Mon Sep 17 00:00:00 2001 From: Iara Souza Date: Fri, 28 Apr 2023 10:53:04 -0300 Subject: [PATCH 05/24] Major changes to DGE. Rebuilt Figures 1, 2 and 3. --- gwas_intersection.csv | 14 + remaining_samples.sh | 39 + renv.lock | 225 +- results/networks/edges2 | 2135 --------------- results/networks/layout.csv | 574 ++++ results/networks/model_edges.txt | 2408 +++++++++++++++++ results/networks/model_nodes.txt | 574 ++++ results/networks/nodes2 | 661 ----- results/plots_paper/Table_1.ods | Bin 0 -> 55339 bytes results/tables/TAG.xlsx | Bin 0 -> 46822 bytes results/tables/gwas_intersection.csv | 14 + results/tables/intersect_by_type_and_gwas.csv | 1215 +++++++++ .../tables/intersect_by_type_and_gwas.xlsx | Bin 0 -> 61458 bytes .../intersect_regions_by_sex_female.csv | 679 +++++ .../intersect_regions_by_sex_female.xlsx | Bin 0 -> 46004 bytes .../tables/intersect_regions_by_sex_male.csv | 464 ++++ .../tables/intersect_regions_by_sex_male.xlsx | Bin 0 -> 33415 bytes results/tables/intersection_tables.xlsx | Bin 0 -> 32241 bytes results/tables/mdd_filtered.csv | 52 + results/tables/number_of_samples.xlsx | Bin 0 -> 6872 bytes results/tx_enrich/go_terms.csv | 22 + scripts/edger_diff_gene.R | 15 +- scripts/gwas_intersections.R | 92 +- scripts/network.R | 27 +- scripts/network_layout.R | 16 + scripts/organize_dge_dte_after_filtering.R | 4 +- scripts/outliers_edge_ppcseq_gene.R | 2 + scripts/plots.rmd | 43 +- 28 files changed, 6250 insertions(+), 3025 deletions(-) create mode 100644 gwas_intersection.csv create mode 100644 remaining_samples.sh delete mode 100644 results/networks/edges2 create mode 100644 results/networks/layout.csv create mode 100644 results/networks/model_edges.txt create mode 100644 results/networks/model_nodes.txt delete mode 100644 results/networks/nodes2 create mode 100644 results/plots_paper/Table_1.ods create mode 100644 results/tables/TAG.xlsx create mode 100644 results/tables/gwas_intersection.csv create mode 100644 results/tables/intersect_by_type_and_gwas.csv create mode 100644 results/tables/intersect_by_type_and_gwas.xlsx create mode 100644 results/tables/intersect_regions_by_sex_female.csv create mode 100644 results/tables/intersect_regions_by_sex_female.xlsx create mode 100644 results/tables/intersect_regions_by_sex_male.csv create mode 100644 results/tables/intersect_regions_by_sex_male.xlsx create mode 100644 results/tables/intersection_tables.xlsx create mode 100644 results/tables/mdd_filtered.csv create mode 100644 results/tables/number_of_samples.xlsx create mode 100644 results/tx_enrich/go_terms.csv create mode 100644 scripts/network_layout.R diff --git a/gwas_intersection.csv b/gwas_intersection.csv new file mode 100644 index 0000000..8359231 --- /dev/null +++ b/gwas_intersection.csv @@ -0,0 +1,14 @@ +association_id,variant_id,risk_allele,risk_frequency,genome_wide,pvalue,pvalue_description,range,beta_number,beta_direction,chromosome_name,chromosome_position,functional_class,ensembl_gene_name,hgnc_symbol,group,type +41136253,rs58621819,T,0.2097,FALSE,2e-10,NA,[1.01-1.02],NA,NA,11,65547359,intron_variant,ENSG00000168056,LTBP3,OFC_female,DGE +41136409,rs12923444,C,0.4375,FALSE,2e-24,NA,[1.02-1.03],NA,NA,16,21628389,intron_variant,ENSG00000197006,METTL9,OFC_female,DGE +41135995,rs10789214,T,0.5661,FALSE,4e-10,NA,[1.009-1.018],NA,NA,1,66681134,intron_variant,ENSG00000118473,SGIP1,OFC_female,DTE +41136026,rs17641524,C,0.7909,FALSE,8e-20,NA,[1.02-1.03],NA,NA,1,197735587,splice_region_variant,ENSG00000213047,DENND1B,Cg25_male,DTE +41136085,rs45510091,A,0.9472,FALSE,8e-21,NA,[1.037-1.057],NA,NA,4,122265238,intron_variant,ENSG00000138688,BLTP1,Cg25_male,DGE +30547745,rs10127497,T,0.1382,FALSE,1e-08,NA,[0.0064-0.013],0.0097,increase,1,66584461,intron_variant,ENSG00000118473,SGIP1,OFC_female,DTE +30547749,rs6679379,T,0.2875,FALSE,3e-08,NA,[0.0047-0.0097],0.0072,increase,1,66733473,non_coding_transcript_exon_variant,ENSG00000118473,SGIP1,OFC_female,DTE +30547797,rs12118513,A,0.2148,FALSE,1e-07,NA,[0.0049-0.0103],0.0076,decrease,1,197547956,intron_variant,ENSG00000213047,DENND1B,Cg25_male,DTE +30547801,rs17641524,T,0.2086,FALSE,2e-07,NA,[0.0048-0.0102],0.0075,decrease,1,197735587,splice_region_variant,ENSG00000213047,DENND1B,Cg25_male,DTE +30547485,rs10929355,G,0.4558,FALSE,6e-09,NA,[0.005-0.01],0.0075,decrease,2,15258840,intron_variant,ENSG00000151779,NBAS,OFC_female,DGE +64732910,rs2894699,T,0.4305,FALSE,4e-09,NA,[0.017-0.033],0.024859993,decrease,7,114419101,intron_variant,ENSG00000128573,FOXP2,Sub_male,DGE +64733014,rs7146581,T,0.2246,FALSE,2e-08,NA,[0.018-0.037],0.027423386,increase,14,102834735,intron_variant,ENSG00000131323,TRAF3,Nac_female,DTE +64733043,rs2369818,T,0.4386,FALSE,3e-08,NA,[0.015-0.031],0.023054866,increase,16,21602688,intron_variant,ENSG00000197006,METTL9,OFC_female,DGE diff --git a/remaining_samples.sh b/remaining_samples.sh new file mode 100644 index 0000000..a65496c --- /dev/null +++ b/remaining_samples.sh @@ -0,0 +1,39 @@ +curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/002/SRR5961862/SRR5961862_2.fastq.gz -o SRR5961862_2.fastq.gz +curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/003/SRR5961863/SRR5961863_2.fastq.gz -o SRR5961863_2.fastq.gz +curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/004/SRR5961864/SRR5961864_1.fastq.gz -o SRR5961864_1.fastq.gz +curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/004/SRR5961864/SRR5961864_2.fastq.gz -o SRR5961864_2.fastq.gz +curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/008/SRR5961938/SRR5961938_2.fastq.gz -o SRR5961938_2.fastq.gz +curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/007/SRR5961937/SRR5961937_1.fastq.gz -o SRR5961937_1.fastq.gz +curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/007/SRR5961937/SRR5961937_2.fastq.gz -o SRR5961937_2.fastq.gz +curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/002/SRR5961942/SRR5961942_1.fastq.gz -o SRR5961942_1.fastq.gz +curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/002/SRR5961942/SRR5961942_2.fastq.gz -o SRR5961942_2.fastq.gz +curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/000/SRR5961940/SRR5961940_1.fastq.gz -o SRR5961940_1.fastq.gz +curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/000/SRR5961940/SRR5961940_2.fastq.gz -o SRR5961940_2.fastq.gz +curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/003/SRR5961943/SRR5961943_1.fastq.gz -o SRR5961943_1.fastq.gz +curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/003/SRR5961943/SRR5961943_2.fastq.gz -o SRR5961943_2.fastq.gz +curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/004/SRR5961944/SRR5961944_1.fastq.gz -o SRR5961944_1.fastq.gz +curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/004/SRR5961944/SRR5961944_2.fastq.gz -o SRR5961944_2.fastq.gz +curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/006/SRR5961946/SRR5961946_1.fastq.gz -o SRR5961946_1.fastq.gz +curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/006/SRR5961946/SRR5961946_2.fastq.gz -o SRR5961946_2.fastq.gz +curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/005/SRR5961945/SRR5961945_1.fastq.gz -o SRR5961945_1.fastq.gz +curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/005/SRR5961945/SRR5961945_2.fastq.gz -o SRR5961945_2.fastq.gz +curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/007/SRR5961947/SRR5961947_1.fastq.gz -o SRR5961947_1.fastq.gz +curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/007/SRR5961947/SRR5961947_2.fastq.gz -o SRR5961947_2.fastq.gz +curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/008/SRR5961948/SRR5961948_1.fastq.gz -o SRR5961948_1.fastq.gz +curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/008/SRR5961948/SRR5961948_2.fastq.gz -o SRR5961948_2.fastq.gz +curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/009/SRR5961949/SRR5961949_1.fastq.gz -o SRR5961949_1.fastq.gz +curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/009/SRR5961949/SRR5961949_2.fastq.gz -o SRR5961949_2.fastq.gz +curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/000/SRR5961950/SRR5961950_1.fastq.gz -o SRR5961950_1.fastq.gz +curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/000/SRR5961950/SRR5961950_2.fastq.gz -o SRR5961950_2.fastq.gz +curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/001/SRR5961951/SRR5961951_1.fastq.gz -o SRR5961951_1.fastq.gz +curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/001/SRR5961951/SRR5961951_2.fastq.gz -o SRR5961951_2.fastq.gz +curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/002/SRR5961952/SRR5961952_1.fastq.gz -o SRR5961952_1.fastq.gz +curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/002/SRR5961952/SRR5961952_2.fastq.gz -o SRR5961952_2.fastq.gz +curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/003/SRR5961953/SRR5961953_2.fastq.gz -o SRR5961953_2.fastq.gz +curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/004/SRR5961954/SRR5961954_1.fastq.gz -o SRR5961954_1.fastq.gz +curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/004/SRR5961954/SRR5961954_2.fastq.gz -o SRR5961954_2.fastq.gz +curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/005/SRR5961955/SRR5961955_1.fastq.gz -o SRR5961955_1.fastq.gz +curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/005/SRR5961955/SRR5961955_2.fastq.gz -o SRR5961955_2.fastq.gz +curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/006/SRR5961956/SRR5961956_1.fastq.gz -o SRR5961956_1.fastq.gz +curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/006/SRR5961956/SRR5961956_2.fastq.gz -o SRR5961956_2.fastq.gz +curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/007/SRR5961957/SRR5961957_1.fastq.gz -o SRR5961957_1.fastq.gz diff --git a/renv.lock b/renv.lock index ec24f2c..5e7a305 100644 --- a/renv.lock +++ b/renv.lock @@ -905,6 +905,21 @@ "S4Vectors" ] }, + "TreeAndLeaf": { + "Package": "TreeAndLeaf", + "Version": "1.6.1", + "Source": "Bioconductor", + "git_url": "https://git.bioconductor.org/packages/TreeAndLeaf", + "git_branch": "RELEASE_3_14", + "git_last_commit": "171d519", + "git_last_commit_date": "2021-10-27", + "Hash": "b8f10ab9082a4c3cbcc136006706ef4e", + "Requirements": [ + "RedeR", + "ape", + "igraph" + ] + }, "UpSetR": { "Package": "UpSetR", "Version": "1.4.0", @@ -1181,14 +1196,6 @@ "Hash": "0baa960e3b49c6176a4f42addcbacc59", "Requirements": [] }, - "brio": { - "Package": "brio", - "Version": "1.1.3", - "Source": "Repository", - "Repository": "CRAN", - "Hash": "976cf154dfb043c012d87cddd8bca363", - "Requirements": [] - }, "broom": { "Package": "broom", "Version": "0.7.11", @@ -1335,13 +1342,11 @@ }, "cli": { "Package": "cli", - "Version": "3.1.0", + "Version": "3.6.1", "Source": "Repository", "Repository": "CRAN", - "Hash": "66a3834e54593c89d8beefb312347e58", - "Requirements": [ - "glue" - ] + "Hash": "89e6d8219950eac806ae0c489052048a", + "Requirements": [] }, "clipr": { "Package": "clipr", @@ -1410,14 +1415,6 @@ "Hash": "0f22be39ec1d141fd03683c06f3a6e67", "Requirements": [] }, - "concatenate": { - "Package": "concatenate", - "Version": "1.0.0", - "Source": "Repository", - "Repository": "CRAN", - "Hash": "94b165d30bf16386c2f096409d502463", - "Requirements": [] - }, "conquer": { "Package": "conquer", "Version": "1.2.1", @@ -1516,13 +1513,13 @@ }, "desc": { "Package": "desc", - "Version": "1.4.0", + "Version": "1.4.2", "Source": "Repository", "Repository": "CRAN", - "Hash": "28763d08fadd0b733e3cee9dab4e12fe", + "Hash": "6b9602c7ebbe87101a9c8edb6e8b6d21", "Requirements": [ "R6", - "crayon", + "cli", "rprojroot" ] }, @@ -1534,16 +1531,6 @@ "Hash": "fe1a3788cf243db3eca07ae661860793", "Requirements": [] }, - "diffobj": { - "Package": "diffobj", - "Version": "0.3.5", - "Source": "Repository", - "Repository": "CRAN", - "Hash": "bcaa8b95f8d7d01a5dedfd959ce88ab8", - "Requirements": [ - "crayon" - ] - }, "digest": { "Package": "digest", "Version": "0.6.29", @@ -2156,12 +2143,13 @@ "Package": "ggtree", "Version": "3.2.1", "Source": "Bioconductor", + "RemoteType": "bioconductor", "Remotes": "GuangchuangYu/treeio", "git_url": "https://git.bioconductor.org/packages/ggtree", "git_branch": "RELEASE_3_14", "git_last_commit": "d3747e6", "git_last_commit_date": "2021-11-14", - "Hash": "f156c85173024c88e2fdfd63ccca3fd7", + "Hash": "5711c057a04e53ed1c70909939dd9ad9", "Requirements": [ "ape", "aplot", @@ -2319,33 +2307,6 @@ "Hash": "2ace6c4a06297d0b364e0444384a2b82", "Requirements": [] }, - "gwasrapidd": { - "Package": "gwasrapidd", - "Version": "0.99.12", - "Source": "Repository", - "Repository": "CRAN", - "Hash": "56be6fbe33e1892fea54591d36881510", - "Requirements": [ - "assertthat", - "concatenate", - "dplyr", - "glue", - "httr", - "jsonlite", - "lubridate", - "magrittr", - "pingr", - "plyr", - "progress", - "purrr", - "rlang", - "stringr", - "testthat", - "tibble", - "tidyr", - "urltools" - ] - }, "haven": { "Package": "haven", "Version": "2.4.3", @@ -2901,10 +2862,10 @@ }, "openssl": { "Package": "openssl", - "Version": "1.4.6", + "Version": "2.0.6", "Source": "Repository", "Repository": "CRAN", - "Hash": "69fdf291af288f32fd4cd93315084ea8", + "Hash": "0f7cd2962e3044bb940cca4f4b5cecbe", "Requirements": [ "askpass" ] @@ -3017,16 +2978,6 @@ "vctrs" ] }, - "pingr": { - "Package": "pingr", - "Version": "2.0.1", - "Source": "Repository", - "Repository": "CRAN", - "Hash": "e293e79be42ffd336d938937fd3017fb", - "Requirements": [ - "processx" - ] - }, "pkgbuild": { "Package": "pkgbuild", "Version": "1.3.1", @@ -3052,22 +3003,6 @@ "Hash": "01f28d4278f15c76cddbea05899c5d6f", "Requirements": [] }, - "pkgload": { - "Package": "pkgload", - "Version": "1.2.4", - "Source": "Repository", - "Repository": "CRAN", - "Hash": "7533cd805940821bf23eaf3c8d4c1735", - "Requirements": [ - "cli", - "crayon", - "desc", - "rlang", - "rprojroot", - "rstudioapi", - "withr" - ] - }, "plogr": { "Package": "plogr", "Version": "0.2.0", @@ -3152,14 +3087,6 @@ "tidyr" ] }, - "praise": { - "Package": "praise", - "Version": "1.0.0", - "Source": "Repository", - "Repository": "CRAN", - "Hash": "a555924add98c99d2f411e37e7d25e9f", - "Requirements": [] - }, "prettyunits": { "Package": "prettyunits", "Version": "1.1.1", @@ -3291,6 +3218,14 @@ "reshape2" ] }, + "rJava": { + "Package": "rJava", + "Version": "1.0-6", + "Source": "Repository", + "Repository": "CRAN", + "Hash": "0415819f6baa75d86d52483f7292b623", + "Requirements": [] + }, "ranger": { "Package": "ranger", "Version": "0.13.1", @@ -3452,10 +3387,10 @@ }, "rlang": { "Package": "rlang", - "Version": "0.4.12", + "Version": "1.1.0", "Source": "Repository", "Repository": "CRAN", - "Hash": "0879f5388fe6e4d56d7ef0b7ccb031e5", + "Hash": "dc079ccd156cde8647360f473c1fa718", "Requirements": [] }, "rmarkdown": { @@ -3828,34 +3763,6 @@ "Hash": "fd792ceac77f96b647fa8d6e1788969a", "Requirements": [] }, - "testthat": { - "Package": "testthat", - "Version": "3.1.1", - "Source": "Repository", - "Repository": "CRAN", - "Hash": "2a5c5646456762131ce40272964599d3", - "Requirements": [ - "R6", - "brio", - "callr", - "cli", - "crayon", - "desc", - "digest", - "ellipsis", - "evaluate", - "jsonlite", - "lifecycle", - "magrittr", - "pkgload", - "praise", - "processx", - "ps", - "rlang", - "waldo", - "withr" - ] - }, "tibble": { "Package": "tibble", "Version": "3.1.6", @@ -4040,16 +3947,6 @@ "tidytree" ] }, - "triebeard": { - "Package": "triebeard", - "Version": "0.3.0", - "Source": "Repository", - "Repository": "CRAN", - "Hash": "847a9d113b78baca4a9a8639609ea228", - "Requirements": [ - "Rcpp" - ] - }, "tweenr": { "Package": "tweenr", "Version": "1.0.2", @@ -4111,17 +4008,6 @@ "cpp11" ] }, - "urltools": { - "Package": "urltools", - "Version": "1.7.3", - "Source": "Repository", - "Repository": "CRAN", - "Hash": "e86a704261a105f4703f653e05defa3e", - "Requirements": [ - "Rcpp", - "triebeard" - ] - }, "utf8": { "Package": "utf8", "Version": "1.2.2", @@ -4205,28 +4091,12 @@ "withr" ] }, - "waldo": { - "Package": "waldo", - "Version": "0.3.1", - "Source": "Repository", - "Repository": "CRAN", - "Hash": "ad8cfff5694ac5b3c354f8f2044bd976", - "Requirements": [ - "cli", - "diffobj", - "fansi", - "glue", - "rematch2", - "rlang", - "tibble" - ] - }, "withr": { "Package": "withr", - "Version": "2.4.3", + "Version": "2.5.0", "Source": "Repository", "Repository": "CRAN", - "Hash": "a376b424c4817cda4920bbbeb3364e85", + "Hash": "c0e49a9760983e81e55cdd9be92e7182", "Requirements": [] }, "xfun": { @@ -4237,6 +4107,27 @@ "Hash": "e2e5fb1a74fbb68b27d6efc5372635dc", "Requirements": [] }, + "xlsx": { + "Package": "xlsx", + "Version": "0.6.5", + "Source": "Repository", + "Repository": "CRAN", + "Hash": "d24d579f59a3b6da1e1cf4660425443e", + "Requirements": [ + "rJava", + "xlsxjars" + ] + }, + "xlsxjars": { + "Package": "xlsxjars", + "Version": "0.6.1", + "Source": "Repository", + "Repository": "CRAN", + "Hash": "4c4b3bc29a916f33f1298dd951133351", + "Requirements": [ + "rJava" + ] + }, "xml2": { "Package": "xml2", "Version": "1.3.3", diff --git a/results/networks/edges2 b/results/networks/edges2 deleted file mode 100644 index e167bbd..0000000 --- a/results/networks/edges2 +++ /dev/null @@ -1,2135 +0,0 @@ -node_a node_b weight -0 1 0.0 -0 2 0.0 -0 3 0.0 -0 4 0.0 -0 5 0.0 -0 6 0.0 -0 7 0.0 -0 8 0.0 -0 9 0.0 -0 10 0.0 -11 12 0.0 -13 14 0.0 -13 15 0.0 -13 16 0.0 -13 17 0.0 -13 18 0.0 -13 19 0.0 -13 20 0.0 -13 21 0.0 -13 22 0.0 -13 23 0.0 -13 24 0.0 -13 25 0.0 -13 26 0.0 -13 27 0.0 -13 28 0.0 -29 30 0.0 -31 32 0.0 -33 34 0.0 -35 36 0.0 -37 38 0.0 -37 39 0.0 -37 40 0.0 -37 41 0.0 -37 42 0.0 -37 43 0.0 -37 44 0.0 -37 45 0.0 -46 47 0.0 -48 49 0.0 -48 50 0.0 -48 51 0.0 -48 52 0.0 -34 48 0.0 -48 53 0.0 -48 54 0.0 -48 55 0.0 -48 56 0.0 -48 57 0.0 -58 59 0.0 -58 60 0.0 -58 61 0.0 -62 63 0.0 -62 64 0.0 -62 65 0.0 -66 67 0.0 -66 68 0.0 -65 66 0.0 -66 69 0.0 -70 71 0.0 -70 72 0.0 -70 73 0.0 -70 74 0.0 -70 75 0.0 -70 76 0.0 -70 77 0.0 -70 78 0.0 -70 79 0.0 -80 81 0.0 -80 82 0.0 -80 83 0.0 -80 84 0.0 -80 85 0.0 -53 55 0.0 -53 86 0.0 -53 87 0.0 -34 53 0.0 -88 89 0.0 -88 90 0.0 -88 91 0.0 -88 92 0.0 -88 93 0.0 -88 94 0.0 -88 95 0.0 -88 96 0.0 -88 97 0.0 -88 98 0.0 -15 88 0.0 -99 100 0.0 -99 101 0.0 -99 102 0.0 -99 103 0.0 -99 104 0.0 -99 105 0.0 -99 106 0.0 -107 108 0.0 -109 110 0.0 -109 111 0.0 -109 112 0.0 -109 113 0.0 -114 115 0.0 -114 116 0.0 -60 114 0.0 -114 117 0.0 -114 118 0.0 -86 119 0.0 -120 121 0.0 -120 122 0.0 -120 123 0.0 -120 124 0.0 -120 125 0.0 -120 126 0.0 -120 127 0.0 -120 128 0.0 -65 120 0.0 -15 120 0.0 -120 129 0.0 -120 130 0.0 -120 131 0.0 -120 132 0.0 -69 120 0.0 -133 134 0.0 -133 135 0.0 -133 136 0.0 -137 138 0.0 -69 139 0.0 -139 140 0.0 -139 141 0.0 -123 139 0.0 -139 142 0.0 -139 143 0.0 -139 144 0.0 -139 145 0.0 -139 146 0.0 -139 147 0.0 -139 148 0.0 -139 149 0.0 -139 150 0.0 -139 151 0.0 -139 152 0.0 -59 139 0.0 -139 153 0.0 -139 154 0.0 -139 155 0.0 -139 156 0.0 -139 157 0.0 -139 158 0.0 -139 159 0.0 -139 160 0.0 -139 161 0.0 -139 162 0.0 -163 164 0.0 -163 165 0.0 -163 166 0.0 -167 168 0.0 -167 169 0.0 -16 167 0.0 -14 167 0.0 -170 171 0.0 -170 172 0.0 -32 173 0.0 -174 175 0.0 -176 177 0.0 -4 5 0.0 -5 178 0.0 -5 7 0.0 -5 10 0.0 -5 6 0.0 -5 9 0.0 -5 8 0.0 -5 179 0.0 -5 180 0.0 -5 181 0.0 -3 182 0.0 -86 182 0.0 -183 184 0.0 -150 183 0.0 -183 185 0.0 -151 183 0.0 -183 186 0.0 -183 187 0.0 -183 188 0.0 -183 189 0.0 -183 190 0.0 -183 191 0.0 -183 192 0.0 -30 183 0.0 -144 183 0.0 -183 193 0.0 -194 195 0.0 -44 196 0.0 -197 198 0.0 -19 197 0.0 -197 199 0.0 -197 200 0.0 -197 201 0.0 -14 197 0.0 -16 197 0.0 -202 203 0.0 -202 204 0.0 -69 202 0.0 -202 205 0.0 -202 206 0.0 -65 202 0.0 -202 207 0.0 -60 202 0.0 -202 208 0.0 -202 209 0.0 -202 210 0.0 -202 211 0.0 -191 202 0.0 -212 213 0.0 -47 212 0.0 -118 214 0.0 -215 216 0.0 -57 217 0.0 -113 218 0.0 -96 213 0.0 -91 96 0.0 -96 98 0.0 -92 96 0.0 -96 97 0.0 -93 96 0.0 -15 96 0.0 -49 96 0.0 -96 219 0.0 -220 221 0.0 -101 220 0.0 -220 222 0.0 -220 223 0.0 -220 224 0.0 -102 220 0.0 -220 225 0.0 -220 226 0.0 -131 220 0.0 -220 227 0.0 -220 228 0.0 -220 229 0.0 -49 220 0.0 -86 220 0.0 -87 220 0.0 -220 230 0.0 -220 231 0.0 -89 211 0.0 -89 232 0.0 -89 162 0.0 -15 89 0.0 -89 223 0.0 -89 97 0.0 -89 127 0.0 -89 233 0.0 -234 235 0.0 -14 199 0.0 -16 199 0.0 -236 237 0.0 -15 236 0.0 -236 238 0.0 -228 236 0.0 -3 239 0.0 -239 240 0.0 -239 241 0.0 -67 68 0.0 -68 179 0.0 -68 181 0.0 -68 180 0.0 -68 242 0.0 -125 221 0.0 -125 222 0.0 -243 244 0.0 -243 245 0.0 -75 246 0.0 -155 246 0.0 -246 247 0.0 -246 248 0.0 -216 246 0.0 -246 249 0.0 -73 246 0.0 -246 250 0.0 -211 246 0.0 -246 251 0.0 -246 252 0.0 -191 246 0.0 -246 253 0.0 -74 246 0.0 -254 255 0.0 -39 149 0.0 -39 256 0.0 -39 257 0.0 -39 150 0.0 -39 258 0.0 -39 259 0.0 -39 260 0.0 -39 63 0.0 -39 261 0.0 -39 262 0.0 -39 45 0.0 -39 43 0.0 -39 263 0.0 -38 39 0.0 -39 44 0.0 -39 40 0.0 -39 41 0.0 -115 124 0.0 -115 123 0.0 -63 122 0.0 -264 265 0.0 -264 266 0.0 -264 267 0.0 -268 269 0.0 -268 270 0.0 -124 268 0.0 -268 271 0.0 -126 268 0.0 -268 272 0.0 -268 273 0.0 -268 274 0.0 -65 268 0.0 -67 268 0.0 -275 276 0.0 -225 275 0.0 -275 277 0.0 -275 278 0.0 -275 279 0.0 -104 275 0.0 -280 281 0.0 -15 282 0.0 -81 282 0.0 -101 283 0.0 -101 106 0.0 -50 284 0.0 -284 285 0.0 -100 286 0.0 -100 263 0.0 -238 287 0.0 -288 289 0.0 -288 290 0.0 -152 288 0.0 -288 291 0.0 -205 288 0.0 -69 288 0.0 -288 292 0.0 -251 288 0.0 -204 288 0.0 -288 293 0.0 -73 288 0.0 -250 288 0.0 -247 288 0.0 -252 288 0.0 -294 295 0.0 -294 296 0.0 -294 297 0.0 -298 299 0.0 -59 298 0.0 -154 298 0.0 -161 298 0.0 -162 298 0.0 -158 298 0.0 -103 300 0.0 -102 103 0.0 -103 106 0.0 -103 301 0.0 -118 302 0.0 -222 303 0.0 -104 304 0.0 -104 305 0.0 -104 306 0.0 -104 307 0.0 -104 308 0.0 -104 309 0.0 -104 127 0.0 -15 104 0.0 -104 310 0.0 -104 276 0.0 -104 311 0.0 -104 312 0.0 -104 313 0.0 -104 314 0.0 -104 315 0.0 -102 104 0.0 -104 316 0.0 -104 106 0.0 -104 281 0.0 -104 317 0.0 -318 319 0.0 -113 320 0.0 -86 113 0.0 -23 124 0.0 -23 321 0.0 -23 322 0.0 -15 23 0.0 -17 23 0.0 -19 23 0.0 -23 27 0.0 -23 323 0.0 -23 324 0.0 -86 325 0.0 -77 315 0.0 -79 315 0.0 -315 326 0.0 -69 315 0.0 -65 315 0.0 -315 327 0.0 -209 328 0.0 -329 330 0.0 -331 332 0.0 -227 333 0.0 -227 278 0.0 -227 334 0.0 -335 336 0.0 -15 335 0.0 -41 337 0.0 -45 337 0.0 -43 337 0.0 -131 157 0.0 -131 338 0.0 -131 231 0.0 -15 131 0.0 -131 132 0.0 -131 339 0.0 -131 340 0.0 -341 342 0.0 -87 341 0.0 -51 341 0.0 -341 343 0.0 -15 277 0.0 -277 344 0.0 -277 345 0.0 -49 277 0.0 -277 346 0.0 -277 347 0.0 -277 348 0.0 -277 336 0.0 -277 349 0.0 -277 279 0.0 -276 277 0.0 -51 350 0.0 -350 351 0.0 -69 126 0.0 -126 352 0.0 -126 353 0.0 -126 354 0.0 -260 355 0.0 -263 355 0.0 -355 356 0.0 -195 355 0.0 -262 357 0.0 -279 332 0.0 -15 279 0.0 -276 279 0.0 -279 358 0.0 -279 359 0.0 -279 347 0.0 -56 279 0.0 -279 360 0.0 -279 348 0.0 -361 362 0.0 -363 364 0.0 -152 354 0.0 -145 354 0.0 -158 354 0.0 -156 354 0.0 -142 354 0.0 -354 365 0.0 -59 354 0.0 -353 354 0.0 -352 354 0.0 -216 366 0.0 -187 216 0.0 -77 216 0.0 -72 190 0.0 -72 276 0.0 -72 159 0.0 -205 367 0.0 -291 367 0.0 -367 368 0.0 -367 369 0.0 -4 9 0.0 -7 9 0.0 -6 9 0.0 -8 9 0.0 -9 86 0.0 -9 10 0.0 -124 370 0.0 -228 334 0.0 -228 371 0.0 -228 372 0.0 -228 238 0.0 -15 228 0.0 -228 319 0.0 -86 228 0.0 -228 373 0.0 -110 374 0.0 -374 375 0.0 -313 374 0.0 -374 376 0.0 -171 374 0.0 -374 377 0.0 -244 245 0.0 -7 59 0.0 -7 151 0.0 -7 146 0.0 -7 156 0.0 -7 155 0.0 -7 180 0.0 -4 7 0.0 -2 7 0.0 -7 10 0.0 -7 8 0.0 -6 7 0.0 -238 373 0.0 -319 373 0.0 -77 285 0.0 -77 378 0.0 -77 379 0.0 -74 77 0.0 -77 326 0.0 -77 211 0.0 -77 79 0.0 -336 380 0.0 -336 371 0.0 -157 336 0.0 -55 177 0.0 -177 381 0.0 -108 382 0.0 -383 384 0.0 -79 378 0.0 -378 379 0.0 -74 378 0.0 -378 385 0.0 -326 378 0.0 -211 378 0.0 -274 386 0.0 -274 387 0.0 -274 388 0.0 -15 274 0.0 -209 274 0.0 -65 274 0.0 -274 389 0.0 -390 391 0.0 -392 393 0.0 -75 191 0.0 -75 154 0.0 -74 75 0.0 -75 290 0.0 -75 211 0.0 -75 247 0.0 -75 292 0.0 -73 75 0.0 -75 250 0.0 -394 395 0.0 -158 385 0.0 -16 385 0.0 -14 385 0.0 -385 396 0.0 -82 84 0.0 -84 85 0.0 -83 84 0.0 -15 397 0.0 -132 397 0.0 -397 398 0.0 -397 399 0.0 -128 397 0.0 -127 397 0.0 -143 201 0.0 -146 201 0.0 -145 201 0.0 -151 201 0.0 -147 201 0.0 -152 201 0.0 -142 201 0.0 -59 201 0.0 -148 201 0.0 -149 201 0.0 -201 365 0.0 -150 201 0.0 -158 201 0.0 -154 201 0.0 -14 201 0.0 -201 257 0.0 -198 201 0.0 -15 201 0.0 -157 201 0.0 -16 201 0.0 -400 401 0.0 -147 402 0.0 -147 403 0.0 -147 192 0.0 -147 191 0.0 -147 299 0.0 -147 189 0.0 -144 147 0.0 -147 404 0.0 -147 405 0.0 -147 406 0.0 -147 155 0.0 -147 157 0.0 -143 147 0.0 -147 156 0.0 -59 147 0.0 -142 147 0.0 -146 147 0.0 -147 148 0.0 -147 151 0.0 -145 147 0.0 -147 257 0.0 -147 158 0.0 -147 365 0.0 -147 149 0.0 -147 150 0.0 -147 154 0.0 -147 152 0.0 -45 61 0.0 -45 407 0.0 -45 408 0.0 -45 409 0.0 -45 164 0.0 -45 63 0.0 -40 45 0.0 -45 410 0.0 -41 45 0.0 -38 45 0.0 -42 45 0.0 -43 45 0.0 -44 45 0.0 -380 411 0.0 -224 412 0.0 -224 324 0.0 -195 224 0.0 -102 224 0.0 -205 224 0.0 -224 413 0.0 -27 224 0.0 -414 415 0.0 -276 344 0.0 -344 416 0.0 -344 417 0.0 -344 418 0.0 -344 345 0.0 -344 419 0.0 -179 344 0.0 -50 420 0.0 -420 421 0.0 -420 422 0.0 -293 423 0.0 -158 423 0.0 -146 423 0.0 -145 423 0.0 -142 423 0.0 -405 423 0.0 -152 423 0.0 -151 423 0.0 -150 423 0.0 -143 423 0.0 -149 423 0.0 -148 423 0.0 -155 423 0.0 -59 423 0.0 -257 423 0.0 -156 423 0.0 -365 423 0.0 -154 423 0.0 -157 423 0.0 -278 334 0.0 -319 334 0.0 -157 334 0.0 -334 424 0.0 -276 309 0.0 -307 309 0.0 -425 426 0.0 -425 427 0.0 -229 425 0.0 -425 428 0.0 -333 425 0.0 -429 430 0.0 -429 431 0.0 -432 433 0.0 -82 83 0.0 -82 85 0.0 -233 434 0.0 -158 352 0.0 -16 158 0.0 -73 158 0.0 -158 211 0.0 -158 435 0.0 -61 158 0.0 -158 436 0.0 -158 402 0.0 -90 158 0.0 -158 379 0.0 -60 158 0.0 -158 250 0.0 -15 158 0.0 -69 158 0.0 -158 406 0.0 -124 158 0.0 -158 299 0.0 -158 191 0.0 -158 161 0.0 -123 158 0.0 -153 158 0.0 -158 404 0.0 -158 405 0.0 -158 162 0.0 -158 160 0.0 -142 158 0.0 -154 158 0.0 -158 365 0.0 -145 158 0.0 -146 158 0.0 -157 158 0.0 -152 158 0.0 -155 158 0.0 -148 158 0.0 -150 158 0.0 -151 158 0.0 -158 257 0.0 -143 158 0.0 -59 158 0.0 -149 158 0.0 -156 158 0.0 -295 297 0.0 -208 437 0.0 -437 438 0.0 -437 439 0.0 -440 441 0.0 -440 442 0.0 -15 440 0.0 -440 443 0.0 -56 444 0.0 -445 446 0.0 -311 447 0.0 -311 317 0.0 -102 311 0.0 -311 316 0.0 -305 311 0.0 -311 312 0.0 -187 190 0.0 -184 190 0.0 -189 190 0.0 -190 192 0.0 -144 190 0.0 -417 418 0.0 -179 418 0.0 -448 449 0.0 -242 448 0.0 -265 266 0.0 -265 267 0.0 -345 450 0.0 -417 450 0.0 -416 450 0.0 -4 450 0.0 -352 450 0.0 -450 451 0.0 -450 452 0.0 -453 454 0.0 -453 455 0.0 -427 453 0.0 -453 456 0.0 -330 453 0.0 -187 188 0.0 -187 189 0.0 -187 457 0.0 -187 192 0.0 -187 253 0.0 -187 366 0.0 -30 187 0.0 -144 187 0.0 -187 193 0.0 -144 458 0.0 -458 459 0.0 -458 460 0.0 -458 461 0.0 -285 458 0.0 -124 462 0.0 -67 415 0.0 -54 67 0.0 -266 267 0.0 -123 155 0.0 -112 123 0.0 -123 211 0.0 -123 192 0.0 -123 463 0.0 -123 276 0.0 -123 250 0.0 -81 123 0.0 -73 123 0.0 -59 123 0.0 -123 143 0.0 -123 191 0.0 -123 464 0.0 -123 152 0.0 -123 156 0.0 -123 465 0.0 -123 142 0.0 -123 148 0.0 -65 123 0.0 -123 151 0.0 -123 146 0.0 -123 145 0.0 -69 123 0.0 -123 149 0.0 -123 154 0.0 -123 157 0.0 -123 124 0.0 -439 466 0.0 -439 467 0.0 -439 468 0.0 -439 469 0.0 -438 439 0.0 -15 22 0.0 -22 25 0.0 -20 22 0.0 -443 470 0.0 -443 471 0.0 -398 443 0.0 -442 443 0.0 -15 443 0.0 -65 409 0.0 -209 409 0.0 -433 472 0.0 -41 387 0.0 -41 473 0.0 -41 260 0.0 -41 258 0.0 -41 474 0.0 -41 262 0.0 -41 475 0.0 -41 259 0.0 -41 261 0.0 -41 410 0.0 -41 63 0.0 -41 43 0.0 -41 263 0.0 -40 41 0.0 -38 41 0.0 -41 44 0.0 -476 477 0.0 -225 476 0.0 -92 478 0.0 -92 252 0.0 -92 471 0.0 -92 479 0.0 -92 310 0.0 -74 92 0.0 -92 211 0.0 -73 92 0.0 -92 250 0.0 -92 291 0.0 -92 98 0.0 -92 95 0.0 -92 94 0.0 -15 92 0.0 -91 92 0.0 -92 97 0.0 -92 93 0.0 -86 338 0.0 -1 442 0.0 -442 480 0.0 -332 442 0.0 -15 442 0.0 -442 481 0.0 -179 181 0.0 -181 482 0.0 -178 181 0.0 -180 181 0.0 -483 484 0.0 -124 142 0.0 -73 124 0.0 -124 250 0.0 -124 317 0.0 -124 463 0.0 -124 406 0.0 -124 211 0.0 -124 151 0.0 -124 276 0.0 -124 152 0.0 -124 143 0.0 -81 124 0.0 -124 156 0.0 -124 146 0.0 -124 464 0.0 -124 148 0.0 -124 149 0.0 -65 124 0.0 -124 465 0.0 -124 154 0.0 -124 157 0.0 -69 124 0.0 -485 486 0.0 -225 485 0.0 -485 487 0.0 -291 485 0.0 -165 488 0.0 -348 489 0.0 -253 490 0.0 -65 484 0.0 -65 406 0.0 -65 411 0.0 -65 235 0.0 -65 157 0.0 -65 436 0.0 -63 65 0.0 -65 69 0.0 -65 209 0.0 -435 491 0.0 -191 491 0.0 -30 162 0.0 -30 148 0.0 -30 185 0.0 -30 184 0.0 -30 492 0.0 -30 457 0.0 -30 156 0.0 -30 144 0.0 -30 192 0.0 -30 200 0.0 -30 193 0.0 -30 191 0.0 -30 59 0.0 -426 493 0.0 -238 426 0.0 -494 495 0.0 -271 496 0.0 -118 481 0.0 -136 184 0.0 -368 369 0.0 -368 487 0.0 -291 368 0.0 -47 497 0.0 -497 498 0.0 -497 499 0.0 -497 500 0.0 -410 474 0.0 -473 474 0.0 -63 474 0.0 -179 482 0.0 -180 482 0.0 -486 487 0.0 -291 486 0.0 -310 324 0.0 -73 324 0.0 -102 324 0.0 -324 501 0.0 -324 477 0.0 -324 412 0.0 -324 502 0.0 -49 503 0.0 -503 504 0.0 -127 463 0.0 -15 127 0.0 -127 505 0.0 -127 506 0.0 -127 507 0.0 -127 128 0.0 -127 399 0.0 -127 398 0.0 -127 132 0.0 -86 508 0.0 -15 146 0.0 -15 479 0.0 -15 404 0.0 -15 257 0.0 -15 155 0.0 -15 145 0.0 -15 142 0.0 -15 148 0.0 -15 152 0.0 -15 150 0.0 -15 156 0.0 -15 151 0.0 -15 149 0.0 -15 405 0.0 -15 365 0.0 -15 20 0.0 -15 18 0.0 -15 81 0.0 -15 509 0.0 -15 510 0.0 -15 511 0.0 -15 321 0.0 -15 16 0.0 -15 507 0.0 -15 27 0.0 -15 19 0.0 -14 15 0.0 -15 49 0.0 -15 17 0.0 -15 153 0.0 -15 463 0.0 -15 273 0.0 -15 61 0.0 -15 322 0.0 -15 332 0.0 -15 128 0.0 -15 198 0.0 -15 399 0.0 -15 132 0.0 -15 94 0.0 -15 143 0.0 -15 398 0.0 -15 59 0.0 -15 154 0.0 -15 69 0.0 -15 512 0.0 -15 340 0.0 -15 502 0.0 -15 225 0.0 -15 98 0.0 -15 159 0.0 -15 348 0.0 -15 238 0.0 -15 513 0.0 -15 514 0.0 -15 28 0.0 -15 102 0.0 -15 91 0.0 -15 499 0.0 -15 339 0.0 -15 306 0.0 -15 93 0.0 -15 141 0.0 -15 121 0.0 -15 97 0.0 -90 240 0.0 -90 251 0.0 -90 257 0.0 -90 152 0.0 -90 154 0.0 -90 405 0.0 -90 143 0.0 -90 157 0.0 -59 90 0.0 -90 156 0.0 -90 155 0.0 -90 149 0.0 -90 365 0.0 -90 145 0.0 -90 142 0.0 -90 150 0.0 -90 148 0.0 -90 146 0.0 -464 515 0.0 -515 516 0.0 -515 517 0.0 -435 518 0.0 -348 360 0.0 -241 349 0.0 -346 349 0.0 -276 349 0.0 -343 438 0.0 -343 468 0.0 -343 466 0.0 -343 430 0.0 -343 431 0.0 -343 504 0.0 -343 519 0.0 -343 520 0.0 -51 343 0.0 -87 343 0.0 -16 289 0.0 -168 289 0.0 -289 293 0.0 -289 521 0.0 -289 522 0.0 -289 523 0.0 -241 276 0.0 -164 175 0.0 -44 164 0.0 -164 410 0.0 -63 164 0.0 -164 291 0.0 -164 364 0.0 -283 524 0.0 -74 200 0.0 -74 285 0.0 -74 247 0.0 -74 525 0.0 -74 253 0.0 -74 326 0.0 -74 457 0.0 -74 526 0.0 -74 249 0.0 -74 527 0.0 -74 252 0.0 -74 79 0.0 -73 74 0.0 -74 250 0.0 -74 379 0.0 -74 211 0.0 -74 251 0.0 -468 528 0.0 -171 468 0.0 -468 469 0.0 -467 468 0.0 -468 529 0.0 -466 468 0.0 -438 468 0.0 -430 468 0.0 -231 530 0.0 -86 530 0.0 -305 531 0.0 -102 305 0.0 -305 314 0.0 -305 312 0.0 -60 365 0.0 -352 365 0.0 -189 365 0.0 -192 365 0.0 -365 403 0.0 -153 365 0.0 -191 365 0.0 -144 365 0.0 -365 404 0.0 -365 406 0.0 -150 365 0.0 -365 405 0.0 -151 365 0.0 -257 365 0.0 -143 365 0.0 -59 365 0.0 -149 365 0.0 -156 365 0.0 -142 365 0.0 -154 365 0.0 -145 365 0.0 -146 365 0.0 -157 365 0.0 -152 365 0.0 -155 365 0.0 -148 365 0.0 -251 253 0.0 -249 253 0.0 -191 253 0.0 -8 180 0.0 -179 180 0.0 -86 532 0.0 -293 533 0.0 -498 499 0.0 -498 500 0.0 -534 535 0.0 -91 95 0.0 -95 98 0.0 -95 97 0.0 -93 95 0.0 -94 95 0.0 -25 210 0.0 -193 210 0.0 -210 306 0.0 -21 210 0.0 -464 465 0.0 -465 536 0.0 -465 516 0.0 -465 537 0.0 -10 538 0.0 -4 10 0.0 -6 10 0.0 -10 539 0.0 -8 10 0.0 -10 86 0.0 -523 540 0.0 -521 523 0.0 -523 541 0.0 -522 523 0.0 -332 470 0.0 -57 332 0.0 -1 332 0.0 -3 542 0.0 -238 372 0.0 -86 238 0.0 -238 319 0.0 -56 238 0.0 -61 511 0.0 -69 511 0.0 -510 511 0.0 -285 459 0.0 -459 461 0.0 -459 460 0.0 -152 200 0.0 -200 543 0.0 -200 247 0.0 -200 379 0.0 -200 252 0.0 -200 326 0.0 -160 200 0.0 -200 211 0.0 -159 200 0.0 -73 200 0.0 -151 200 0.0 -200 250 0.0 -150 200 0.0 -193 200 0.0 -191 200 0.0 -484 544 0.0 -411 484 0.0 -195 356 0.0 -316 531 0.0 -316 317 0.0 -312 316 0.0 -314 316 0.0 -3 345 0.0 -276 345 0.0 -345 416 0.0 -330 454 0.0 -330 456 0.0 -477 502 0.0 -102 502 0.0 -333 545 0.0 -106 188 0.0 -102 106 0.0 -106 463 0.0 -105 106 0.0 -49 546 0.0 -504 546 0.0 -242 547 0.0 -242 449 0.0 -141 548 0.0 -479 548 0.0 -57 132 0.0 -55 57 0.0 -56 57 0.0 -159 276 0.0 -49 276 0.0 -276 549 0.0 -276 346 0.0 -516 536 0.0 -550 551 0.0 -550 552 0.0 -144 185 0.0 -185 192 0.0 -553 554 0.0 -55 553 0.0 -466 529 0.0 -251 457 0.0 -4 8 0.0 -2 8 0.0 -8 471 0.0 -6 8 0.0 -20 25 0.0 -140 270 0.0 -141 270 0.0 -270 555 0.0 -162 240 0.0 -143 162 0.0 -151 162 0.0 -148 162 0.0 -162 406 0.0 -162 556 0.0 -144 162 0.0 -161 162 0.0 -59 162 0.0 -155 162 0.0 -154 162 0.0 -156 162 0.0 -157 162 0.0 -159 162 0.0 -160 162 0.0 -153 162 0.0 -470 557 0.0 -375 558 0.0 -171 375 0.0 -313 375 0.0 -375 377 0.0 -375 376 0.0 -504 559 0.0 -504 560 0.0 -504 561 0.0 -504 562 0.0 -206 504 0.0 -223 504 0.0 -504 519 0.0 -87 563 0.0 -86 563 0.0 -430 431 0.0 -179 419 0.0 -297 564 0.0 -102 565 0.0 -565 566 0.0 -479 565 0.0 -306 565 0.0 -91 98 0.0 -91 97 0.0 -91 93 0.0 -91 94 0.0 -192 567 0.0 -73 192 0.0 -192 404 0.0 -143 192 0.0 -192 211 0.0 -145 192 0.0 -184 192 0.0 -150 192 0.0 -142 192 0.0 -188 192 0.0 -152 192 0.0 -146 192 0.0 -149 192 0.0 -189 192 0.0 -148 192 0.0 -151 192 0.0 -16 192 0.0 -192 568 0.0 -191 192 0.0 -192 193 0.0 -192 406 0.0 -144 192 0.0 -428 569 0.0 -428 570 0.0 -272 428 0.0 -86 428 0.0 -271 428 0.0 -333 428 0.0 -513 538 0.0 -291 538 0.0 -538 571 0.0 -538 572 0.0 -460 538 0.0 -151 250 0.0 -151 189 0.0 -69 151 0.0 -151 299 0.0 -151 191 0.0 -151 404 0.0 -144 151 0.0 -151 405 0.0 -151 406 0.0 -143 151 0.0 -149 151 0.0 -151 156 0.0 -59 151 0.0 -151 257 0.0 -150 151 0.0 -146 151 0.0 -151 152 0.0 -148 151 0.0 -151 155 0.0 -151 157 0.0 -151 154 0.0 -142 151 0.0 -145 151 0.0 -61 132 0.0 -132 509 0.0 -132 507 0.0 -132 340 0.0 -132 231 0.0 -132 398 0.0 -132 399 0.0 -128 132 0.0 -221 230 0.0 -230 573 0.0 -225 230 0.0 -230 477 0.0 -574 575 0.0 -63 299 0.0 -16 299 0.0 -146 299 0.0 -299 404 0.0 -299 402 0.0 -154 299 0.0 -143 299 0.0 -203 299 0.0 -250 290 0.0 -59 250 0.0 -148 250 0.0 -191 250 0.0 -146 250 0.0 -149 250 0.0 -69 250 0.0 -14 250 0.0 -79 250 0.0 -16 250 0.0 -157 250 0.0 -250 251 0.0 -154 250 0.0 -247 250 0.0 -211 250 0.0 -250 252 0.0 -73 250 0.0 -14 191 0.0 -14 18 0.0 -14 102 0.0 -14 291 0.0 -14 576 0.0 -14 73 0.0 -14 396 0.0 -14 247 0.0 -14 169 0.0 -14 198 0.0 -14 573 0.0 -14 577 0.0 -14 19 0.0 -14 168 0.0 -14 16 0.0 -43 356 0.0 -260 356 0.0 -263 356 0.0 -356 578 0.0 -262 479 0.0 -17 262 0.0 -261 262 0.0 -262 263 0.0 -258 262 0.0 -259 262 0.0 -260 262 0.0 -223 416 0.0 -223 293 0.0 -223 225 0.0 -157 569 0.0 -130 399 0.0 -130 456 0.0 -130 454 0.0 -130 509 0.0 -130 427 0.0 -130 455 0.0 -231 579 0.0 -86 231 0.0 -231 340 0.0 -580 581 0.0 -580 582 0.0 -3 580 0.0 -543 583 0.0 -73 463 0.0 -73 191 0.0 -73 79 0.0 -59 73 0.0 -73 157 0.0 -69 73 0.0 -16 73 0.0 -73 251 0.0 -73 154 0.0 -73 252 0.0 -73 211 0.0 -73 247 0.0 -86 584 0.0 -372 584 0.0 -584 585 0.0 -493 584 0.0 -52 584 0.0 -321 586 0.0 -321 500 0.0 -321 322 0.0 -321 323 0.0 -321 587 0.0 -198 321 0.0 -321 588 0.0 -168 169 0.0 -16 168 0.0 -19 168 0.0 -86 278 0.0 -86 171 0.0 -86 377 0.0 -86 272 0.0 -86 570 0.0 -86 589 0.0 -86 590 0.0 -55 86 0.0 -51 86 0.0 -34 86 0.0 -86 319 0.0 -49 86 0.0 -86 348 0.0 -56 86 0.0 -86 320 0.0 -86 87 0.0 -4 6 0.0 -4 352 0.0 -4 451 0.0 -4 452 0.0 -76 252 0.0 -252 293 0.0 -252 463 0.0 -252 379 0.0 -251 252 0.0 -247 252 0.0 -211 252 0.0 -293 591 0.0 -247 290 0.0 -2 49 0.0 -2 467 0.0 -2 271 0.0 -2 272 0.0 -2 52 0.0 -2 69 0.0 -188 193 0.0 -189 193 0.0 -191 193 0.0 -59 193 0.0 -144 193 0.0 -351 592 0.0 -93 140 0.0 -93 141 0.0 -93 98 0.0 -93 94 0.0 -93 97 0.0 -509 513 0.0 -551 552 0.0 -552 593 0.0 -416 451 0.0 -416 417 0.0 -416 452 0.0 -416 594 0.0 -551 593 0.0 -102 306 0.0 -1 263 0.0 -263 286 0.0 -263 595 0.0 -259 263 0.0 -258 263 0.0 -263 578 0.0 -261 263 0.0 -260 263 0.0 -226 571 0.0 -226 460 0.0 -226 572 0.0 -596 597 0.0 -34 87 0.0 -51 87 0.0 -56 87 0.0 -87 348 0.0 -144 186 0.0 -144 404 0.0 -144 191 0.0 -144 184 0.0 -144 556 0.0 -144 240 0.0 -144 159 0.0 -144 188 0.0 -144 568 0.0 -144 161 0.0 -144 150 0.0 -142 144 0.0 -144 405 0.0 -144 148 0.0 -144 146 0.0 -144 145 0.0 -144 257 0.0 -144 189 0.0 -144 152 0.0 -143 144 0.0 -144 149 0.0 -144 406 0.0 -517 598 0.0 -256 599 0.0 -475 599 0.0 -105 600 0.0 -43 256 0.0 -44 256 0.0 -38 256 0.0 -40 256 0.0 -257 403 0.0 -257 567 0.0 -240 257 0.0 -44 257 0.0 -191 257 0.0 -40 257 0.0 -257 404 0.0 -257 406 0.0 -155 257 0.0 -146 257 0.0 -152 257 0.0 -148 257 0.0 -157 257 0.0 -142 257 0.0 -154 257 0.0 -145 257 0.0 -143 257 0.0 -149 257 0.0 -156 257 0.0 -59 257 0.0 -257 405 0.0 -150 257 0.0 -97 141 0.0 -97 140 0.0 -97 98 0.0 -94 97 0.0 -49 561 0.0 -601 602 0.0 -83 85 0.0 -64 603 0.0 -116 118 0.0 -60 118 0.0 -461 604 0.0 -604 605 0.0 -255 606 0.0 -319 606 0.0 -146 402 0.0 -154 402 0.0 -143 402 0.0 -499 500 0.0 -348 499 0.0 -454 607 0.0 -456 607 0.0 -607 608 0.0 -60 116 0.0 -116 117 0.0 -411 544 0.0 -598 609 0.0 -351 610 0.0 -259 260 0.0 -259 261 0.0 -258 259 0.0 -463 611 0.0 -188 463 0.0 -211 463 0.0 -79 463 0.0 -291 369 0.0 -386 612 0.0 -78 249 0.0 -76 78 0.0 -17 487 0.0 -17 141 0.0 -17 258 0.0 -17 479 0.0 -17 19 0.0 -17 27 0.0 -258 261 0.0 -261 595 0.0 -260 261 0.0 -613 614 0.0 -379 525 0.0 -21 27 0.0 -19 27 0.0 -204 205 0.0 -159 204 0.0 -204 615 0.0 -229 581 0.0 -229 339 0.0 -108 616 0.0 -49 539 0.0 -539 617 0.0 -233 372 0.0 -233 618 0.0 -16 577 0.0 -297 415 0.0 -83 619 0.0 -83 620 0.0 -308 312 0.0 -372 493 0.0 -364 493 0.0 -148 160 0.0 -148 188 0.0 -148 161 0.0 -69 148 0.0 -148 191 0.0 -148 403 0.0 -148 404 0.0 -148 406 0.0 -148 157 0.0 -148 152 0.0 -148 155 0.0 -146 148 0.0 -145 148 0.0 -142 148 0.0 -148 154 0.0 -59 148 0.0 -148 149 0.0 -148 156 0.0 -143 148 0.0 -148 150 0.0 -148 405 0.0 -222 621 0.0 -64 269 0.0 -198 269 0.0 -272 570 0.0 -69 460 0.0 -291 460 0.0 -460 461 0.0 -285 460 0.0 -102 460 0.0 -317 460 0.0 -222 460 0.0 -460 572 0.0 -460 571 0.0 -258 479 0.0 -258 622 0.0 -258 260 0.0 -225 470 0.0 -244 339 0.0 -405 567 0.0 -310 317 0.0 -237 415 0.0 -237 376 0.0 -519 520 0.0 -161 406 0.0 -404 406 0.0 -156 406 0.0 -191 406 0.0 -189 406 0.0 -405 406 0.0 -149 406 0.0 -152 406 0.0 -143 406 0.0 -146 406 0.0 -142 406 0.0 -157 406 0.0 -150 406 0.0 -145 406 0.0 -209 387 0.0 -272 273 0.0 -322 323 0.0 -63 473 0.0 -43 63 0.0 -38 63 0.0 -44 63 0.0 -63 410 0.0 -110 581 0.0 -339 581 0.0 -49 623 0.0 -149 189 0.0 -143 189 0.0 -150 189 0.0 -272 624 0.0 -272 625 0.0 -271 272 0.0 -156 626 0.0 -209 626 0.0 -154 626 0.0 -157 626 0.0 -146 626 0.0 -404 436 0.0 -157 436 0.0 -143 436 0.0 -69 436 0.0 -247 251 0.0 -251 292 0.0 -251 379 0.0 -211 251 0.0 -102 291 0.0 -16 102 0.0 -102 312 0.0 -102 477 0.0 -102 141 0.0 -102 572 0.0 -102 571 0.0 -102 225 0.0 -314 531 0.0 -314 317 0.0 -312 314 0.0 -278 372 0.0 -372 585 0.0 -44 60 0.0 -44 155 0.0 -44 145 0.0 -44 146 0.0 -44 407 0.0 -44 408 0.0 -44 475 0.0 -44 149 0.0 -38 44 0.0 -40 44 0.0 -43 44 0.0 -347 348 0.0 -348 590 0.0 -60 117 0.0 -608 627 0.0 -454 608 0.0 -456 608 0.0 -479 487 0.0 -293 479 0.0 -16 18 0.0 -18 19 0.0 -161 240 0.0 -155 161 0.0 -59 161 0.0 -161 556 0.0 -156 161 0.0 -159 161 0.0 -157 161 0.0 -154 161 0.0 -153 161 0.0 -160 161 0.0 -16 573 0.0 -291 573 0.0 -293 573 0.0 -24 25 0.0 -25 513 0.0 -16 396 0.0 -152 352 0.0 -145 352 0.0 -156 352 0.0 -142 352 0.0 -59 352 0.0 -352 451 0.0 -352 353 0.0 -352 452 0.0 -377 558 0.0 -171 558 0.0 -376 558 0.0 -313 558 0.0 -61 143 0.0 -143 160 0.0 -16 143 0.0 -69 143 0.0 -60 143 0.0 -143 403 0.0 -143 191 0.0 -143 404 0.0 -143 405 0.0 -142 143 0.0 -143 152 0.0 -143 156 0.0 -143 154 0.0 -143 145 0.0 -143 146 0.0 -143 157 0.0 -143 155 0.0 -143 150 0.0 -59 143 0.0 -143 149 0.0 -247 292 0.0 -292 326 0.0 -191 247 0.0 -79 247 0.0 -69 247 0.0 -16 247 0.0 -211 247 0.0 -587 628 0.0 -322 587 0.0 -427 456 0.0 -427 454 0.0 -427 455 0.0 -417 451 0.0 -451 452 0.0 -60 629 0.0 -60 156 0.0 -59 60 0.0 -60 157 0.0 -60 364 0.0 -60 154 0.0 -60 152 0.0 -60 69 0.0 -60 547 0.0 -60 149 0.0 -60 155 0.0 -60 61 0.0 -60 150 0.0 -52 571 0.0 -52 69 0.0 -135 630 0.0 -61 150 0.0 -150 191 0.0 -150 403 0.0 -40 150 0.0 -150 404 0.0 -150 405 0.0 -150 156 0.0 -149 150 0.0 -59 150 0.0 -142 150 0.0 -150 154 0.0 -145 150 0.0 -146 150 0.0 -150 155 0.0 -150 152 0.0 -150 157 0.0 -415 631 0.0 -55 632 0.0 -614 633 0.0 -240 634 0.0 -142 403 0.0 -40 142 0.0 -142 191 0.0 -142 404 0.0 -142 405 0.0 -142 146 0.0 -142 152 0.0 -142 155 0.0 -142 157 0.0 -142 154 0.0 -142 145 0.0 -142 149 0.0 -142 156 0.0 -59 142 0.0 -51 278 0.0 -157 278 0.0 -135 635 0.0 -141 635 0.0 -55 635 0.0 -293 635 0.0 -636 637 0.0 -225 271 0.0 -271 638 0.0 -271 333 0.0 -198 639 0.0 -571 572 0.0 -291 571 0.0 -222 571 0.0 -317 571 0.0 -430 469 0.0 -430 466 0.0 -430 438 0.0 -149 211 0.0 -69 211 0.0 -154 211 0.0 -191 211 0.0 -157 211 0.0 -211 379 0.0 -79 211 0.0 -211 326 0.0 -51 629 0.0 -598 629 0.0 -16 169 0.0 -492 640 0.0 -128 507 0.0 -128 399 0.0 -128 398 0.0 -398 399 0.0 -186 188 0.0 -347 590 0.0 -61 510 0.0 -69 510 0.0 -54 471 0.0 -165 166 0.0 -166 627 0.0 -165 627 0.0 -56 641 0.0 -56 319 0.0 -454 455 0.0 -624 625 0.0 -417 452 0.0 -179 417 0.0 -188 191 0.0 -79 191 0.0 -16 191 0.0 -191 404 0.0 -155 191 0.0 -191 405 0.0 -154 191 0.0 -157 191 0.0 -145 191 0.0 -152 191 0.0 -146 191 0.0 -149 191 0.0 -191 207 0.0 -156 191 0.0 -59 191 0.0 -225 487 0.0 -225 477 0.0 -225 291 0.0 -43 407 0.0 -38 407 0.0 -40 407 0.0 -198 407 0.0 -171 376 0.0 -255 376 0.0 -313 376 0.0 -376 377 0.0 -43 408 0.0 -38 408 0.0 -40 408 0.0 -198 408 0.0 -213 281 0.0 -222 642 0.0 -222 572 0.0 -49 559 0.0 -304 307 0.0 -643 644 0.0 -69 145 0.0 -145 403 0.0 -40 145 0.0 -145 404 0.0 -145 155 0.0 -145 152 0.0 -145 157 0.0 -145 146 0.0 -145 154 0.0 -145 156 0.0 -145 149 0.0 -59 145 0.0 -145 405 0.0 -455 456 0.0 -645 646 0.0 -647 648 0.0 -1 649 0.0 -171 313 0.0 -313 377 0.0 -312 313 0.0 -140 293 0.0 -55 293 0.0 -198 293 0.0 -293 477 0.0 -141 293 0.0 -291 293 0.0 -333 650 0.0 -255 377 0.0 -171 377 0.0 -467 469 0.0 -466 469 0.0 -438 469 0.0 -521 522 0.0 -438 467 0.0 -285 461 0.0 -157 461 0.0 -291 572 0.0 -317 572 0.0 -3 179 0.0 -16 576 0.0 -49 560 0.0 -49 562 0.0 -16 154 0.0 -16 291 0.0 -16 198 0.0 -16 19 0.0 -403 405 0.0 -404 405 0.0 -155 405 0.0 -157 405 0.0 -146 405 0.0 -154 405 0.0 -149 405 0.0 -156 405 0.0 -152 405 0.0 -59 405 0.0 -342 651 0.0 -171 255 0.0 -171 179 0.0 -198 586 0.0 -157 209 0.0 -69 281 0.0 -157 652 0.0 -653 654 0.0 -55 255 0.0 -255 655 0.0 -154 159 0.0 -59 159 0.0 -155 159 0.0 -156 159 0.0 -159 160 0.0 -157 159 0.0 -159 505 0.0 -69 159 0.0 -159 556 0.0 -153 159 0.0 -322 500 0.0 -198 322 0.0 -322 399 0.0 -55 141 0.0 -141 487 0.0 -140 141 0.0 -135 141 0.0 -61 146 0.0 -61 154 0.0 -61 157 0.0 -61 149 0.0 -61 69 0.0 -438 466 0.0 -340 656 0.0 -153 155 0.0 -153 160 0.0 -153 157 0.0 -153 156 0.0 -153 556 0.0 -59 153 0.0 -153 154 0.0 -24 513 0.0 -513 514 0.0 -154 207 0.0 -291 487 0.0 -260 578 0.0 -40 155 0.0 -40 146 0.0 -40 149 0.0 -40 43 0.0 -38 40 0.0 -6 403 0.0 -54 403 0.0 -403 404 0.0 -146 403 0.0 -152 403 0.0 -149 403 0.0 -1 157 0.0 -157 340 0.0 -69 157 0.0 -157 404 0.0 -157 160 0.0 -157 198 0.0 -152 157 0.0 -156 157 0.0 -146 157 0.0 -155 157 0.0 -154 157 0.0 -59 157 0.0 -149 157 0.0 -38 43 0.0 -69 154 0.0 -154 404 0.0 -154 160 0.0 -146 154 0.0 -152 154 0.0 -154 155 0.0 -59 154 0.0 -149 154 0.0 -154 156 0.0 -59 69 0.0 -69 146 0.0 -69 149 0.0 -69 657 0.0 -657 658 0.0 -260 595 0.0 -79 285 0.0 -285 379 0.0 -326 379 0.0 -79 326 0.0 -19 198 0.0 -43 475 0.0 -34 55 0.0 -152 404 0.0 -152 156 0.0 -149 152 0.0 -59 152 0.0 -146 152 0.0 -152 155 0.0 -155 391 0.0 -79 379 0.0 -146 404 0.0 -146 155 0.0 -59 146 0.0 -146 156 0.0 -146 149 0.0 -155 404 0.0 -156 404 0.0 -59 404 0.0 -149 404 0.0 -149 160 0.0 -149 155 0.0 -59 149 0.0 -149 156 0.0 -340 659 0.0 -156 160 0.0 -155 156 0.0 -59 156 0.0 -59 160 0.0 -59 155 0.0 -94 98 0.0 -155 160 0.0 diff --git a/results/networks/layout.csv b/results/networks/layout.csv new file mode 100644 index 0000000..6fd43a8 --- /dev/null +++ b/results/networks/layout.csv @@ -0,0 +1,574 @@ +x,y +455.273103727162,-368.892142934348 +426.791658897507,-368.616473553289 +363.731082114518,-342.787645337025 +419.867482935603,-389.262969170422 +481.053850293815,-394.909545652206 +434.320378388567,-264.096229819477 +478.002999230834,-237.134685973414 +359.68904190151,-309.624126504328 +62.1649976380318,-472.849304416747 +98.4261159378247,-456.852191756959 +136.21984279983,-474.227164587402 +103.161244563718,-481.584528968504 +163.085576421858,-438.187392093896 +99.6020883319393,-427.667781681755 +124.982714929516,-423.489599407211 +115.340089389055,-441.682059500723 +87.9966069397504,-409.800328596135 +125.836016173011,-384.588008262489 +99.5195343339567,-541.481280147315 +152.583365949434,-454.324535756526 +79.9757057973461,-476.691638759321 +39.1419764647195,-504.571341246833 +228.01499650842,-302.158836076303 +112.253466329959,-314.016297254401 +258.816033080947,-339.170641070806 +332.544423134587,-321.182202139463 +396.266505569454,-119.724078490362 +363.243264791565,-160.454769596167 +220.2620206137,-317.859159119 +198.465218214709,-381.114283951397 +404.347330365196,-308.723831284965 +426.134405705751,-346.158537060289 +398.044760533157,-291.246276238395 +353.283930881842,-398.777725360274 +390.641310573652,-336.289548278736 +365.141773082344,-289.975523627776 +184.849414513661,-627.377748161885 +182.18726734006,-565.781183684172 +226.424853872054,-607.831268579447 +104.271281138725,-205.865452014544 +65.0872001913592,-154.176138058766 +105.919679198305,-278.942126334195 +150.315195974359,-282.104008762396 +110.291301023513,-255.108668681527 +140.472757486802,-181.001359904141 +88.2067976611811,-196.461886890722 +116.216697788073,-235.444560548674 +163.840265989424,-564.008587164087 +227.488795375831,-431.638778804062 +130.087996784768,-620.31249621128 +158.922239595078,-624.595547127684 +282.993766559138,-178.438515275785 +305.355449685101,-146.315466623196 +285.811804728069,-254.548837777152 +302.962339259881,-234.677043462561 +231.312568475177,-165.146875614567 +271.054151053392,-230.626940944788 +266.120977867653,-193.124198169665 +437.355157020992,-388.714431542888 +491.506715833212,-410.873859998158 +318.684646909458,-368.234401102365 +511.307773827899,-402.438777195413 +358.242713200047,-364.665615644363 +322.494355886696,-220.723354719453 +335.063555605444,-267.503121483509 +251.116097041628,-250.728722194757 +314.214608604592,-608.131963344809 +276.544211816976,-507.533593711346 +340.103530997593,-679.73374977378 +417.581651140262,-290.315371182386 +254.541171925729,-200.989837502243 +194.98701930009,-217.93898425691 +213.088502290024,-264.60169691598 +351.998348670495,-207.705114887728 +536.707863154138,-322.183811325424 +595.810440194241,-319.68672000214 +452.77106928276,-331.098604511781 +14.9590911379013,-626.735192427283 +44.7294379670214,-589.466561515405 +417.163326960645,-485.222216939957 +368.881568485074,-450.988664156406 +206.755641518597,-449.474371216344 +186.318965022608,-440.748967995927 +134.226318535192,-403.178769869133 +196.872372407565,-404.702360271024 +152.78852985358,-402.574059723996 +172.103472441848,-400.357501465807 +236.549834253849,-376.295512373031 +294.576128205799,-425.717959781054 +113.209889547609,-408.562934651679 +139.572326745131,-435.34595182882 +133.084699110673,-455.58370227363 +153.383723357032,-421.509198156181 +160.576588006814,-475.163842147692 +115.295182741668,-464.840782120129 +102.823928080431,-391.521011201217 +125.333407576371,-489.005184594857 +175.479737146714,-458.904883194306 +152.238655233518,-493.774704823406 +178.162651936831,-422.800861354481 +324.790212342264,-427.931755103576 +204.775591279631,-590.616251981405 +207.831202450147,-525.500984899661 +86.1716424810543,-495.540319419446 +215.174782732218,-400.215789443054 +209.772225534824,-350.97171979717 +241.65019567507,-281.407179477108 +234.124122946396,-480.733542725128 +289.559042767325,-230.742519660151 +86.3298103123281,-354.585114102052 +56.2864630184666,-424.564725824267 +201.587503352108,-470.899980090088 +253.671190478953,-454.488887145231 +169.862435224302,-512.401640953862 +124.540511061298,-297.451631585031 +201.67573858791,-553.287111738994 +108.108844588825,-347.413104623043 +221.068399494791,-465.767787605734 +310.802344236398,-578.55532379217 +284.654570727497,-527.299103869239 +154.773296789024,-150.26696908243 +87.1043268846381,-157.776264021621 +219.622370512066,-205.067918424443 +223.818108735319,-420.020133025417 +64.7989457345902,-360.775735030246 +285.964910128168,-484.037170930178 +296.775534800044,-401.771902516698 +533.602022755952,-359.129220559663 +491.889999940517,-316.40384812432 +330.420245501405,-377.949980756909 +329.586761645777,-355.732367212162 +305.721361864077,-339.258367426921 +293.675643192707,-350.534467406502 +262.378625520734,-391.249730538649 +400.973982311885,-380.081705178433 +307.82420587584,-379.720346590401 +400.962523173892,-579.604659766041 +427.984121669747,-619.087971070769 +372.016493789708,-582.088218106702 +358.146459068376,-518.661169190505 +344.724221834946,-538.230302644474 +382.686932560483,-569.509573793451 +392.711881341113,-536.777868372786 +357.173793527117,-558.134221309798 +220.23706295968,-550.110981257352 +-300,0 +-280,0 +166.641946921925,-362.400277227905 +86.5498164461224,-377.484838797694 +175.87897245012,-380.560041037013 +151.547829052816,-381.80839892083 +129.707537490906,-342.753077789152 +109.231430395901,-369.317037278617 +185.254997492513,-364.450437790796 +148.539214623836,-361.573503348956 +55.740660082747,-533.214033628279 +241.179132764412,-234.269031556781 +291.532270386681,-272.657575691235 +206.904328002455,-171.610877437235 +216.825558380426,-123.791152888067 +226.399689688938,-248.52837108311 +225.379275539027,-223.083465807751 +339.708654622341,-402.994416661616 +387.302819251758,-384.553035956214 +385.508937171008,-409.993932712902 +364.751494446692,-385.491816124272 +405.113008480214,-435.799651137153 +483.707439785422,-355.411309055141 +461.917075884472,-305.556340186937 +498.261595517035,-226.250249711537 +450.215656360132,-247.828316517156 +355.806953104474,-172.054603651052 +329.253148498892,-176.3732538669 +546.907183890708,-542.140526926149 +504.33435734588,-498.608404262613 +543.889393281142,-507.351770850707 +564.06765068197,-525.879883417891 +589.945392925792,-532.332072326982 +95.7048124029178,-237.376877900536 +75.4768193609052,-257.557199796785 +137.66965089965,-261.166651491345 +31.96968323403,-210.969578385331 +42.100374455517,-201.643707134615 +130.285122515836,-243.401805646526 +127.436874967322,-275.522623915749 +156.388949829141,-307.220610743529 +115.320709123853,-185.712236701596 +81.2015121715556,-274.337219400506 +159.449542960522,-256.483577250703 +45.708821937497,-246.031372771123 +135.810386599574,-224.262994087806 +79.987792331515,-223.398570412614 +242.938743956921,-522.151511923503 +223.976039961227,-585.888707338804 +328.463643529854,-484.849637895243 +268.43665913246,-563.52973753385 +243.371195988583,-542.661933344981 +245.821628297616,-572.534407652969 +203.888233249353,-500.150039734649 +246.592462947841,-660.187898551935 +72.008788022061,-241.732689358239 +89.3942059570607,-173.779439248425 +66.9691301031181,-195.132341330095 +338.083269482153,-438.550898311746 +409.727513568871,-369.463186163127 +182.337538051402,-341.385758928497 +403.22582649694,-396.399516720275 +248.321142098619,-466.59391311094 +338.126933116869,-301.252553644553 +348.777538657233,-286.332203649068 +383.844371217034,-322.469472721648 +344.681118820278,-387.336743960137 +350.867499938965,-330.476837530734 +314.65056200228,-353.789823420385 +185.390371862562,-174.757276486998 +209.432110475496,-236.209362855407 +372.111228855334,-436.572600469192 +504.988672628801,-344.017396682523 +405.579163134287,-347.175233589757 +301.506532814998,-281.481416943537 +258.935689207618,-310.509736620221 +322.93284033113,-295.96216380269 +391.095803020958,-267.909478842079 +384.543607469721,-242.170514901667 +347.765206653904,-187.03682969241 +282.122244797968,-457.865593425774 +-260,0 +-240,0 +315.097979441535,-92.4888369168979 +134.897285680375,-140.664797315054 +149.273626833246,-203.369171404342 +45.1372023375232,-350.71612087178 +282.879197434823,-323.401787894448 +247.190673636295,-328.785025295001 +159.205128917204,-340.170936610488 +74.8611449388087,-431.116592144728 +129.325329815897,-361.16996058725 +190.89219076134,-299.888101131873 +125.245330260467,-325.368754928317 +309.815802964787,-269.418084486071 +227.669009306713,-343.81490651746 +151.199684778242,-236.858488726555 +325.803376128089,-253.545712916827 +168.184958041991,-237.888840521571 +276.965209447695,-283.675797619311 +189.476924881698,-590.222180598253 +305.208980356687,-214.761863959752 +309.796326394922,-315.795020307585 +311.380112779046,-250.916883698152 +302.66928376519,-171.255362508121 +231.853672368164,-199.556908843236 +338.720904405827,-155.845791154141 +325.703940639089,-149.202774938616 +352.533035286456,-268.503062993265 +273.952261282619,-302.972842833821 +363.179478043053,-223.23950697267 +254.417610203369,-231.231693833829 +278.629525366338,-212.406359856791 +309.801486051055,-300.083151040836 +223.266374722349,-106.088263574546 +190.540225921246,-236.997266881843 +189.247247151729,-159.333973746276 +360.901300007422,-132.946671832475 +225.159862640683,-184.372616183698 +290.883652334499,-294.556121040991 +204.881150502951,-327.494397049437 +243.83567687199,-186.6627135062 +269.002152191797,-166.214199171041 +214.776172900946,-192.454723869862 +301.849047993591,-363.95359153397 +247.948174749296,-165.096988986895 +290.702021970533,-163.863493630563 +280.599593271208,-135.868420250693 +248.897660633495,-144.493634097361 +254.507091813544,-183.688411034447 +230.628092752395,-266.652642586615 +291.927880292582,-202.528026932029 +557.20492118028,-414.322805968298 +456.741325086234,-420.802778282566 +206.609149984562,-427.121278503937 +281.185411721204,-410.332777475308 +210.034687303024,-214.015615462559 +248.70502400293,-263.665047577923 +399.181551072503,-484.459390146482 +351.832566088992,-451.285861402511 +498.63554579869,-383.491016731571 +576.835453008169,-391.218272159437 +132.8793215764,-569.481092888593 +-43.0614987092503,-333.272271007305 +13.8702828450758,-344.204167274904 +394.210220851137,-443.09370625163 +415.05933160994,-425.175737360763 +366.932254707496,-417.520297222384 +286.698614554713,-444.482486245332 +300.715626774979,-452.755651952086 +261.077510287727,-435.170030986711 +277.08426214201,-473.590983226876 +241.7223792121,-500.713265442491 +295.676981332034,-466.883326788297 +332.857868458983,-512.259815767821 +307.991409598154,-437.336759225344 +313.474639788847,-458.892526819726 +461.329630453839,-11.3819887526434 +462.650540887034,-54.430722318503 +506.785267154995,-297.929786611386 +419.020302161917,-322.133133339637 +373.579763818137,-366.109287873744 +472.955213958762,-291.291165394194 +254.90704382157,-276.930540919987 +262.033433500802,-214.551101048032 +228.74499792868,-514.593004865999 +183.818497301607,-487.501821731155 +377.079579487757,-521.587038333702 +423.871023964592,-305.429732166479 +181.381875019001,-277.921353452858 +209.038646700327,-297.020018068951 +170.94467213783,-289.286882761059 +276.355801432691,-156.456118284018 +61.5824624634674,-112.08809795104 +443.577455825279,-292.804006716795 +464.632990199857,-269.898746179252 +325.964709354661,-209.824916054969 +373.274250765625,-200.116962151916 +310.401488888631,-419.692125286757 +232.426822251586,-325.220571415934 +431.429638047737,-401.711599196593 +378.02029323568,-349.045759886311 +441.299175675272,-358.293019571777 +435.401994174583,-328.186766589727 +344.200517393119,-361.184867080814 +393.066205244091,-360.35715994185 +186.981623203552,-265.979638961998 +373.910451930947,-496.819179007828 +421.595192960014,-412.791442829933 +397.581749371212,-145.551628326032 +422.853275505761,-137.553408447497 +441.195526433648,-177.867310071606 +409.832402560789,-165.540832328922 +449.718363170598,-102.905785618902 +129.060291403481,-198.620457382631 +94.0392789211314,-253.891898765061 +426.859207822136,-232.746402642959 +511.634809702633,-246.133177345069 +83.2122856518978,-447.232388932788 +496.924553585283,-159.891786764733 +461.208887539111,-188.740504918755 +175.958090458975,-257.031613932935 +174.85711804599,-204.878573275061 +-220,0 +-200,0 +311.486735067287,-403.891665405926 +328.780910246515,-394.131488240175 +353.033004022881,-430.399198035929 +328.622768981837,-411.108749392992 +294.059395838096,-385.038940358026 +-180,0 +-160,0 +-140,0 +247.746631233007,-615.974697609808 +197.910808178803,-614.546077767907 +230.577414436582,-448.321246902896 +261.250704286474,-515.584765399158 +171.863248652755,-585.395377952665 +259.908157704366,-597.033300737813 +268.967220696415,-586.52111621971 +513.847256171788,-188.387704357448 +290.580967447579,-309.550270265511 +318.754927976521,-235.940470046181 +337.945187402489,-340.842121861629 +337.087238303543,-280.257459443386 +276.458091872778,-339.382382143844 +320.476598086239,-326.789393994092 +128.349389930732,-159.91192551191 +621.449804890723,-386.154938517788 +601.005673516096,-270.728725360748 +519.633945311281,-273.830269427826 +504.111365621826,-268.716981733423 +30.2703976086057,-140.254102407301 +65.7220477906933,-179.907335759386 +268.1572989012,-350.814361314108 +243.081779503461,-311.99993209988 +271.432303634082,-446.283700768368 +280.317766066559,-433.156585317919 +247.440508778714,-298.313289764878 +324.793243289573,-445.228838590653 +294.124781910728,-412.639513192159 +198.088593735283,-281.913354999907 +247.914919353925,-412.700672343196 +283.845586034844,-369.745180056745 +140.462304455441,-325.119445064629 +317.274212635722,-387.129564953383 +341.533225515181,-421.515458801414 +279.12995296958,-354.32038891961 +265.363089370629,-322.280267963553 +281.016882530713,-422.19630465618 +417.073614881597,-453.933142921515 +494.400173540986,-470.691146552737 +456.529617586138,-438.096455029866 +539.038382588434,-478.931515732122 +439.395751483779,-480.504010831474 +437.963170636488,-459.881179828621 +515.033286676223,10.7964492041704 +500.663287997446,-30.8776979133073 +483.046908950513,-4.5865795592613 +582.630619517448,-24.7111217328472 +553.952035779753,-55.545383269135 +264.539165399916,-531.02187121851 +79.3797679557755,-393.399335467935 +170.287503192559,-320.362490677294 +-300,-20 +-280,-20 +307.666518226849,-528.688637645367 +292.958038881046,-126.048252714361 +619.375902331489,-405.592790511915 +381.902458035055,-287.515877286996 +-240,-20 +-220,-20 +-200,-20 +658.597749150514,-254.614002996636 +644.120898626318,-277.375494883969 +634.195574441158,-242.850491941112 +571.511419766115,-498.831183215471 +335.01014517771,-118.476229735909 +95.8419709845412,-299.403613474606 +62.8122963694999,-401.918434114046 +638.947586440758,-320.084332109537 +539.390991848973,-77.2549496875794 +502.940668400646,-66.5943420665885 +498.003342900303,-95.9988898537302 +536.450302916476,-47.666192658991 +514.958929202126,-49.4933115101622 +-180,-20 +-160,-20 +-140,-20 +-300,-40 +97.5859769530247,-324.99889659925 +319.039447446177,-514.020846165882 +469.779133334853,-352.898356313243 +610.685627323572,-147.271426738403 +573.423857267764,-167.037228959561 +402.8324440748,-226.717992613188 +389.142151740154,-206.667635259871 +369.45162640805,-253.203965209541 +363.740097271643,-717.31161046351 +51.9400419842983,-379.7027513302 +440.312808543538,-374.667768808674 +-3.57201757435691,-218.078195108533 +63.009803290402,-307.199438805667 +217.765720169318,-571.14618173997 +265.595161107355,-460.652700180741 +269.889185539763,-418.869221679291 +-280,-40 +-260,-40 +192.693958500563,-195.586074205065 +225.293947797211,-642.80044766825 +232.996657843934,-672.637001480537 +194.761642656947,-647.675321127647 +-240,-40 +-220,-40 +378.838034117255,-54.1519622849294 +374.764576397867,-109.470970445496 +341.324112353445,-373.350722681112 +109.782912387191,-503.786903870527 +90.5516451332662,-530.204663190845 +529.754576532636,-285.468481351264 +421.376351494825,-67.7578741282475 +436.972571812824,-560.533679907839 +388.94384524555,-552.200886444089 +416.342407318308,-538.380901806712 +419.992997246957,-524.578803507724 +541.142583318263,-104.489679345558 +530.459133374913,-89.8377753346417 +-7.40262066758868,-346.226500791165 +15.5127659441393,-379.121388412497 +16.6318588018147,-361.905398126855 +78.6708249431729,-318.974902244511 +-2.45933510763094,-369.694722459751 +52.0378740048898,-336.233890291264 +-200,-40 +-180,-40 +-160,-40 +266.245436349702,-262.341805139423 +471.450687461212,-378.347683172757 +400.084565250299,-463.466325357667 +373.016429261954,-472.476211937834 +266.646918736387,-247.95474164134 +487.519202221475,-213.311821305869 +450.157170524593,-401.221515013897 +546.180140576863,-158.117050706626 +284.160606172417,-80.4600141076485 +-140,-40 +352.962866875745,-242.597438556575 +348.122506948065,-256.154172983806 +346.151875702409,-488.073327975413 +383.900101730977,-68.0656307165319 +326.333780662041,-280.75267868441 +321.857280495676,-337.48659449248 +51.123962486902,-229.57525024802 +476.724219518693,-457.4495963555 +429.127047367396,-434.737870089691 +-300,-60 +-280,-60 +396.279039636615,-59.5635882820803 +402.972554000127,-74.7282910960054 +364.83174826586,-62.019684908224 +522.88239701876,-346.472718097558 +-260,-20 +318.882997393719,-165.196275060782 +31.5143962830487,-340.86987969682 +277.67471394895,-99.9493977704377 +333.668585378481,-462.892556341767 +476.852049544748,-492.624764044657 +318.733792512646,-193.612229908827 +298.755784565078,-185.416139975829 +243.90688312623,-218.970034333329 +421.606826083493,-278.278388674217 +409.204523415256,-276.9238137032 +310.612895307087,-286.881750743196 +484.591277819005,-552.397840332744 +434.399754247394,-510.754409963555 +519.061686786215,-581.790484396712 +353.537612880976,-411.632234177706 +397.354860430326,-501.451807933244 +332.768832692518,-232.558477922563 +478.606066345899,-604.808339940542 +263.794672433302,-150.894981926876 +250.884131581249,-637.954626357002 +244.82291157434,-598.364939003929 +233.316630449711,-563.613292283626 +260.391505002034,-497.574320508105 +556.346787864739,-343.534290664872 +224.974183469212,-282.176126728202 +187.740243930967,-546.412207021561 +113.570992327948,-159.977903489349 +-260,-60 +-240,-60 +509.153950848806,-635.896527126886 +478.068451022132,-433.268630108426 +326.197429199763,-308.083562358552 +478.326925231839,-324.725786587399 +450.712475547216,-347.334214123908 +-220,-60 +-200,-60 +245.926990122563,-89.1243776834677 +348.439185193919,-123.733792239947 +-180,-60 +-160,-60 +144.911687363722,-576.419281662429 +216.686324285845,-664.102721929004 +348.408731369801,-599.718840730453 +329.443272631316,-547.224941426892 +141.48978918498,-511.532532100447 +40.5318801722557,-285.752983923291 +373.761797686281,-274.070454948154 +15.2464293328145,-320.842906687532 +95.8288159459572,-129.995922304735 +443.114919421416,-533.88686866335 +-140,-60 +-300,-80 +465.531240710262,-406.134162344563 +348.425526846174,-349.092460534263 +344.732180892491,-723.910109250374 +409.527458046381,-261.524143618074 +402.144925702498,-248.534476772168 +-280,-80 +-260,-80 +247.206599597923,-433.803119665837 +354.046009084892,-472.22593215512 +8.79501391377188,-396.512667227916 +349.550206302137,-230.962223579301 +-240,-80 +-220,-80 +339.264288204346,-219.0112434179 diff --git a/results/networks/model_edges.txt b/results/networks/model_edges.txt new file mode 100644 index 0000000..493da78 --- /dev/null +++ b/results/networks/model_edges.txt @@ -0,0 +1,2408 @@ +node_a node_b weight +0 1 0.0 +0 2 0.0 +0 3 0.0 +0 4 0.0 +5 6 0.0 +5 7 0.0 +8 9 0.0 +8 10 0.0 +8 11 0.0 +8 12 0.0 +8 13 0.0 +8 14 0.0 +8 15 0.0 +8 16 0.0 +8 17 0.0 +8 18 0.0 +8 19 0.0 +8 20 0.0 +8 21 0.0 +22 23 0.0 +22 24 0.0 +22 25 0.0 +26 27 0.0 +28 29 0.0 +25 30 0.0 +25 31 0.0 +2 25 0.0 +25 32 0.0 +23 25 0.0 +25 33 0.0 +25 34 0.0 +25 35 0.0 +24 25 0.0 +7 25 0.0 +36 37 0.0 +36 38 0.0 +39 40 0.0 +39 41 0.0 +39 42 0.0 +39 43 0.0 +39 44 0.0 +39 45 0.0 +39 46 0.0 +47 48 0.0 +47 49 0.0 +47 50 0.0 +32 35 0.0 +51 52 0.0 +51 53 0.0 +51 54 0.0 +51 55 0.0 +51 56 0.0 +51 57 0.0 +58 59 0.0 +58 60 0.0 +58 61 0.0 +58 62 0.0 +63 64 0.0 +63 65 0.0 +66 67 0.0 +66 68 0.0 +7 69 0.0 +70 71 0.0 +70 72 0.0 +70 73 0.0 +74 75 0.0 +74 76 0.0 +77 78 0.0 +79 80 0.0 +9 81 0.0 +81 82 0.0 +81 83 0.0 +33 81 0.0 +81 84 0.0 +81 85 0.0 +16 81 0.0 +17 81 0.0 +81 86 0.0 +81 87 0.0 +81 88 0.0 +19 81 0.0 +13 81 0.0 +81 89 0.0 +81 90 0.0 +81 91 0.0 +81 92 0.0 +12 81 0.0 +15 81 0.0 +14 81 0.0 +81 93 0.0 +10 81 0.0 +81 94 0.0 +81 95 0.0 +81 96 0.0 +81 97 0.0 +81 98 0.0 +81 99 0.0 +3 81 0.0 +81 100 0.0 +101 102 0.0 +90 103 0.0 +98 103 0.0 +96 103 0.0 +95 103 0.0 +91 103 0.0 +16 103 0.0 +93 103 0.0 +104 105 0.0 +104 106 0.0 +104 107 0.0 +104 108 0.0 +104 109 0.0 +104 110 0.0 +104 111 0.0 +104 112 0.0 +104 113 0.0 +104 114 0.0 +104 115 0.0 +104 116 0.0 +104 117 0.0 +118 119 0.0 +120 121 0.0 +120 122 0.0 +24 123 0.0 +123 124 0.0 +123 125 0.0 +11 123 0.0 +123 126 0.0 +61 127 0.0 +127 128 0.0 +129 130 0.0 +129 131 0.0 +129 132 0.0 +129 133 0.0 +87 129 0.0 +129 134 0.0 +129 135 0.0 +136 137 0.0 +136 138 0.0 +136 139 0.0 +136 140 0.0 +136 141 0.0 +136 142 0.0 +136 143 0.0 +18 144 0.0 +18 21 0.0 +18 20 0.0 +145 146 0.0 +30 31 0.0 +86 147 0.0 +82 147 0.0 +92 147 0.0 +147 148 0.0 +14 147 0.0 +84 147 0.0 +93 147 0.0 +89 147 0.0 +83 147 0.0 +29 147 0.0 +17 147 0.0 +87 147 0.0 +147 149 0.0 +16 147 0.0 +147 150 0.0 +147 151 0.0 +147 152 0.0 +147 153 0.0 +147 154 0.0 +11 155 0.0 +72 156 0.0 +156 157 0.0 +158 159 0.0 +158 160 0.0 +158 161 0.0 +71 158 0.0 +87 162 0.0 +133 162 0.0 +162 163 0.0 +162 164 0.0 +162 165 0.0 +33 166 0.0 +167 168 0.0 +3 167 0.0 +169 170 0.0 +54 171 0.0 +171 172 0.0 +173 174 0.0 +173 175 0.0 +173 176 0.0 +173 177 0.0 +178 179 0.0 +43 178 0.0 +86 178 0.0 +178 180 0.0 +178 181 0.0 +121 178 0.0 +178 182 0.0 +42 178 0.0 +41 178 0.0 +178 183 0.0 +178 184 0.0 +178 185 0.0 +114 178 0.0 +178 186 0.0 +178 187 0.0 +178 188 0.0 +116 178 0.0 +178 189 0.0 +178 190 0.0 +178 191 0.0 +99 192 0.0 +192 193 0.0 +98 192 0.0 +91 192 0.0 +92 192 0.0 +139 192 0.0 +38 192 0.0 +192 194 0.0 +144 192 0.0 +192 195 0.0 +140 192 0.0 +192 196 0.0 +192 197 0.0 +102 192 0.0 +192 198 0.0 +38 199 0.0 +191 200 0.0 +41 191 0.0 +114 191 0.0 +182 191 0.0 +185 191 0.0 +42 191 0.0 +187 191 0.0 +45 191 0.0 +186 191 0.0 +121 191 0.0 +191 201 0.0 +191 202 0.0 +179 191 0.0 +116 191 0.0 +190 191 0.0 +189 191 0.0 +88 203 0.0 +88 204 0.0 +88 205 0.0 +88 117 0.0 +88 206 0.0 +88 207 0.0 +208 209 0.0 +157 208 0.0 +208 210 0.0 +208 211 0.0 +208 212 0.0 +56 208 0.0 +208 213 0.0 +214 215 0.0 +31 62 0.0 +31 76 0.0 +31 204 0.0 +31 216 0.0 +31 128 0.0 +31 217 0.0 +31 218 0.0 +31 163 0.0 +7 31 0.0 +219 220 0.0 +205 221 0.0 +221 222 0.0 +221 223 0.0 +221 224 0.0 +221 225 0.0 +226 227 0.0 +52 228 0.0 +52 57 0.0 +52 54 0.0 +229 230 0.0 +154 231 0.0 +105 154 0.0 +154 205 0.0 +116 154 0.0 +98 154 0.0 +154 232 0.0 +9 154 0.0 +10 154 0.0 +154 233 0.0 +94 154 0.0 +42 154 0.0 +154 234 0.0 +85 154 0.0 +154 185 0.0 +154 235 0.0 +114 154 0.0 +29 154 0.0 +12 154 0.0 +19 154 0.0 +97 154 0.0 +13 154 0.0 +95 154 0.0 +91 154 0.0 +90 154 0.0 +15 154 0.0 +99 154 0.0 +82 154 0.0 +83 154 0.0 +92 154 0.0 +154 236 0.0 +87 154 0.0 +14 154 0.0 +86 154 0.0 +17 154 0.0 +84 154 0.0 +16 154 0.0 +89 154 0.0 +151 154 0.0 +150 154 0.0 +149 154 0.0 +148 154 0.0 +152 154 0.0 +153 154 0.0 +161 237 0.0 +237 238 0.0 +237 239 0.0 +237 240 0.0 +237 241 0.0 +90 237 0.0 +237 242 0.0 +106 237 0.0 +117 237 0.0 +17 237 0.0 +236 237 0.0 +105 237 0.0 +237 243 0.0 +187 237 0.0 +237 244 0.0 +41 237 0.0 +42 237 0.0 +185 237 0.0 +180 237 0.0 +188 237 0.0 +107 245 0.0 +107 240 0.0 +246 247 0.0 +53 246 0.0 +246 248 0.0 +246 249 0.0 +239 246 0.0 +246 250 0.0 +246 251 0.0 +246 252 0.0 +122 246 0.0 +246 253 0.0 +246 254 0.0 +246 255 0.0 +244 246 0.0 +246 256 0.0 +65 246 0.0 +257 258 0.0 +161 257 0.0 +250 257 0.0 +53 257 0.0 +55 259 0.0 +53 55 0.0 +55 57 0.0 +55 260 0.0 +55 261 0.0 +11 98 0.0 +11 86 0.0 +11 82 0.0 +11 235 0.0 +11 91 0.0 +11 99 0.0 +11 96 0.0 +11 85 0.0 +11 94 0.0 +11 92 0.0 +9 11 0.0 +10 11 0.0 +11 97 0.0 +11 84 0.0 +11 13 0.0 +11 20 0.0 +11 16 0.0 +11 14 0.0 +11 17 0.0 +11 83 0.0 +11 15 0.0 +11 89 0.0 +11 93 0.0 +11 90 0.0 +11 19 0.0 +11 150 0.0 +11 105 0.0 +172 262 0.0 +56 263 0.0 +56 264 0.0 +56 265 0.0 +56 266 0.0 +56 87 0.0 +56 267 0.0 +56 268 0.0 +56 269 0.0 +56 133 0.0 +56 270 0.0 +56 271 0.0 +56 224 0.0 +53 56 0.0 +56 272 0.0 +56 273 0.0 +56 57 0.0 +56 274 0.0 +56 275 0.0 +56 215 0.0 +56 276 0.0 +61 277 0.0 +61 278 0.0 +12 279 0.0 +95 279 0.0 +16 279 0.0 +247 279 0.0 +10 279 0.0 +9 279 0.0 +86 279 0.0 +94 279 0.0 +91 279 0.0 +93 279 0.0 +92 279 0.0 +17 279 0.0 +82 279 0.0 +19 279 0.0 +99 279 0.0 +90 279 0.0 +83 279 0.0 +89 279 0.0 +87 279 0.0 +150 279 0.0 +213 279 0.0 +279 280 0.0 +281 282 0.0 +72 281 0.0 +283 284 0.0 +285 286 0.0 +1 285 0.0 +3 285 0.0 +113 287 0.0 +288 289 0.0 +290 291 0.0 +211 290 0.0 +290 292 0.0 +87 293 0.0 +133 293 0.0 +293 294 0.0 +100 293 0.0 +293 295 0.0 +293 296 0.0 +29 297 0.0 +144 297 0.0 +195 297 0.0 +84 298 0.0 +298 299 0.0 +216 298 0.0 +133 298 0.0 +298 300 0.0 +87 298 0.0 +284 298 0.0 +298 301 0.0 +21 110 0.0 +20 21 0.0 +302 303 0.0 +268 275 0.0 +266 268 0.0 +87 210 0.0 +133 210 0.0 +210 304 0.0 +210 305 0.0 +210 306 0.0 +210 258 0.0 +210 307 0.0 +210 212 0.0 +7 210 0.0 +161 308 0.0 +53 308 0.0 +308 309 0.0 +133 308 0.0 +160 308 0.0 +87 308 0.0 +250 308 0.0 +159 270 0.0 +105 207 0.0 +207 310 0.0 +207 311 0.0 +139 142 0.0 +140 142 0.0 +142 143 0.0 +80 142 0.0 +141 142 0.0 +138 142 0.0 +194 312 0.0 +133 212 0.0 +212 313 0.0 +87 212 0.0 +212 305 0.0 +54 212 0.0 +212 306 0.0 +7 212 0.0 +275 314 0.0 +275 315 0.0 +275 316 0.0 +109 275 0.0 +260 275 0.0 +263 275 0.0 +266 275 0.0 +234 275 0.0 +87 275 0.0 +205 275 0.0 +133 275 0.0 +275 317 0.0 +274 275 0.0 +7 275 0.0 +244 275 0.0 +83 311 0.0 +90 311 0.0 +82 311 0.0 +150 311 0.0 +19 311 0.0 +89 311 0.0 +93 311 0.0 +310 311 0.0 +121 318 0.0 +45 121 0.0 +319 320 0.0 +128 319 0.0 +7 319 0.0 +106 321 0.0 +242 321 0.0 +321 322 0.0 +62 323 0.0 +62 232 0.0 +62 324 0.0 +62 153 0.0 +34 62 0.0 +62 325 0.0 +35 62 0.0 +62 278 0.0 +206 326 0.0 +87 326 0.0 +133 326 0.0 +326 327 0.0 +326 328 0.0 +168 326 0.0 +326 329 0.0 +326 330 0.0 +114 200 0.0 +188 200 0.0 +187 200 0.0 +183 200 0.0 +41 200 0.0 +205 331 0.0 +164 332 0.0 +164 165 0.0 +164 292 0.0 +164 291 0.0 +164 333 0.0 +163 164 0.0 +133 164 0.0 +164 218 0.0 +7 164 0.0 +334 335 0.0 +224 334 0.0 +334 336 0.0 +334 337 0.0 +335 338 0.0 +45 230 0.0 +45 339 0.0 +45 340 0.0 +45 114 0.0 +45 46 0.0 +224 335 0.0 +335 336 0.0 +335 337 0.0 +258 341 0.0 +87 258 0.0 +84 258 0.0 +35 320 0.0 +320 342 0.0 +128 320 0.0 +187 289 0.0 +289 343 0.0 +344 345 0.0 +43 116 0.0 +43 241 0.0 +43 114 0.0 +43 180 0.0 +41 43 0.0 +42 43 0.0 +43 185 0.0 +150 346 0.0 +72 346 0.0 +346 347 0.0 +190 346 0.0 +348 349 0.0 +41 179 0.0 +42 179 0.0 +179 184 0.0 +179 185 0.0 +179 183 0.0 +114 179 0.0 +179 202 0.0 +179 190 0.0 +116 179 0.0 +179 189 0.0 +133 350 0.0 +87 350 0.0 +300 350 0.0 +350 351 0.0 +350 352 0.0 +350 353 0.0 +269 350 0.0 +350 354 0.0 +100 350 0.0 +355 356 0.0 +355 357 0.0 +29 144 0.0 +144 358 0.0 +37 144 0.0 +117 144 0.0 +144 359 0.0 +144 360 0.0 +144 361 0.0 +144 362 0.0 +67 144 0.0 +38 144 0.0 +144 198 0.0 +144 363 0.0 +144 197 0.0 +144 364 0.0 +144 195 0.0 +102 144 0.0 +144 196 0.0 +341 365 0.0 +17 366 0.0 +366 367 0.0 +256 366 0.0 +80 366 0.0 +53 366 0.0 +366 368 0.0 +106 366 0.0 +366 369 0.0 +366 370 0.0 +366 371 0.0 +190 372 0.0 +286 373 0.0 +304 374 0.0 +304 375 0.0 +304 376 0.0 +168 304 0.0 +377 378 0.0 +247 253 0.0 +248 253 0.0 +253 368 0.0 +87 234 0.0 +54 87 0.0 +87 185 0.0 +87 198 0.0 +87 247 0.0 +48 87 0.0 +87 379 0.0 +87 380 0.0 +87 381 0.0 +87 382 0.0 +87 220 0.0 +87 383 0.0 +87 330 0.0 +87 384 0.0 +87 109 0.0 +87 385 0.0 +87 165 0.0 +87 386 0.0 +87 100 0.0 +29 87 0.0 +87 124 0.0 +87 370 0.0 +87 265 0.0 +72 87 0.0 +87 360 0.0 +87 352 0.0 +87 151 0.0 +87 387 0.0 +87 351 0.0 +87 388 0.0 +87 353 0.0 +7 87 0.0 +87 269 0.0 +87 105 0.0 +87 116 0.0 +87 389 0.0 +87 254 0.0 +87 343 0.0 +87 300 0.0 +87 264 0.0 +87 354 0.0 +87 236 0.0 +87 135 0.0 +87 390 0.0 +87 391 0.0 +87 209 0.0 +87 160 0.0 +87 306 0.0 +87 392 0.0 +87 393 0.0 +87 163 0.0 +87 295 0.0 +53 87 0.0 +87 232 0.0 +87 294 0.0 +87 213 0.0 +87 130 0.0 +87 296 0.0 +87 284 0.0 +87 132 0.0 +9 87 0.0 +87 301 0.0 +87 148 0.0 +87 149 0.0 +87 152 0.0 +87 394 0.0 +87 153 0.0 +87 131 0.0 +10 87 0.0 +87 133 0.0 +87 96 0.0 +82 87 0.0 +12 87 0.0 +13 87 0.0 +87 92 0.0 +87 94 0.0 +85 87 0.0 +87 150 0.0 +15 87 0.0 +83 87 0.0 +87 89 0.0 +19 87 0.0 +17 87 0.0 +87 95 0.0 +87 90 0.0 +87 91 0.0 +87 98 0.0 +87 99 0.0 +16 87 0.0 +87 93 0.0 +14 87 0.0 +87 97 0.0 +84 87 0.0 +86 87 0.0 +76 204 0.0 +76 163 0.0 +76 313 0.0 +7 76 0.0 +292 390 0.0 +291 292 0.0 +211 292 0.0 +218 292 0.0 +84 292 0.0 +292 395 0.0 +278 396 0.0 +396 397 0.0 +396 398 0.0 +175 396 0.0 +396 399 0.0 +396 400 0.0 +401 402 0.0 +401 403 0.0 +49 50 0.0 +404 405 0.0 +117 406 0.0 +29 150 0.0 +42 150 0.0 +114 150 0.0 +150 360 0.0 +150 407 0.0 +150 238 0.0 +150 343 0.0 +150 408 0.0 +150 340 0.0 +111 150 0.0 +150 185 0.0 +133 150 0.0 +105 150 0.0 +150 235 0.0 +109 150 0.0 +150 389 0.0 +150 205 0.0 +150 236 0.0 +116 150 0.0 +150 151 0.0 +20 150 0.0 +150 234 0.0 +149 150 0.0 +9 150 0.0 +10 150 0.0 +96 150 0.0 +150 152 0.0 +148 150 0.0 +82 150 0.0 +150 153 0.0 +16 150 0.0 +19 150 0.0 +93 150 0.0 +12 150 0.0 +14 150 0.0 +17 150 0.0 +97 150 0.0 +84 150 0.0 +90 150 0.0 +86 150 0.0 +95 150 0.0 +92 150 0.0 +91 150 0.0 +94 150 0.0 +85 150 0.0 +13 150 0.0 +98 150 0.0 +83 150 0.0 +15 150 0.0 +99 150 0.0 +89 150 0.0 +409 410 0.0 +296 411 0.0 +294 296 0.0 +133 296 0.0 +271 412 0.0 +53 271 0.0 +271 272 0.0 +271 276 0.0 +271 273 0.0 +286 413 0.0 +168 375 0.0 +247 414 0.0 +415 416 0.0 +415 417 0.0 +374 418 0.0 +418 419 0.0 +418 420 0.0 +177 421 0.0 +176 177 0.0 +175 177 0.0 +172 422 0.0 +205 423 0.0 +416 417 0.0 +86 234 0.0 +60 234 0.0 +41 234 0.0 +114 234 0.0 +234 424 0.0 +234 386 0.0 +16 234 0.0 +153 234 0.0 +185 234 0.0 +17 234 0.0 +48 234 0.0 +42 234 0.0 +83 234 0.0 +234 236 0.0 +15 234 0.0 +14 234 0.0 +116 234 0.0 +234 314 0.0 +234 316 0.0 +90 234 0.0 +89 234 0.0 +234 315 0.0 +19 234 0.0 +12 234 0.0 +95 234 0.0 +234 260 0.0 +109 234 0.0 +85 234 0.0 +97 234 0.0 +13 234 0.0 +105 234 0.0 +99 234 0.0 +84 234 0.0 +29 234 0.0 +205 234 0.0 +75 425 0.0 +426 427 0.0 +426 428 0.0 +426 429 0.0 +405 426 0.0 +426 430 0.0 +359 362 0.0 +113 362 0.0 +115 362 0.0 +431 432 0.0 +433 434 0.0 +12 236 0.0 +205 236 0.0 +91 236 0.0 +109 236 0.0 +19 236 0.0 +42 236 0.0 +236 435 0.0 +90 236 0.0 +15 236 0.0 +85 236 0.0 +185 236 0.0 +97 236 0.0 +95 236 0.0 +105 236 0.0 +13 236 0.0 +99 236 0.0 +235 236 0.0 +92 236 0.0 +14 236 0.0 +17 236 0.0 +16 236 0.0 +148 236 0.0 +86 236 0.0 +89 236 0.0 +83 236 0.0 +84 236 0.0 +152 236 0.0 +153 236 0.0 +149 236 0.0 +138 140 0.0 +138 139 0.0 +138 143 0.0 +294 323 0.0 +126 294 0.0 +294 354 0.0 +133 294 0.0 +294 436 0.0 +3 168 0.0 +3 437 0.0 +3 4 0.0 +3 100 0.0 +438 439 0.0 +42 205 0.0 +185 205 0.0 +205 386 0.0 +83 205 0.0 +205 235 0.0 +114 205 0.0 +85 205 0.0 +117 205 0.0 +90 205 0.0 +153 205 0.0 +15 205 0.0 +48 205 0.0 +205 408 0.0 +12 205 0.0 +89 205 0.0 +19 205 0.0 +97 205 0.0 +205 314 0.0 +205 316 0.0 +95 205 0.0 +99 205 0.0 +205 315 0.0 +13 205 0.0 +84 205 0.0 +205 260 0.0 +109 205 0.0 +105 205 0.0 +29 205 0.0 +345 440 0.0 +440 441 0.0 +209 440 0.0 +440 442 0.0 +255 440 0.0 +242 440 0.0 +405 430 0.0 +405 428 0.0 +12 20 0.0 +20 85 0.0 +9 20 0.0 +10 20 0.0 +13 20 0.0 +20 97 0.0 +17 20 0.0 +14 20 0.0 +16 20 0.0 +15 20 0.0 +19 20 0.0 +68 443 0.0 +16 41 0.0 +16 29 0.0 +16 435 0.0 +16 111 0.0 +16 133 0.0 +16 235 0.0 +16 151 0.0 +16 389 0.0 +16 444 0.0 +16 343 0.0 +9 16 0.0 +16 148 0.0 +16 124 0.0 +16 149 0.0 +16 152 0.0 +16 109 0.0 +10 16 0.0 +16 116 0.0 +16 153 0.0 +16 82 0.0 +15 16 0.0 +16 83 0.0 +16 89 0.0 +16 99 0.0 +16 92 0.0 +16 98 0.0 +13 16 0.0 +16 96 0.0 +16 85 0.0 +16 94 0.0 +16 91 0.0 +16 97 0.0 +16 86 0.0 +16 95 0.0 +16 90 0.0 +16 84 0.0 +16 93 0.0 +16 19 0.0 +12 16 0.0 +14 16 0.0 +16 17 0.0 +306 445 0.0 +139 141 0.0 +140 141 0.0 +141 143 0.0 +189 446 0.0 +23 447 0.0 +116 447 0.0 +109 447 0.0 +389 447 0.0 +163 397 0.0 +245 448 0.0 +363 448 0.0 +38 448 0.0 +117 448 0.0 +111 449 0.0 +449 450 0.0 +388 449 0.0 +84 282 0.0 +282 386 0.0 +224 282 0.0 +451 452 0.0 +119 436 0.0 +322 442 0.0 +255 322 0.0 +242 322 0.0 +72 161 0.0 +29 72 0.0 +72 453 0.0 +53 72 0.0 +72 220 0.0 +72 242 0.0 +72 180 0.0 +54 72 0.0 +72 133 0.0 +72 347 0.0 +42 72 0.0 +72 185 0.0 +41 72 0.0 +72 190 0.0 +72 388 0.0 +72 383 0.0 +71 72 0.0 +72 157 0.0 +245 454 0.0 +363 454 0.0 +454 455 0.0 +454 456 0.0 +38 454 0.0 +457 458 0.0 +255 441 0.0 +441 442 0.0 +242 441 0.0 +256 270 0.0 +42 256 0.0 +53 256 0.0 +249 256 0.0 +256 367 0.0 +254 256 0.0 +459 460 0.0 +269 386 0.0 +133 269 0.0 +269 385 0.0 +269 353 0.0 +269 352 0.0 +100 269 0.0 +269 354 0.0 +269 351 0.0 +269 300 0.0 +133 295 0.0 +97 133 0.0 +133 247 0.0 +12 133 0.0 +10 133 0.0 +9 133 0.0 +98 133 0.0 +94 133 0.0 +86 133 0.0 +82 133 0.0 +19 133 0.0 +95 133 0.0 +90 133 0.0 +91 133 0.0 +83 133 0.0 +17 133 0.0 +89 133 0.0 +85 133 0.0 +99 133 0.0 +96 133 0.0 +93 133 0.0 +133 379 0.0 +48 133 0.0 +133 380 0.0 +133 381 0.0 +133 382 0.0 +133 383 0.0 +133 384 0.0 +133 385 0.0 +133 220 0.0 +133 370 0.0 +133 149 0.0 +92 133 0.0 +133 165 0.0 +133 265 0.0 +133 386 0.0 +133 330 0.0 +133 360 0.0 +13 133 0.0 +7 133 0.0 +133 353 0.0 +133 388 0.0 +133 352 0.0 +133 300 0.0 +133 387 0.0 +100 133 0.0 +133 461 0.0 +15 133 0.0 +133 351 0.0 +105 133 0.0 +133 354 0.0 +133 301 0.0 +133 254 0.0 +133 135 0.0 +133 209 0.0 +130 133 0.0 +133 390 0.0 +133 160 0.0 +133 213 0.0 +133 306 0.0 +133 163 0.0 +133 392 0.0 +133 393 0.0 +53 133 0.0 +133 391 0.0 +133 284 0.0 +133 264 0.0 +132 133 0.0 +133 232 0.0 +133 394 0.0 +131 133 0.0 +29 343 0.0 +187 343 0.0 +17 343 0.0 +98 343 0.0 +90 343 0.0 +96 343 0.0 +82 343 0.0 +15 343 0.0 +84 343 0.0 +10 343 0.0 +12 343 0.0 +89 343 0.0 +94 343 0.0 +14 343 0.0 +86 343 0.0 +83 343 0.0 +99 343 0.0 +93 343 0.0 +13 343 0.0 +91 343 0.0 +95 343 0.0 +97 343 0.0 +92 343 0.0 +19 343 0.0 +343 462 0.0 +78 463 0.0 +307 464 0.0 +303 430 0.0 +303 428 0.0 +303 427 0.0 +303 402 0.0 +303 403 0.0 +303 460 0.0 +303 465 0.0 +332 466 0.0 +332 467 0.0 +332 381 0.0 +332 382 0.0 +332 468 0.0 +332 469 0.0 +71 161 0.0 +161 244 0.0 +161 309 0.0 +160 161 0.0 +161 250 0.0 +273 412 0.0 +276 412 0.0 +67 117 0.0 +67 102 0.0 +67 363 0.0 +38 67 0.0 +67 242 0.0 +67 450 0.0 +53 160 0.0 +160 190 0.0 +160 309 0.0 +160 250 0.0 +428 470 0.0 +336 428 0.0 +428 429 0.0 +428 471 0.0 +427 428 0.0 +428 430 0.0 +402 428 0.0 +95 124 0.0 +124 472 0.0 +124 265 0.0 +124 473 0.0 +124 474 0.0 +124 151 0.0 +124 152 0.0 +124 475 0.0 +89 124 0.0 +124 476 0.0 +124 477 0.0 +124 424 0.0 +23 124 0.0 +17 124 0.0 +124 435 0.0 +83 124 0.0 +116 124 0.0 +92 124 0.0 +14 124 0.0 +124 444 0.0 +109 124 0.0 +478 479 0.0 +478 480 0.0 +93 111 0.0 +93 424 0.0 +93 462 0.0 +93 149 0.0 +93 116 0.0 +9 93 0.0 +93 235 0.0 +10 93 0.0 +82 93 0.0 +92 93 0.0 +91 93 0.0 +93 94 0.0 +93 96 0.0 +85 93 0.0 +93 98 0.0 +13 93 0.0 +83 93 0.0 +15 93 0.0 +93 99 0.0 +89 93 0.0 +19 93 0.0 +12 93 0.0 +17 93 0.0 +14 93 0.0 +93 97 0.0 +84 93 0.0 +90 93 0.0 +86 93 0.0 +93 95 0.0 +187 189 0.0 +182 189 0.0 +189 190 0.0 +116 189 0.0 +220 383 0.0 +220 379 0.0 +220 481 0.0 +220 370 0.0 +220 265 0.0 +7 204 0.0 +204 482 0.0 +391 483 0.0 +483 484 0.0 +393 485 0.0 +57 485 0.0 +105 265 0.0 +265 444 0.0 +116 265 0.0 +83 265 0.0 +109 265 0.0 +211 265 0.0 +213 265 0.0 +265 370 0.0 +315 316 0.0 +190 250 0.0 +250 309 0.0 +170 486 0.0 +163 333 0.0 +163 291 0.0 +163 218 0.0 +163 487 0.0 +7 163 0.0 +360 382 0.0 +105 382 0.0 +381 382 0.0 +90 435 0.0 +324 435 0.0 +435 477 0.0 +180 435 0.0 +340 435 0.0 +188 435 0.0 +153 435 0.0 +148 435 0.0 +41 435 0.0 +114 435 0.0 +42 435 0.0 +85 435 0.0 +185 435 0.0 +91 435 0.0 +13 435 0.0 +83 435 0.0 +17 435 0.0 +116 435 0.0 +109 435 0.0 +439 488 0.0 +365 439 0.0 +80 371 0.0 +80 143 0.0 +14 185 0.0 +14 105 0.0 +14 102 0.0 +14 151 0.0 +14 198 0.0 +14 29 0.0 +14 444 0.0 +14 389 0.0 +14 149 0.0 +9 14 0.0 +14 235 0.0 +14 148 0.0 +14 152 0.0 +10 14 0.0 +14 153 0.0 +14 109 0.0 +14 82 0.0 +14 96 0.0 +14 116 0.0 +13 14 0.0 +14 98 0.0 +14 85 0.0 +14 94 0.0 +14 91 0.0 +14 92 0.0 +14 89 0.0 +14 99 0.0 +14 15 0.0 +14 83 0.0 +12 14 0.0 +14 17 0.0 +14 19 0.0 +14 86 0.0 +14 95 0.0 +14 90 0.0 +14 84 0.0 +14 97 0.0 +272 489 0.0 +272 273 0.0 +272 276 0.0 +479 490 0.0 +233 239 0.0 +239 276 0.0 +239 255 0.0 +232 239 0.0 +239 491 0.0 +35 239 0.0 +213 239 0.0 +239 492 0.0 +239 242 0.0 +239 244 0.0 +254 354 0.0 +53 254 0.0 +301 493 0.0 +300 493 0.0 +57 276 0.0 +53 57 0.0 +54 57 0.0 +57 386 0.0 +260 261 0.0 +460 494 0.0 +232 495 0.0 +247 495 0.0 +24 300 0.0 +24 126 0.0 +24 475 0.0 +24 496 0.0 +24 35 0.0 +23 24 0.0 +7 24 0.0 +41 95 0.0 +41 386 0.0 +41 99 0.0 +41 190 0.0 +41 497 0.0 +41 241 0.0 +41 116 0.0 +41 46 0.0 +41 187 0.0 +41 340 0.0 +41 184 0.0 +41 243 0.0 +41 183 0.0 +41 114 0.0 +41 180 0.0 +41 188 0.0 +41 42 0.0 +41 185 0.0 +255 442 0.0 +209 255 0.0 +255 492 0.0 +242 255 0.0 +54 255 0.0 +444 473 0.0 +109 473 0.0 +424 473 0.0 +427 471 0.0 +165 291 0.0 +339 378 0.0 +186 378 0.0 +187 378 0.0 +157 383 0.0 +383 388 0.0 +370 383 0.0 +71 383 0.0 +274 276 0.0 +498 499 0.0 +152 387 0.0 +152 238 0.0 +82 152 0.0 +19 152 0.0 +12 152 0.0 +152 408 0.0 +15 152 0.0 +152 477 0.0 +85 152 0.0 +13 152 0.0 +95 152 0.0 +109 152 0.0 +152 235 0.0 +151 152 0.0 +17 152 0.0 +92 152 0.0 +86 152 0.0 +89 152 0.0 +83 152 0.0 +84 152 0.0 +148 152 0.0 +152 153 0.0 +149 152 0.0 +500 501 0.0 +460 502 0.0 +460 503 0.0 +460 504 0.0 +108 460 0.0 +54 460 0.0 +460 465 0.0 +437 505 0.0 +65 247 0.0 +65 185 0.0 +53 65 0.0 +42 65 0.0 +65 244 0.0 +65 248 0.0 +153 238 0.0 +148 238 0.0 +17 238 0.0 +86 238 0.0 +402 403 0.0 +168 376 0.0 +410 506 0.0 +54 507 0.0 +53 248 0.0 +247 248 0.0 +248 264 0.0 +83 424 0.0 +424 463 0.0 +42 424 0.0 +9 424 0.0 +10 424 0.0 +15 424 0.0 +114 424 0.0 +94 424 0.0 +91 424 0.0 +90 424 0.0 +97 424 0.0 +19 424 0.0 +424 475 0.0 +99 424 0.0 +13 424 0.0 +95 424 0.0 +424 474 0.0 +85 424 0.0 +424 508 0.0 +116 424 0.0 +424 444 0.0 +23 424 0.0 +235 424 0.0 +109 424 0.0 +424 477 0.0 +317 509 0.0 +83 185 0.0 +83 111 0.0 +83 151 0.0 +83 389 0.0 +83 444 0.0 +9 83 0.0 +83 149 0.0 +83 148 0.0 +83 116 0.0 +10 83 0.0 +83 109 0.0 +83 153 0.0 +83 96 0.0 +82 83 0.0 +83 92 0.0 +83 91 0.0 +83 94 0.0 +83 85 0.0 +83 98 0.0 +13 83 0.0 +15 83 0.0 +83 99 0.0 +83 89 0.0 +19 83 0.0 +17 83 0.0 +12 83 0.0 +83 97 0.0 +83 84 0.0 +83 90 0.0 +83 95 0.0 +83 86 0.0 +400 510 0.0 +400 511 0.0 +206 400 0.0 +278 400 0.0 +242 512 0.0 +512 513 0.0 +512 514 0.0 +85 185 0.0 +29 85 0.0 +85 117 0.0 +85 477 0.0 +85 105 0.0 +85 153 0.0 +85 116 0.0 +85 109 0.0 +9 85 0.0 +10 85 0.0 +85 96 0.0 +85 235 0.0 +82 85 0.0 +15 85 0.0 +85 99 0.0 +85 89 0.0 +85 92 0.0 +13 85 0.0 +85 98 0.0 +85 91 0.0 +85 94 0.0 +85 97 0.0 +85 90 0.0 +85 95 0.0 +85 86 0.0 +84 85 0.0 +19 85 0.0 +17 85 0.0 +12 85 0.0 +125 300 0.0 +300 360 0.0 +300 385 0.0 +300 301 0.0 +216 300 0.0 +100 300 0.0 +300 351 0.0 +300 352 0.0 +300 354 0.0 +300 353 0.0 +151 408 0.0 +84 408 0.0 +114 408 0.0 +153 408 0.0 +139 368 0.0 +53 368 0.0 +264 368 0.0 +185 241 0.0 +29 185 0.0 +95 185 0.0 +116 185 0.0 +97 185 0.0 +99 185 0.0 +13 185 0.0 +105 185 0.0 +185 240 0.0 +185 190 0.0 +46 185 0.0 +184 185 0.0 +84 185 0.0 +185 187 0.0 +7 185 0.0 +183 185 0.0 +180 185 0.0 +114 185 0.0 +185 243 0.0 +185 188 0.0 +42 185 0.0 +99 462 0.0 +91 462 0.0 +98 462 0.0 +95 462 0.0 +97 462 0.0 +19 462 0.0 +13 462 0.0 +143 195 0.0 +139 143 0.0 +140 143 0.0 +143 467 0.0 +194 247 0.0 +140 194 0.0 +139 194 0.0 +84 510 0.0 +174 352 0.0 +174 421 0.0 +174 175 0.0 +174 176 0.0 +7 323 0.0 +7 515 0.0 +7 516 0.0 +7 276 0.0 +7 517 0.0 +7 53 0.0 +7 242 0.0 +7 218 0.0 +7 305 0.0 +7 213 0.0 +7 165 0.0 +7 170 0.0 +7 306 0.0 +7 172 0.0 +7 244 0.0 +216 301 0.0 +132 390 0.0 +130 390 0.0 +131 390 0.0 +106 339 0.0 +339 340 0.0 +46 339 0.0 +230 339 0.0 +518 519 0.0 +518 520 0.0 +13 29 0.0 +13 105 0.0 +13 153 0.0 +13 109 0.0 +13 116 0.0 +13 148 0.0 +9 13 0.0 +10 13 0.0 +13 82 0.0 +13 96 0.0 +13 235 0.0 +13 98 0.0 +13 94 0.0 +13 91 0.0 +13 92 0.0 +13 89 0.0 +13 99 0.0 +13 15 0.0 +13 17 0.0 +12 13 0.0 +13 19 0.0 +13 95 0.0 +13 86 0.0 +13 90 0.0 +13 84 0.0 +13 97 0.0 +94 116 0.0 +94 148 0.0 +9 94 0.0 +94 235 0.0 +10 94 0.0 +94 96 0.0 +82 94 0.0 +91 94 0.0 +94 98 0.0 +92 94 0.0 +94 99 0.0 +89 94 0.0 +15 94 0.0 +17 94 0.0 +12 94 0.0 +19 94 0.0 +84 94 0.0 +90 94 0.0 +94 95 0.0 +86 94 0.0 +94 97 0.0 +29 42 0.0 +42 386 0.0 +42 116 0.0 +42 46 0.0 +42 84 0.0 +42 105 0.0 +42 190 0.0 +42 184 0.0 +42 187 0.0 +42 243 0.0 +42 183 0.0 +42 188 0.0 +42 114 0.0 +42 180 0.0 +384 484 0.0 +384 521 0.0 +384 522 0.0 +384 388 0.0 +384 387 0.0 +71 184 0.0 +44 188 0.0 +188 354 0.0 +188 244 0.0 +188 386 0.0 +188 340 0.0 +188 243 0.0 +187 188 0.0 +184 188 0.0 +180 188 0.0 +114 188 0.0 +183 188 0.0 +244 523 0.0 +180 241 0.0 +206 329 0.0 +2 329 0.0 +105 329 0.0 +329 330 0.0 +264 309 0.0 +53 309 0.0 +466 524 0.0 +132 233 0.0 +132 232 0.0 +130 132 0.0 +132 135 0.0 +132 461 0.0 +131 132 0.0 +330 437 0.0 +206 330 0.0 +327 330 0.0 +168 330 0.0 +328 330 0.0 +2 330 0.0 +374 419 0.0 +374 420 0.0 +53 264 0.0 +140 323 0.0 +140 467 0.0 +139 140 0.0 +514 525 0.0 +513 525 0.0 +222 223 0.0 +193 526 0.0 +526 527 0.0 +278 325 0.0 +206 278 0.0 +37 193 0.0 +193 528 0.0 +193 195 0.0 +102 193 0.0 +193 197 0.0 +193 198 0.0 +183 386 0.0 +180 183 0.0 +183 186 0.0 +183 243 0.0 +183 184 0.0 +183 187 0.0 +114 183 0.0 +105 183 0.0 +98 463 0.0 +98 245 0.0 +98 102 0.0 +98 116 0.0 +98 198 0.0 +9 98 0.0 +98 235 0.0 +82 98 0.0 +10 98 0.0 +86 98 0.0 +12 98 0.0 +97 98 0.0 +90 98 0.0 +95 98 0.0 +84 98 0.0 +19 98 0.0 +17 98 0.0 +15 98 0.0 +98 99 0.0 +89 98 0.0 +92 98 0.0 +96 98 0.0 +91 98 0.0 +131 232 0.0 +131 233 0.0 +130 131 0.0 +131 135 0.0 +131 461 0.0 +225 529 0.0 +111 529 0.0 +217 530 0.0 +380 388 0.0 +380 531 0.0 +122 380 0.0 +50 245 0.0 +119 225 0.0 +111 119 0.0 +245 456 0.0 +38 245 0.0 +245 532 0.0 +38 455 0.0 +391 484 0.0 +306 391 0.0 +180 190 0.0 +190 533 0.0 +186 190 0.0 +114 190 0.0 +29 190 0.0 +190 347 0.0 +190 201 0.0 +190 202 0.0 +116 190 0.0 +111 225 0.0 +126 323 0.0 +126 352 0.0 +365 488 0.0 +534 535 0.0 +524 536 0.0 +92 111 0.0 +92 151 0.0 +92 389 0.0 +92 444 0.0 +29 92 0.0 +92 198 0.0 +9 92 0.0 +92 149 0.0 +92 148 0.0 +92 153 0.0 +10 92 0.0 +92 109 0.0 +92 116 0.0 +82 92 0.0 +92 96 0.0 +15 92 0.0 +92 99 0.0 +89 92 0.0 +91 92 0.0 +92 97 0.0 +90 92 0.0 +86 92 0.0 +92 95 0.0 +84 92 0.0 +19 92 0.0 +12 92 0.0 +17 92 0.0 +114 386 0.0 +46 386 0.0 +333 537 0.0 +153 323 0.0 +116 153 0.0 +97 153 0.0 +153 233 0.0 +153 232 0.0 +99 153 0.0 +15 153 0.0 +12 153 0.0 +19 153 0.0 +95 153 0.0 +109 153 0.0 +82 153 0.0 +17 153 0.0 +86 153 0.0 +89 153 0.0 +84 153 0.0 +151 153 0.0 +148 153 0.0 +149 153 0.0 +130 135 0.0 +340 497 0.0 +475 477 0.0 +109 475 0.0 +116 475 0.0 +370 538 0.0 +370 387 0.0 +370 371 0.0 +539 540 0.0 +305 539 0.0 +399 519 0.0 +284 399 0.0 +541 542 0.0 +89 184 0.0 +184 243 0.0 +84 184 0.0 +114 184 0.0 +86 184 0.0 +184 186 0.0 +184 187 0.0 +327 328 0.0 +186 273 0.0 +224 273 0.0 +273 543 0.0 +267 273 0.0 +273 276 0.0 +323 354 0.0 +352 354 0.0 +100 354 0.0 +351 354 0.0 +353 354 0.0 +37 198 0.0 +37 38 0.0 +37 102 0.0 +37 463 0.0 +37 117 0.0 +267 276 0.0 +95 148 0.0 +95 117 0.0 +95 477 0.0 +95 444 0.0 +95 151 0.0 +95 105 0.0 +95 116 0.0 +95 109 0.0 +9 95 0.0 +95 235 0.0 +10 95 0.0 +82 95 0.0 +84 95 0.0 +90 95 0.0 +86 95 0.0 +95 97 0.0 +12 95 0.0 +17 95 0.0 +19 95 0.0 +95 99 0.0 +89 95 0.0 +15 95 0.0 +91 95 0.0 +95 96 0.0 +172 544 0.0 +203 388 0.0 +23 508 0.0 +109 508 0.0 +444 508 0.0 +545 546 0.0 +105 514 0.0 +242 514 0.0 +389 514 0.0 +230 514 0.0 +53 514 0.0 +172 514 0.0 +513 514 0.0 +96 463 0.0 +117 235 0.0 +151 235 0.0 +17 235 0.0 +109 235 0.0 +10 235 0.0 +9 235 0.0 +89 235 0.0 +116 235 0.0 +12 235 0.0 +96 235 0.0 +99 235 0.0 +90 235 0.0 +15 235 0.0 +97 235 0.0 +84 235 0.0 +91 235 0.0 +19 235 0.0 +113 547 0.0 +38 548 0.0 +38 115 0.0 +38 456 0.0 +38 195 0.0 +38 197 0.0 +38 102 0.0 +38 363 0.0 +284 519 0.0 +549 550 0.0 +89 551 0.0 +113 551 0.0 +84 551 0.0 +97 551 0.0 +10 407 0.0 +9 407 0.0 +109 407 0.0 +84 407 0.0 +15 407 0.0 +105 407 0.0 +187 243 0.0 +180 187 0.0 +187 340 0.0 +114 187 0.0 +186 187 0.0 +53 242 0.0 +53 54 0.0 +53 371 0.0 +53 232 0.0 +53 513 0.0 +53 209 0.0 +23 552 0.0 +165 333 0.0 +211 333 0.0 +102 111 0.0 +86 102 0.0 +102 115 0.0 +102 117 0.0 +29 102 0.0 +97 102 0.0 +102 361 0.0 +102 528 0.0 +102 527 0.0 +99 102 0.0 +102 196 0.0 +102 197 0.0 +102 198 0.0 +102 195 0.0 +305 306 0.0 +306 540 0.0 +23 389 0.0 +116 389 0.0 +109 389 0.0 +86 389 0.0 +17 389 0.0 +89 389 0.0 +230 389 0.0 +157 247 0.0 +247 553 0.0 +247 442 0.0 +244 247 0.0 +82 151 0.0 +17 151 0.0 +86 151 0.0 +151 477 0.0 +89 151 0.0 +109 151 0.0 +84 151 0.0 +149 151 0.0 +148 151 0.0 +73 492 0.0 +213 492 0.0 +242 492 0.0 +54 492 0.0 +244 492 0.0 +109 316 0.0 +109 554 0.0 +109 113 0.0 +19 109 0.0 +15 109 0.0 +109 474 0.0 +84 109 0.0 +109 114 0.0 +90 109 0.0 +89 109 0.0 +109 477 0.0 +17 109 0.0 +109 444 0.0 +23 109 0.0 +109 116 0.0 +444 476 0.0 +91 444 0.0 +89 444 0.0 +444 474 0.0 +23 444 0.0 +17 444 0.0 +444 477 0.0 +116 444 0.0 +168 437 0.0 +186 555 0.0 +15 360 0.0 +15 148 0.0 +15 105 0.0 +15 111 0.0 +15 116 0.0 +9 15 0.0 +10 15 0.0 +15 82 0.0 +15 96 0.0 +15 19 0.0 +15 17 0.0 +15 90 0.0 +15 89 0.0 +12 15 0.0 +15 97 0.0 +15 84 0.0 +15 86 0.0 +15 91 0.0 +15 99 0.0 +233 387 0.0 +387 388 0.0 +116 180 0.0 +46 180 0.0 +105 180 0.0 +114 180 0.0 +522 556 0.0 +175 421 0.0 +175 176 0.0 +419 420 0.0 +89 111 0.0 +84 111 0.0 +111 450 0.0 +90 111 0.0 +105 111 0.0 +99 111 0.0 +86 111 0.0 +111 360 0.0 +91 111 0.0 +19 111 0.0 +2 105 0.0 +29 91 0.0 +91 360 0.0 +91 116 0.0 +91 198 0.0 +9 91 0.0 +10 91 0.0 +82 91 0.0 +91 96 0.0 +89 91 0.0 +91 99 0.0 +19 91 0.0 +12 91 0.0 +17 91 0.0 +91 97 0.0 +86 91 0.0 +90 91 0.0 +84 91 0.0 +211 499 0.0 +84 211 0.0 +557 558 0.0 +54 450 0.0 +206 209 0.0 +206 559 0.0 +115 197 0.0 +388 560 0.0 +402 429 0.0 +402 427 0.0 +402 430 0.0 +99 114 0.0 +105 114 0.0 +29 114 0.0 +114 116 0.0 +114 243 0.0 +84 114 0.0 +114 340 0.0 +46 114 0.0 +195 528 0.0 +198 528 0.0 +353 385 0.0 +352 353 0.0 +351 353 0.0 +100 353 0.0 +351 352 0.0 +100 351 0.0 +477 554 0.0 +305 540 0.0 +360 381 0.0 +105 381 0.0 +68 561 0.0 +73 562 0.0 +176 421 0.0 +100 352 0.0 +116 477 0.0 +46 116 0.0 +9 116 0.0 +10 116 0.0 +86 116 0.0 +12 116 0.0 +96 116 0.0 +84 116 0.0 +90 116 0.0 +97 116 0.0 +82 116 0.0 +19 116 0.0 +99 116 0.0 +110 116 0.0 +23 116 0.0 +89 116 0.0 +17 116 0.0 +209 563 0.0 +209 442 0.0 +209 242 0.0 +54 209 0.0 +195 361 0.0 +197 361 0.0 +198 361 0.0 +361 388 0.0 +17 23 0.0 +23 477 0.0 +172 317 0.0 +172 513 0.0 +54 172 0.0 +17 29 0.0 +17 110 0.0 +17 198 0.0 +9 17 0.0 +17 148 0.0 +17 149 0.0 +10 17 0.0 +17 82 0.0 +17 96 0.0 +17 99 0.0 +17 89 0.0 +12 17 0.0 +17 19 0.0 +17 84 0.0 +17 90 0.0 +17 86 0.0 +17 97 0.0 +213 280 0.0 +263 266 0.0 +564 565 0.0 +242 491 0.0 +35 491 0.0 +244 491 0.0 +186 202 0.0 +29 566 0.0 +106 371 0.0 +356 357 0.0 +323 567 0.0 +165 218 0.0 +224 336 0.0 +224 337 0.0 +224 276 0.0 +27 54 0.0 +148 568 0.0 +233 244 0.0 +29 244 0.0 +35 244 0.0 +244 276 0.0 +54 244 0.0 +244 388 0.0 +117 244 0.0 +232 244 0.0 +213 244 0.0 +242 244 0.0 +218 562 0.0 +336 337 0.0 +427 429 0.0 +429 430 0.0 +1 213 0.0 +242 513 0.0 +9 96 0.0 +10 96 0.0 +82 96 0.0 +86 96 0.0 +84 96 0.0 +12 96 0.0 +96 97 0.0 +19 96 0.0 +96 99 0.0 +89 96 0.0 +90 96 0.0 +54 105 0.0 +54 243 0.0 +168 336 0.0 +84 113 0.0 +113 117 0.0 +105 215 0.0 +105 276 0.0 +12 105 0.0 +9 12 0.0 +10 12 0.0 +12 82 0.0 +12 19 0.0 +12 97 0.0 +12 84 0.0 +12 86 0.0 +12 90 0.0 +12 89 0.0 +12 99 0.0 +474 477 0.0 +201 202 0.0 +82 232 0.0 +35 232 0.0 +232 442 0.0 +232 233 0.0 +64 232 0.0 +97 360 0.0 +84 360 0.0 +99 360 0.0 +19 360 0.0 +105 360 0.0 +196 364 0.0 +427 430 0.0 +99 196 0.0 +196 197 0.0 +196 198 0.0 +195 196 0.0 +29 149 0.0 +82 149 0.0 +86 149 0.0 +148 149 0.0 +84 149 0.0 +89 149 0.0 +242 442 0.0 +19 29 0.0 +9 19 0.0 +10 19 0.0 +19 82 0.0 +19 99 0.0 +19 89 0.0 +19 84 0.0 +19 90 0.0 +19 86 0.0 +19 97 0.0 +139 467 0.0 +86 198 0.0 +29 198 0.0 +97 198 0.0 +99 198 0.0 +195 198 0.0 +197 198 0.0 +84 323 0.0 +29 84 0.0 +84 301 0.0 +84 105 0.0 +9 84 0.0 +84 148 0.0 +10 84 0.0 +82 84 0.0 +84 388 0.0 +84 90 0.0 +84 89 0.0 +84 97 0.0 +84 86 0.0 +84 99 0.0 +34 35 0.0 +33 34 0.0 +195 197 0.0 +97 105 0.0 +99 105 0.0 +105 117 0.0 +105 517 0.0 +517 569 0.0 +46 230 0.0 +230 340 0.0 +570 571 0.0 +369 371 0.0 +117 532 0.0 +195 527 0.0 +9 90 0.0 +10 90 0.0 +82 90 0.0 +89 90 0.0 +90 99 0.0 +90 97 0.0 +86 90 0.0 +29 86 0.0 +29 97 0.0 +29 99 0.0 +46 340 0.0 +213 284 0.0 +157 572 0.0 +10 82 0.0 +10 86 0.0 +10 89 0.0 +10 99 0.0 +10 97 0.0 +9 97 0.0 +82 97 0.0 +86 97 0.0 +89 97 0.0 +97 99 0.0 +9 86 0.0 +9 82 0.0 +9 89 0.0 +9 99 0.0 +99 117 0.0 +99 148 0.0 +82 99 0.0 +86 99 0.0 +89 99 0.0 +301 550 0.0 +157 388 0.0 +89 148 0.0 +82 89 0.0 +86 89 0.0 +213 301 0.0 +130 461 0.0 +82 148 0.0 +82 86 0.0 +388 521 0.0 +86 148 0.0 diff --git a/results/networks/model_nodes.txt b/results/networks/model_nodes.txt new file mode 100644 index 0000000..1c31085 --- /dev/null +++ b/results/networks/model_nodes.txt @@ -0,0 +1,574 @@ +node_id alias shape size color x y weight +0 VAMP3 ELLIPSE 20.0 #ffcccc 509.94 37.11 0.0 +1 VPS53 ELLIPSE 20.0 #ffcccc 426.1 192.06 0.0 +2 PICALM ELLIPSE 20.0 #ffcccc 230.49 122.35 0.0 +3 STX5 ELLIPSE 20.0 #ffcccc 393.29 22.8 0.0 +4 SNAP47 ELLIPSE 20.0 #ffcccc 614.44 -72.34 0.0 +5 PKP2 ELLIPSE 20.0 #ffcccc 159.97 1087.33 0.0 +6 KRT18 ELLIPSE 20.0 #ffcccc 245.34 1330.12 0.0 +7 CTNNB1 ELLIPSE 20.0 #ffcccc -50.61 641.73 0.0 +8 MRPS35 ELLIPSE 20.0 #ffcccc -574.2 88.33 0.0 +9 C18orf32 ELLIPSE 20.0 #ffcccc -374.66 156.25 0.0 +10 RPL17-C18orf32 ELLIPSE 20.0 #ffcccc -356.15 151.35 0.0 +11 HSPBP1 ELLIPSE 20.0 #ffcccc -384.98 32.64 0.0 +12 RPL10 ELLIPSE 20.0 #ffcccc -434.24 113.75 0.0 +13 RPL3 ELLIPSE 20.0 #ffcccc -423.12 105.81 0.0 +14 RPS15A ELLIPSE 20.0 #ffcccc -482.34 115.58 0.0 +15 RPL13A ELLIPSE 20.0 #ffcccc -398.99 137.44 0.0 +16 RPS23 ELLIPSE 20.0 #ffcccc -447.4 84.53 0.0 +17 RPS14 ELLIPSE 20.0 #ffcccc -422.63 114.01 0.0 +18 MRPL51 ELLIPSE 20.0 #ffcccc -823.67 6.22 0.0 +19 RPL23 ELLIPSE 20.0 #ffcccc -464.6 131.99 0.0 +20 MRPL33 ELLIPSE 20.0 #ffcccc -536.2 31.95 0.0 +21 MRPS18B ELLIPSE 20.0 #ffcccc -755.64 -68.33 0.0 +22 TNS1 ELLIPSE 20.0 #ffcccc 198.61 163.5 0.0 +23 NOLC1 ELLIPSE 20.0 #ffcccc -113.28 37.12 0.0 +24 ZYX ELLIPSE 20.0 #ffcccc 102.54 277.44 0.0 +25 VCL ELLIPSE 20.0 #ffcccc 197.34 409.57 0.0 +26 SLC22A4 ELLIPSE 20.0 #ffcccc -372.04 1314.96 0.0 +27 PDZK1 ELLIPSE 20.0 #ffcccc -309.8 1003.47 0.0 +28 PDRG1 ELLIPSE 20.0 #ffcccc -853.72 -259.75 0.0 +29 PFDN5 ELLIPSE 20.0 #ffcccc -582.8 61.1 0.0 +30 TENT4A ELLIPSE 20.0 #ffcccc 377.05 635.17 0.0 +31 RAP1B ELLIPSE 20.0 #ffcccc 213.46 753.07 0.0 +32 MYL12A ELLIPSE 20.0 #ffcccc 311.35 551.81 0.0 +33 MANF ELLIPSE 20.0 #ffcccc 310.85 282.86 0.0 +34 WDR1 ELLIPSE 20.0 #ffcccc 308.6 462.64 0.0 +35 ACTG1 ELLIPSE 20.0 #ffcccc 31.69 513.71 0.0 +36 HSCB ELLIPSE 20.0 #ffcccc -1323.18 -47.82 0.0 +37 PMPCA ELLIPSE 20.0 #ffcccc -1017.7 -5.2 0.0 +38 SDHB ELLIPSE 20.0 #ffcccc -1193.7 2.41 0.0 +39 PNN ELLIPSE 20.0 #ffcccc -514.15 -416.36 0.0 +40 RSRC2 ELLIPSE 20.0 #ffcccc -559.77 -767.95 0.0 +41 HNRNPM ELLIPSE 20.0 #ffcccc -501.53 -142.98 0.0 +42 HNRNPA2B1 ELLIPSE 20.0 #ffcccc -497.34 -31.06 0.0 +43 HNRNPH3 ELLIPSE 20.0 #ffcccc -509.73 -237.95 0.0 +44 ARGLU1 ELLIPSE 20.0 #ffcccc -440.35 -528.75 0.0 +45 CASC3 ELLIPSE 20.0 #ffcccc -575.95 -364.05 0.0 +46 RNPS1 ELLIPSE 20.0 #ffcccc -479.22 -215.29 0.0 +47 ACOT8 ELLIPSE 20.0 #ffcccc -1113.99 -338.3 0.0 +48 PEX7 ELLIPSE 20.0 #ffcccc -571.71 -3.56 0.0 +49 PAOX ELLIPSE 20.0 #ffcccc -1332.14 -483.08 0.0 +50 GNPAT ELLIPSE 20.0 #ffcccc -1298.08 -372.22 0.0 +51 STAG2 ELLIPSE 20.0 #ffcccc -69.8 282.64 0.0 +52 JUND ELLIPSE 20.0 #ffcccc 139.51 337.95 0.0 +53 HIST1H2AC ELLIPSE 20.0 #ffcccc -450.77 410.11 0.0 +54 ESR1 ELLIPSE 20.0 #ffcccc -250.49 409.03 0.0 +55 TERF2 ELLIPSE 20.0 #ffcccc 69.31 84.0 0.0 +56 CCNB1 ELLIPSE 20.0 #ffcccc -101.73 114.82 0.0 +57 SMC1A ELLIPSE 20.0 #ffcccc -39.57 213.34 0.0 +58 CORO1A ELLIPSE 20.0 #ffcccc 576.31 339.4 0.0 +59 CD37 ELLIPSE 20.0 #ffcccc 826.98 303.89 0.0 +60 POC1A ELLIPSE 20.0 #ffcccc 304.83 106.23 0.0 +61 DOCK2 ELLIPSE 20.0 #ffcccc 765.82 541.39 0.0 +62 ACTR3 ELLIPSE 20.0 #ffcccc 153.72 439.95 0.0 +63 MGA ELLIPSE 20.0 #ffcccc -805.98 752.7 0.0 +64 BOLA2-SMG1P6 ELLIPSE 20.0 #ffcccc -632.98 819.41 0.0 +65 CBX3 ELLIPSE 20.0 #ffcccc -630.48 392.63 0.0 +66 GSR ELLIPSE 20.0 #ffcccc -1507.04 233.54 0.0 +67 PDHB ELLIPSE 20.0 #ffcccc -1010.36 183.82 0.0 +68 GSTP1 ELLIPSE 20.0 #ffcccc -1814.53 254.78 0.0 +69 TLE5 ELLIPSE 20.0 #ffcccc 197.9 863.38 0.0 +70 SNAPC2 ELLIPSE 20.0 #ffcccc -750.74 632.84 0.0 +71 GTF2E2 ELLIPSE 20.0 #ffcccc -770.68 351.95 0.0 +72 POLR2G ELLIPSE 20.0 #ffcccc -604.01 243.7 0.0 +73 POLR3G ELLIPSE 20.0 #ffcccc -551.14 931.8 0.0 +74 RABAC1 ELLIPSE 20.0 #ffcccc 348.67 1315.69 0.0 +75 NTAQ1 ELLIPSE 20.0 #ffcccc 457.58 1541.3 0.0 +76 RAB5A ELLIPSE 20.0 #ffcccc 156.37 951.26 0.0 +77 CHN2 ELLIPSE 20.0 #ffcccc -1305.43 -649.3 0.0 +78 KMT5B ELLIPSE 20.0 #ffcccc -1145.65 -467.04 0.0 +79 FIS1 ELLIPSE 20.0 #ffcccc -1492.47 559.55 0.0 +80 MAF1 ELLIPSE 20.0 #ffcccc -1219.87 511.76 0.0 +81 SEC61B ELLIPSE 20.0 #ffcccc -261.69 142.38 0.0 +82 RPS10-NUDT3 ELLIPSE 20.0 #ffcccc -424.02 215.48 0.0 +83 RPS7 ELLIPSE 20.0 #ffcccc -377.69 118.45 0.0 +84 RACK1 ELLIPSE 20.0 #ffcccc -353.77 196.08 0.0 +85 RPL7 ELLIPSE 20.0 #ffcccc -375.1 89.32 0.0 +86 RPS10 ELLIPSE 20.0 #ffcccc -459.13 61.65 0.0 +87 RPS27A ELLIPSE 20.0 #ffcccc -321.64 305.85 0.0 +88 CANX ELLIPSE 20.0 #ffcccc -247.66 349.25 0.0 +89 RPS19 ELLIPSE 20.0 #ffcccc -333.85 131.23 0.0 +90 RPL18 ELLIPSE 20.0 #ffcccc -377.83 198.52 0.0 +91 RPL24 ELLIPSE 20.0 #ffcccc -486.16 160.42 0.0 +92 RPS27 ELLIPSE 20.0 #ffcccc -441.76 146.67 0.0 +93 RPL38 ELLIPSE 20.0 #ffcccc -455.56 183.86 0.0 +94 RPL22 ELLIPSE 20.0 #ffcccc -389.12 215.99 0.0 +95 RPL7A ELLIPSE 20.0 #ffcccc -431.34 47.63 0.0 +96 RPL36A ELLIPSE 20.0 #ffcccc -493.84 179.17 0.0 +97 RPL26 ELLIPSE 20.0 #ffcccc -503.66 125.42 0.0 +98 RPL39 ELLIPSE 20.0 #ffcccc -551.56 128.01 0.0 +99 RPL27 ELLIPSE 20.0 #ffcccc -527.45 106.57 0.0 +100 UBE2J2 ELLIPSE 20.0 #ffcccc -30.13 267.8 0.0 +101 SFXN3 ELLIPSE 20.0 #ffcccc -1218.11 -58.67 0.0 +102 UQCRQ ELLIPSE 20.0 #ffcccc -853.91 78.17 0.0 +103 NUFIP2 ELLIPSE 20.0 #ffcccc -594.53 164.76 0.0 +104 C1QBP ELLIPSE 20.0 #ffcccc -631.76 -160.99 0.0 +105 HSPA8 ELLIPSE 20.0 #ffcccc -302.84 172.4 0.0 +106 UBAP2L ELLIPSE 20.0 #ffcccc -804.28 153.92 0.0 +107 GRSF1 ELLIPSE 20.0 #ffcccc -941.54 -297.07 0.0 +108 MAGED2 ELLIPSE 20.0 #ffcccc -303.2 -616.17 0.0 +109 NOP56 ELLIPSE 20.0 #ffcccc -333.69 22.22 0.0 +110 SSBP1 ELLIPSE 20.0 #ffcccc -642.76 -85.54 0.0 +111 NME2 ELLIPSE 20.0 #ffcccc -448.9 -18.74 0.0 +112 GP1BB ELLIPSE 20.0 #ffcccc -802.67 -532.91 0.0 +113 TOMM40 ELLIPSE 20.0 #ffcccc -771.97 -165.62 0.0 +114 DDX39B ELLIPSE 20.0 #ffcccc -455.53 -100.09 0.0 +115 CHCHD2 ELLIPSE 20.0 #ffcccc -1008.83 -84.1 0.0 +116 SNU13 ELLIPSE 20.0 #ffcccc -423.64 4.53 0.0 +117 PHB1 ELLIPSE 20.0 #ffcccc -689.94 35.61 0.0 +118 TMEM97 ELLIPSE 20.0 #ffcccc -100.93 -626.81 0.0 +119 GUK1 ELLIPSE 20.0 #ffcccc -163.69 -492.3 0.0 +120 JADE1 ELLIPSE 20.0 #ffcccc -1084.1 -112.03 0.0 +121 YJU2 ELLIPSE 20.0 #ffcccc -837.04 -402.14 0.0 +122 ING4 ELLIPSE 20.0 #ffcccc -995.51 325.08 0.0 +123 ZPR1 ELLIPSE 20.0 #ffcccc -9.26 134.15 0.0 +124 WDR3 ELLIPSE 20.0 #ffcccc -240.35 16.59 0.0 +125 UBE4B ELLIPSE 20.0 #ffcccc 177.83 268.94 0.0 +126 UFC1 ELLIPSE 20.0 #ffcccc 44.67 299.09 0.0 +127 IL10RA ELLIPSE 20.0 #ffcccc 754.55 764.59 0.0 +128 ITGAL ELLIPSE 20.0 #ffcccc 517.5 834.15 0.0 +129 GLI1 ELLIPSE 20.0 #ffcccc -326.13 682.9 0.0 +130 SEM1 ELLIPSE 20.0 #ffcccc -234.68 598.31 0.0 +131 PSMB5 ELLIPSE 20.0 #ffcccc -308.58 549.26 0.0 +132 PSMB10 ELLIPSE 20.0 #ffcccc -263.6 535.75 0.0 +133 UBB ELLIPSE 20.0 #ffcccc -308.94 360.94 0.0 +134 PTCH2 ELLIPSE 20.0 #ffcccc -403.19 1066.49 0.0 +135 SUFU ELLIPSE 20.0 #ffcccc -351.24 574.7 0.0 +136 ITFG2 ELLIPSE 20.0 #ffcccc -1357.53 713.25 0.0 +137 BTN2A1 ELLIPSE 20.0 #ffcccc -1554.82 819.72 0.0 +138 WDR24 ELLIPSE 20.0 #ffcccc -1270.09 735.0 0.0 +139 ATP6V0B ELLIPSE 20.0 #ffcccc -1166.07 613.91 0.0 +140 ATP6V1H ELLIPSE 20.0 #ffcccc -1078.9 610.79 0.0 +141 BMT2 ELLIPSE 20.0 #ffcccc -1287.82 696.35 0.0 +142 RHEB ELLIPSE 20.0 #ffcccc -1313.32 633.36 0.0 +143 LAMTOR4 ELLIPSE 20.0 #ffcccc -1245.99 594.86 0.0 +144 NDUFB10 ELLIPSE 20.0 #ffcccc -979.88 61.27 0.0 +145 GPLD1 ELLIPSE 20.0 #ffcccc 1667.31 110.5 0.0 +146 PIGW ELLIPSE 20.0 #ffcccc 1771.44 106.85 0.0 +147 EIF1B ELLIPSE 20.0 #ffcccc -461.54 204.48 0.0 +148 EIF3L ELLIPSE 20.0 #ffcccc -326.62 38.81 0.0 +149 EIF1 ELLIPSE 20.0 #ffcccc -425.81 171.06 0.0 +150 RPS3 ELLIPSE 20.0 #ffcccc -402.31 77.49 0.0 +151 EIF3CL ELLIPSE 20.0 #ffcccc -321.2 75.75 0.0 +152 EIF3C ELLIPSE 20.0 #ffcccc -321.93 109.18 0.0 +153 EIF3A ELLIPSE 20.0 #ffcccc -326.9 166.65 0.0 +154 EIF3G ELLIPSE 20.0 #ffcccc -394.5 77.46 0.0 +155 TTC31 ELLIPSE 20.0 #ffcccc -334.42 -398.69 0.0 +156 TCEANC2 ELLIPSE 20.0 #ffcccc -883.1 513.21 0.0 +157 SUPT5H ELLIPSE 20.0 #ffcccc -696.58 607.17 0.0 +158 TBPL1 ELLIPSE 20.0 #ffcccc -913.67 370.93 0.0 +159 KPNA3 ELLIPSE 20.0 #ffcccc -1071.76 378.91 0.0 +160 TADA2B ELLIPSE 20.0 #ffcccc -620.98 300.36 0.0 +161 YEATS2 ELLIPSE 20.0 #ffcccc -690.31 346.4 0.0 +162 FGF23 ELLIPSE 20.0 #ffcccc -178.94 646.11 0.0 +163 MET ELLIPSE 20.0 #ffcccc -24.55 788.5 0.0 +164 KDR ELLIPSE 20.0 #ffcccc -223.35 819.77 0.0 +165 FGFR1 ELLIPSE 20.0 #ffcccc -180.7 738.99 0.0 +166 SLC35B1 ELLIPSE 20.0 #ffcccc 630.9 243.92 0.0 +167 TFG ELLIPSE 20.0 #ffcccc 601.53 -147.67 0.0 +168 GRIA1 ELLIPSE 20.0 #ffcccc 514.81 -58.83 0.0 +169 ACVR2A ELLIPSE 20.0 #ffcccc 104.26 1479.42 0.0 +170 MAGI2 ELLIPSE 20.0 #ffcccc 93.52 1238.44 0.0 +171 TWIST1 ELLIPSE 20.0 #ffcccc -95.22 788.59 0.0 +172 FOXO3 ELLIPSE 20.0 #ffcccc -158.06 865.26 0.0 +173 PLA2G12A ELLIPSE 20.0 #ffcccc 971.22 792.9 0.0 +174 PEDS1-UBE2V1 ELLIPSE 20.0 #ffcccc 743.95 698.69 0.0 +175 PLD4 ELLIPSE 20.0 #ffcccc 880.22 785.73 0.0 +176 PLD3 ELLIPSE 20.0 #ffcccc 938.07 853.85 0.0 +177 LPCAT1 ELLIPSE 20.0 #ffcccc 1047.64 848.59 0.0 +178 SNRPA ELLIPSE 20.0 #ffcccc -574.27 -244.76 0.0 +179 MFAP1 ELLIPSE 20.0 #ffcccc -577.14 -196.35 0.0 +180 HNRNPA3 ELLIPSE 20.0 #ffcccc -534.15 -100.72 0.0 +181 MBNL2 ELLIPSE 20.0 #ffcccc -684.44 -622.04 0.0 +182 FMC1-LUC7L2 ELLIPSE 20.0 #ffcccc -684.51 -486.33 0.0 +183 CTNNBL1 ELLIPSE 20.0 #ffcccc -445.23 -179.6 0.0 +184 FUBP1 ELLIPSE 20.0 #ffcccc -555.03 -64.46 0.0 +185 HNRNPA1 ELLIPSE 20.0 #ffcccc -502.11 1.64 0.0 +186 RBM17 ELLIPSE 20.0 #ffcccc -486.54 -368.44 0.0 +187 SF1 ELLIPSE 20.0 #ffcccc -537.95 -217.15 0.0 +188 SFPQ ELLIPSE 20.0 #ffcccc -419.46 -124.53 0.0 +189 SART1 ELLIPSE 20.0 #ffcccc -641.45 -363.58 0.0 +190 SF3B5 ELLIPSE 20.0 #ffcccc -670.38 -137.05 0.0 +191 SNRPB2 ELLIPSE 20.0 #ffcccc -618.06 -273.76 0.0 +192 ATP5F1E ELLIPSE 20.0 #ffcccc -895.75 229.43 0.0 +193 MT-CO3 ELLIPSE 20.0 #ffcccc -1099.23 126.5 0.0 +194 PPA2 ELLIPSE 20.0 #ffcccc -1088.49 531.2 0.0 +195 UQCR11 ELLIPSE 20.0 #ffcccc -1067.87 183.05 0.0 +196 NDUFB2 ELLIPSE 20.0 #ffcccc -943.76 124.45 0.0 +197 COX6C ELLIPSE 20.0 #ffcccc -1030.7 95.87 0.0 +198 COX7C ELLIPSE 20.0 #ffcccc -746.18 121.49 0.0 +199 CLPP ELLIPSE 20.0 #ffcccc -1501.41 -67.07 0.0 +200 DNAJC8 ELLIPSE 20.0 #ffcccc -498.07 -312.41 0.0 +201 HTATSF1 ELLIPSE 20.0 #ffcccc -768.73 -416.11 0.0 +202 DDX46 ELLIPSE 20.0 #ffcccc -679.14 -392.08 0.0 +203 RAB40A ELLIPSE 20.0 #ffcccc -523.68 618.43 0.0 +204 RAB8B ELLIPSE 20.0 #ffcccc 87.23 799.16 0.0 +205 CCT3 ELLIPSE 20.0 #ffcccc -314.18 -25.23 0.0 +206 HLA-DRA ELLIPSE 20.0 #ffcccc 249.25 406.39 0.0 +207 KCNH2 ELLIPSE 20.0 #ffcccc -537.66 320.11 0.0 +208 PIN1 ELLIPSE 20.0 #ffcccc -217.32 562.25 0.0 +209 NCOR2 ELLIPSE 20.0 #ffcccc -322.34 623.59 0.0 +210 PPP2R5A ELLIPSE 20.0 #ffcccc -2.39 585.36 0.0 +211 PRKCD ELLIPSE 20.0 #ffcccc -265.33 779.62 0.0 +212 AXIN1 ELLIPSE 20.0 #ffcccc -124.18 645.8 0.0 +213 IRF3 ELLIPSE 20.0 #ffcccc -144.55 435.93 0.0 +214 JPT2 ELLIPSE 20.0 #ffcccc 292.0 -366.88 0.0 +215 STMN1 ELLIPSE 20.0 #ffcccc 52.83 -136.77 0.0 +216 MAP2K3 ELLIPSE 20.0 #ffcccc 110.18 610.62 0.0 +217 SIPA1L2 ELLIPSE 20.0 #ffcccc 507.75 1035.82 0.0 +218 BDNF ELLIPSE 20.0 #ffcccc -89.66 897.5 0.0 +219 SLX1A ELLIPSE 20.0 #ffcccc -739.57 915.35 0.0 +220 ERCC4 ELLIPSE 20.0 #ffcccc -550.31 553.85 0.0 +221 TUBG2 ELLIPSE 20.0 #ffcccc 1.45 -499.79 0.0 +222 TOPORS ELLIPSE 20.0 #ffcccc 126.35 -531.26 0.0 +223 BLOC1S2 ELLIPSE 20.0 #ffcccc 18.76 -618.87 0.0 +224 KIFC1 ELLIPSE 20.0 #ffcccc 192.42 -325.97 0.0 +225 NME7 ELLIPSE 20.0 #ffcccc -246.25 -467.49 0.0 +226 CIAO3 ELLIPSE 20.0 #ffcccc 1823.11 -100.05 0.0 +227 CIAO2A ELLIPSE 20.0 #ffcccc 1765.2 -180.64 0.0 +228 MLLT6 ELLIPSE 20.0 #ffcccc 479.78 344.95 0.0 +229 ZC3H4 ELLIPSE 20.0 #ffcccc -391.98 -621.77 0.0 +230 CLP1 ELLIPSE 20.0 #ffcccc -407.44 -223.42 0.0 +231 DFFA ELLIPSE 20.0 #ffcccc -275.99 -345.67 0.0 +232 MYSM1 ELLIPSE 20.0 #ffcccc -320.65 481.01 0.0 +233 MPND ELLIPSE 20.0 #ffcccc -341.39 377.47 0.0 +234 CCT8 ELLIPSE 20.0 #ffcccc -296.71 48.13 0.0 +235 EIF6 ELLIPSE 20.0 #ffcccc -458.53 35.41 0.0 +236 EIF4A1 ELLIPSE 20.0 #ffcccc -375.12 18.21 0.0 +237 FUS ELLIPSE 20.0 #ffcccc -551.96 74.89 0.0 +238 LARP1 ELLIPSE 20.0 #ffcccc -400.03 -41.46 0.0 +239 ARID1A ELLIPSE 20.0 #ffcccc -347.87 445.27 0.0 +240 DHX30 ELLIPSE 20.0 #ffcccc -745.29 -205.83 0.0 +241 HNRNPA1L2 ELLIPSE 20.0 #ffcccc -623.66 -198.44 0.0 +242 RXRA ELLIPSE 20.0 #ffcccc -507.58 566.14 0.0 +243 SAFB ELLIPSE 20.0 #ffcccc -427.19 -71.5 0.0 +244 SMARCA4 ELLIPSE 20.0 #ffcccc -400.24 362.53 0.0 +245 IARS2 ELLIPSE 20.0 #ffcccc -1141.02 -166.69 0.0 +246 H3-3A ELLIPSE 20.0 #ffcccc -735.16 544.72 0.0 +247 FBXL19 ELLIPSE 20.0 #ffcccc -634.27 600.78 0.0 +248 SUV39H1 ELLIPSE 20.0 #ffcccc -676.86 560.85 0.0 +249 TONSL ELLIPSE 20.0 #ffcccc -957.03 602.71 0.0 +250 SGF29 ELLIPSE 20.0 #ffcccc -757.03 314.2 0.0 +251 ING1 ELLIPSE 20.0 #ffcccc -1013.98 836.37 0.0 +252 UBN1 ELLIPSE 20.0 #ffcccc -1032.93 777.54 0.0 +253 SETDB1 ELLIPSE 20.0 #ffcccc -836.41 678.34 0.0 +254 H2BC8 ELLIPSE 20.0 #ffcccc -505.25 453.05 0.0 +255 CARM1 ELLIPSE 20.0 #ffcccc -492.36 683.14 0.0 +256 H2AC8 ELLIPSE 20.0 #ffcccc -757.85 407.74 0.0 +257 BRD8 ELLIPSE 20.0 #ffcccc -673.88 510.15 0.0 +258 TP63 ELLIPSE 20.0 #ffcccc -458.37 629.39 0.0 +259 DERPC ELLIPSE 20.0 #ffcccc 376.13 -114.16 0.0 +260 WRAP53 ELLIPSE 20.0 #ffcccc -10.93 -55.45 0.0 +261 PPP6R3 ELLIPSE 20.0 #ffcccc 243.03 -113.82 0.0 +262 BTG1 ELLIPSE 20.0 #ffcccc -65.56 1185.9 0.0 +263 CCNJ ELLIPSE 20.0 #ffcccc 104.07 -20.34 0.0 +264 DNMT1 ELLIPSE 20.0 #ffcccc -511.48 406.84 0.0 +265 PRKDC ELLIPSE 20.0 #ffcccc -317.8 281.59 0.0 +266 CNPPD1 ELLIPSE 20.0 #ffcccc 142.95 67.76 0.0 +267 STIL ELLIPSE 20.0 #ffcccc 103.96 -95.77 0.0 +268 CDK17 ELLIPSE 20.0 #ffcccc 155.37 1.04 0.0 +269 UBE2E1 ELLIPSE 20.0 #ffcccc -125.97 268.57 0.0 +270 RCC1 ELLIPSE 20.0 #ffcccc -725.29 277.94 0.0 +271 CENPU ELLIPSE 20.0 #ffcccc 11.99 -9.35 0.0 +272 SKA3 ELLIPSE 20.0 #ffcccc 166.26 -112.29 0.0 +273 CEP55 ELLIPSE 20.0 #ffcccc 27.84 -209.66 0.0 +274 LIN9 ELLIPSE 20.0 #ffcccc 92.58 30.63 0.0 +275 CCNE1 ELLIPSE 20.0 #ffcccc -88.23 162.77 0.0 +276 TOP2A ELLIPSE 20.0 #ffcccc -20.22 79.7 0.0 +277 ARHGAP9 ELLIPSE 20.0 #ffcccc 986.04 514.46 0.0 +278 CD247 ELLIPSE 20.0 #ffcccc 517.11 550.45 0.0 +279 OASL ELLIPSE 20.0 #ffcccc -395.62 268.8 0.0 +280 IFITM1 ELLIPSE 20.0 #ffcccc -141.52 552.5 0.0 +281 LMO2 ELLIPSE 20.0 #ffcccc -327.4 -206.84 0.0 +282 MAPRE2 ELLIPSE 20.0 #ffcccc -97.57 -182.51 0.0 +283 HTRA2 ELLIPSE 20.0 #ffcccc 464.37 641.46 0.0 +284 TRAF3 ELLIPSE 20.0 #ffcccc 176.98 517.41 0.0 +285 COG3 ELLIPSE 20.0 #ffcccc 713.09 65.31 0.0 +286 COPZ1 ELLIPSE 20.0 #ffcccc 1046.86 25.22 0.0 +287 TBRG4 ELLIPSE 20.0 #ffcccc -996.07 -488.98 0.0 +288 MARCHF7 ELLIPSE 20.0 #ffcccc -685.86 -788.31 0.0 +289 PCNP ELLIPSE 20.0 #ffcccc -608.31 -461.39 0.0 +290 BLK ELLIPSE 20.0 #ffcccc -235.97 1046.38 0.0 +291 EFNA5 ELLIPSE 20.0 #ffcccc -152.69 952.11 0.0 +292 RASA1 ELLIPSE 20.0 #ffcccc -262.76 872.48 0.0 +293 DERL1 ELLIPSE 20.0 #ffcccc -112.47 330.97 0.0 +294 UBXN1 ELLIPSE 20.0 #ffcccc -91.52 216.89 0.0 +295 RNF139 ELLIPSE 20.0 #ffcccc -114.52 471.47 0.0 +296 NGLY1 ELLIPSE 20.0 #ffcccc 21.66 360.87 0.0 +297 HINT2 ELLIPSE 20.0 #ffcccc -961.49 0.01 0.0 +298 RIPK1 ELLIPSE 20.0 #ffcccc -24.0 467.83 0.0 +299 MAP4K2 ELLIPSE 20.0 #ffcccc 267.76 654.0 0.0 +300 UBE2V1 ELLIPSE 20.0 #ffcccc -45.92 395.21 0.0 +301 IKBKG ELLIPSE 20.0 #ffcccc -46.96 532.37 0.0 +302 CHRNA1 ELLIPSE 20.0 #ffcccc 221.97 -992.49 0.0 +303 CHRM1 ELLIPSE 20.0 #ffcccc 278.94 -837.28 0.0 +304 CACNG8 ELLIPSE 20.0 #ffcccc 618.52 91.9 0.0 +305 WNT8A ELLIPSE 20.0 #ffcccc -3.36 866.61 0.0 +306 DVL1 ELLIPSE 20.0 #ffcccc -131.39 750.81 0.0 +307 PPP4R4 ELLIPSE 20.0 #ffcccc 347.78 935.66 0.0 +308 USP22 ELLIPSE 20.0 #ffcccc -565.76 386.87 0.0 +309 SAP130 ELLIPSE 20.0 #ffcccc -684.38 433.4 0.0 +310 KCNAB1 ELLIPSE 20.0 #ffcccc -813.1 291.93 0.0 +311 KCNQ4 ELLIPSE 20.0 #ffcccc -553.32 212.79 0.0 +312 SCPEP1 ELLIPSE 20.0 #ffcccc -1390.49 591.36 0.0 +313 GAPVD1 ELLIPSE 20.0 #ffcccc 32.38 967.04 0.0 +314 FBXO6 ELLIPSE 20.0 #ffcccc -93.85 -92.97 0.0 +315 GBA1 ELLIPSE 20.0 #ffcccc -76.33 -44.98 0.0 +316 FKBP9 ELLIPSE 20.0 #ffcccc -148.39 -57.82 0.0 +317 PCBP4 ELLIPSE 20.0 #ffcccc 109.04 726.43 0.0 +318 DNAJC5G ELLIPSE 20.0 #ffcccc -1010.42 -677.28 0.0 +319 ITGAE ELLIPSE 20.0 #ffcccc 321.91 819.09 0.0 +320 ITGA9 ELLIPSE 20.0 #ffcccc 426.91 791.68 0.0 +321 MED15 ELLIPSE 20.0 #ffcccc -795.46 573.36 0.0 +322 ANGPTL4 ELLIPSE 20.0 #ffcccc -667.9 760.63 0.0 +323 UNK ELLIPSE 20.0 #ffcccc -213.97 438.57 0.0 +324 ANP32B ELLIPSE 20.0 #ffcccc 65.16 144.32 0.0 +325 MYO9B ELLIPSE 20.0 #ffcccc 463.84 489.29 0.0 +326 AP2S1 ELLIPSE 20.0 #ffcccc 212.42 211.34 0.0 +327 BAIAP2L2 ELLIPSE 20.0 #ffcccc 436.56 98.02 0.0 +328 SGIP1 ELLIPSE 20.0 #ffcccc 476.04 158.37 0.0 +329 AP1B1 ELLIPSE 20.0 #ffcccc 141.22 195.23 0.0 +330 AP2A1 ELLIPSE 20.0 #ffcccc 265.41 177.42 0.0 +331 WDR76 ELLIPSE 20.0 #ffcccc -182.39 -426.84 0.0 +332 GABARAP ELLIPSE 20.0 #ffcccc -678.67 951.22 0.0 +333 PLCB4 ELLIPSE 20.0 #ffcccc -145.62 1002.2 0.0 +334 KIF1B ELLIPSE 20.0 #ffcccc 366.26 -538.17 0.0 +335 KIF3C ELLIPSE 20.0 #ffcccc 450.41 -561.15 0.0 +336 KIF5A ELLIPSE 20.0 #ffcccc 482.89 -487.05 0.0 +337 KLC2 ELLIPSE 20.0 #ffcccc 402.0 -471.99 0.0 +338 IFT46 ELLIPSE 20.0 #ffcccc 432.98 -648.89 0.0 +339 CPSF7 ELLIPSE 20.0 #ffcccc -641.81 -308.07 0.0 +340 SRSF5 ELLIPSE 20.0 #ffcccc -462.99 -271.19 0.0 +341 GAS8 ELLIPSE 20.0 #ffcccc -862.58 1092.79 0.0 +342 FLNC ELLIPSE 20.0 #ffcccc 635.36 956.01 0.0 +343 SRP9 ELLIPSE 20.0 #ffcccc -497.63 58.11 0.0 +344 ALDH8A1 ELLIPSE 20.0 #ffcccc -624.41 1526.4 0.0 +345 ANG ELLIPSE 20.0 #ffcccc -588.52 1307.57 0.0 +346 ZCRB1 ELLIPSE 20.0 #ffcccc -735.09 5.72 0.0 +347 SNRNP25 ELLIPSE 20.0 #ffcccc -850.48 -39.65 0.0 +348 TMEM19 ELLIPSE 20.0 #ffcccc 1683.35 -376.41 0.0 +349 BSCL2 ELLIPSE 20.0 #ffcccc 1625.83 -294.62 0.0 +350 UBE2Q2 ELLIPSE 20.0 #ffcccc -98.33 405.89 0.0 +351 UBE2G1 ELLIPSE 20.0 #ffcccc -124.51 367.9 0.0 +352 UBE2F ELLIPSE 20.0 #ffcccc 35.74 411.93 0.0 +353 UBE2E2 ELLIPSE 20.0 #ffcccc -72.63 344.11 0.0 +354 UBE2A ELLIPSE 20.0 #ffcccc -189.86 300.05 0.0 +355 SEPTIN12 ELLIPSE 20.0 #ffcccc 1634.7 -459.12 0.0 +356 TMEM250 ELLIPSE 20.0 #ffcccc 1708.11 -533.87 0.0 +357 SEPTIN9 ELLIPSE 20.0 #ffcccc 1607.92 -560.85 0.0 +358 CISD2 ELLIPSE 20.0 #ffcccc -1347.82 59.48 0.0 +359 SLC25A45 ELLIPSE 20.0 #ffcccc -1242.96 -146.51 0.0 +360 PARK7 ELLIPSE 20.0 #ffcccc -455.75 266.77 0.0 +361 APOBEC3G ELLIPSE 20.0 #ffcccc -944.2 209.06 0.0 +362 CHCHD6 ELLIPSE 20.0 #ffcccc -1086.52 -176.09 0.0 +363 SDHD ELLIPSE 20.0 #ffcccc -1245.94 39.37 0.0 +364 TIMMDC1 ELLIPSE 20.0 #ffcccc -1196.41 99.17 0.0 +365 CFAP45 ELLIPSE 20.0 #ffcccc -1099.31 1204.49 0.0 +366 CBX8 ELLIPSE 20.0 #ffcccc -847.75 402.77 0.0 +367 H1-10 ELLIPSE 20.0 #ffcccc -1023.88 495.96 0.0 +368 JARID2 ELLIPSE 20.0 #ffcccc -835.44 545.24 0.0 +369 CASP8AP2 ELLIPSE 20.0 #ffcccc -1123.51 470.87 0.0 +370 CETN2 ELLIPSE 20.0 #ffcccc -616.65 494.07 0.0 +371 PHC1 ELLIPSE 20.0 #ffcccc -914.62 442.65 0.0 +372 CCDC97 ELLIPSE 20.0 #ffcccc -920.98 -428.42 0.0 +373 SCYL1 ELLIPSE 20.0 #ffcccc 1215.19 50.32 0.0 +374 CACNA1G ELLIPSE 20.0 #ffcccc 983.73 -126.32 0.0 +375 GRID2 ELLIPSE 20.0 #ffcccc 708.94 -82.63 0.0 +376 EPB41L1 ELLIPSE 20.0 #ffcccc 732.98 -29.72 0.0 +377 PRCC ELLIPSE 20.0 #ffcccc -675.93 -875.59 0.0 +378 RBM10 ELLIPSE 20.0 #ffcccc -607.75 -564.74 0.0 +379 FANCF ELLIPSE 20.0 #ffcccc -409.86 555.53 0.0 +380 EGLN1 ELLIPSE 20.0 #ffcccc -741.05 477.79 0.0 +381 CHMP7 ELLIPSE 20.0 #ffcccc -428.27 503.25 0.0 +382 CHMP6 ELLIPSE 20.0 #ffcccc -475.72 504.99 0.0 +383 GTF2H2 ELLIPSE 20.0 #ffcccc -566.3 441.83 0.0 +384 COMMD6 ELLIPSE 20.0 #ffcccc -557.27 694.0 0.0 +385 TRIM32 ELLIPSE 20.0 #ffcccc -160.83 391.57 0.0 +386 BUB3 ELLIPSE 20.0 #ffcccc -256.76 -31.66 0.0 +387 GPS1 ELLIPSE 20.0 #ffcccc -454.27 448.88 0.0 +388 ELOC ELLIPSE 20.0 #ffcccc -623.69 455.52 0.0 +389 RPP40 ELLIPSE 20.0 #ffcccc -287.62 84.19 0.0 +390 SPRED3 ELLIPSE 20.0 #ffcccc -278.07 649.87 0.0 +391 KLHL12 ELLIPSE 20.0 #ffcccc -358.7 787.16 0.0 +392 LGR6 ELLIPSE 20.0 #ffcccc -165.59 505.39 0.0 +393 XRCC3 ELLIPSE 20.0 #ffcccc -11.23 328.31 0.0 +394 JOSD2 ELLIPSE 20.0 #ffcccc -217.58 500.87 0.0 +395 ANXA6 ELLIPSE 20.0 #ffcccc -299.94 1199.91 0.0 +396 GPR174 ELLIPSE 20.0 #ffcccc 662.33 731.19 0.0 +397 INPPL1 ELLIPSE 20.0 #ffcccc 410.76 863.49 0.0 +398 P2RX7 ELLIPSE 20.0 #ffcccc 826.89 891.08 0.0 +399 CD40LG ELLIPSE 20.0 #ffcccc 540.77 649.33 0.0 +400 GRAP2 ELLIPSE 20.0 #ffcccc 571.77 491.77 0.0 +401 GNRH1 ELLIPSE 20.0 #ffcccc 380.45 -1094.33 0.0 +402 CCK ELLIPSE 20.0 #ffcccc 396.41 -942.94 0.0 +403 EDN3 ELLIPSE 20.0 #ffcccc 314.25 -1004.38 0.0 +404 LIN7C ELLIPSE 20.0 #ffcccc 758.0 -984.35 0.0 +405 SYN1 ELLIPSE 20.0 #ffcccc 651.68 -911.09 0.0 +406 HSD17B12 ELLIPSE 20.0 #ffcccc -990.53 -239.08 0.0 +407 DNAJC1 ELLIPSE 20.0 #ffcccc -232.15 96.99 0.0 +408 GSPT2 ELLIPSE 20.0 #ffcccc -317.04 -83.0 0.0 +409 TM7SF2 ELLIPSE 20.0 #ffcccc 1357.53 -2853.57 0.0 +410 DHCR24 ELLIPSE 20.0 #ffcccc 1386.83 -2751.1 0.0 +411 ITM2B ELLIPSE 20.0 #ffcccc 383.53 402.63 0.0 +412 DONSON ELLIPSE 20.0 #ffcccc 153.89 -165.18 0.0 +413 NBAS ELLIPSE 20.0 #ffcccc 1209.84 -29.9 0.0 +414 SETBP1 ELLIPSE 20.0 #ffcccc -848.41 944.83 0.0 +415 ADAMTS18 ELLIPSE 20.0 #ffcccc 1471.0 249.48 0.0 +416 ADAMTS3 ELLIPSE 20.0 #ffcccc 1573.78 235.98 0.0 +417 ADAMTSL2 ELLIPSE 20.0 #ffcccc 1534.97 331.72 0.0 +418 SCN3A ELLIPSE 20.0 #ffcccc 1134.92 -162.24 0.0 +419 SCN3B ELLIPSE 20.0 #ffcccc 1163.38 -233.54 0.0 +420 SCN1B ELLIPSE 20.0 #ffcccc 1084.62 -249.37 0.0 +421 PLA2G4E ELLIPSE 20.0 #ffcccc 969.96 746.43 0.0 +422 ABCA6 ELLIPSE 20.0 #ffcccc -178.8 1188.82 0.0 +423 ODF1 ELLIPSE 20.0 #ffcccc -113.55 -398.3 0.0 +424 BRIX1 ELLIPSE 20.0 #ffcccc -370.56 -1.0 0.0 +425 TSC22D1 ELLIPSE 20.0 #ffcccc 527.88 1685.35 0.0 +426 SLC6A1 ELLIPSE 20.0 #ffcccc 559.13 -879.37 0.0 +427 CPNE6 ELLIPSE 20.0 #ffcccc 446.34 -850.97 0.0 +428 SNCB ELLIPSE 20.0 #ffcccc 489.26 -777.33 0.0 +429 LY6H ELLIPSE 20.0 #ffcccc 514.8 -950.19 0.0 +430 SYNPR ELLIPSE 20.0 #ffcccc 463.28 -906.72 0.0 +431 GPC2 ELLIPSE 20.0 #ffcccc 1439.41 -455.41 0.0 +432 HS3ST4 ELLIPSE 20.0 #ffcccc 1538.41 -425.22 0.0 +433 TAMALIN ELLIPSE 20.0 #ffcccc -54.73 -3002.12 0.0 +434 MARCHF2 ELLIPSE 20.0 #ffcccc -111.81 -2915.62 0.0 +435 NCL ELLIPSE 20.0 #ffcccc -358.91 -36.72 0.0 +436 UBXN6 ELLIPSE 20.0 #ffcccc 13.3 -283.55 0.0 +437 TRAPPC9 ELLIPSE 20.0 #ffcccc 584.72 -6.18 0.0 +438 DNAI3 ELLIPSE 20.0 #ffcccc -1386.84 1602.48 0.0 +439 CCDC114 ELLIPSE 20.0 #ffcccc -1306.88 1286.89 0.0 +440 FABP1 ELLIPSE 20.0 #ffcccc -500.64 899.08 0.0 +441 RGL1 ELLIPSE 20.0 #ffcccc -578.92 853.18 0.0 +442 CHD9 ELLIPSE 20.0 #ffcccc -508.81 745.51 0.0 +443 ADH5 ELLIPSE 20.0 #ffcccc -1966.95 314.33 0.0 +444 NOL10 ELLIPSE 20.0 #ffcccc -302.19 6.75 0.0 +445 NKD2 ELLIPSE 20.0 #ffcccc -75.29 1089.86 0.0 +446 RP9 ELLIPSE 20.0 #ffcccc -781.89 -698.68 0.0 +447 RPP25L ELLIPSE 20.0 #ffcccc -204.84 -97.44 0.0 +448 PRDX3 ELLIPSE 20.0 #ffcccc -1119.41 -52.8 0.0 +449 CKB ELLIPSE 20.0 #ffcccc -766.85 207.79 0.0 +450 ALDOA ELLIPSE 20.0 #ffcccc -689.6 201.15 0.0 +451 RNF214 ELLIPSE 20.0 #ffcccc 4920.51 367.34 0.0 +452 SMG8 ELLIPSE 20.0 #ffcccc 4829.13 415.96 0.0 +453 NABP1 ELLIPSE 20.0 #ffcccc -1047.62 303.07 0.0 +454 TMEM256 ELLIPSE 20.0 #ffcccc -1356.88 -103.81 0.0 +455 RAB29 ELLIPSE 20.0 #ffcccc -1464.03 -125.37 0.0 +456 TMEM14C ELLIPSE 20.0 #ffcccc -1355.44 -190.38 0.0 +457 TPST1 ELLIPSE 20.0 #ffcccc 690.52 -2926.02 0.0 +458 EIF2B1 ELLIPSE 20.0 #ffcccc 638.2 -3015.99 0.0 +459 OR52A5 ELLIPSE 20.0 #ffcccc -78.11 -850.71 0.0 +460 GNAL ELLIPSE 20.0 #ffcccc 4.07 -733.22 0.0 +461 OAZ1 ELLIPSE 20.0 #ffcccc -237.51 682.85 0.0 +462 SRP72 ELLIPSE 20.0 #ffcccc -628.06 114.07 0.0 +463 PBDC1 ELLIPSE 20.0 #ffcccc -791.57 -100.67 0.0 +464 LCMT2 ELLIPSE 20.0 #ffcccc 522.83 1137.87 0.0 +465 LPAR4 ELLIPSE 20.0 #ffcccc 163.54 -830.83 0.0 +466 GMPPA ELLIPSE 20.0 #ffcccc -805.0 1347.64 0.0 +467 FNIP1 ELLIPSE 20.0 #ffcccc -1108.72 794.41 0.0 +468 TBC1D25 ELLIPSE 20.0 #ffcccc -848.8 1197.4 0.0 +469 ATG5 ELLIPSE 20.0 #ffcccc -767.97 1222.51 0.0 +470 VSNL1 ELLIPSE 20.0 #ffcccc 587.36 -731.89 0.0 +471 CEND1 ELLIPSE 20.0 #ffcccc 603.51 -807.59 0.0 +472 TYW1B ELLIPSE 20.0 #ffcccc -26.75 -346.42 0.0 +473 FTSJ1 ELLIPSE 20.0 #ffcccc -270.75 -173.16 0.0 +474 PUS7L ELLIPSE 20.0 #ffcccc -229.25 -159.5 0.0 +475 DPH5 ELLIPSE 20.0 #ffcccc -156.79 7.54 0.0 +476 ELP2 ELLIPSE 20.0 #ffcccc -126.85 -233.48 0.0 +477 DDX24 ELLIPSE 20.0 #ffcccc -254.28 -74.11 0.0 +478 B4GAT1 ELLIPSE 20.0 #ffcccc 1513.79 -252.17 0.0 +479 PRELP ELLIPSE 20.0 #ffcccc 1590.31 -175.91 0.0 +480 LARGE2 ELLIPSE 20.0 #ffcccc 1438.77 -326.64 0.0 +481 RHNO1 ELLIPSE 20.0 #ffcccc -786.47 870.73 0.0 +482 RPH3A ELLIPSE 20.0 #ffcccc 255.57 1075.48 0.0 +483 KCTD2 ELLIPSE 20.0 #ffcccc -482.67 1119.02 0.0 +484 KLHL2 ELLIPSE 20.0 #ffcccc -518.68 999.36 0.0 +485 ATAD5 ELLIPSE 20.0 #ffcccc 228.92 271.1 0.0 +486 DLGAP1 ELLIPSE 20.0 #ffcccc 175.04 1464.42 0.0 +487 RAB4B ELLIPSE 20.0 #ffcccc 91.28 1088.8 0.0 +488 CFAP299 ELLIPSE 20.0 #ffcccc -1140.87 1366.33 0.0 +489 ECT2L ELLIPSE 20.0 #ffcccc 427.32 -292.97 0.0 +490 B3GNT4 ELLIPSE 20.0 #ffcccc 1665.18 -101.31 0.0 +491 KDM3A ELLIPSE 20.0 #ffcccc -278.4 588.33 0.0 +492 GTF3A ELLIPSE 20.0 #ffcccc -386.22 626.23 0.0 +493 PELI3 ELLIPSE 20.0 #ffcccc 162.29 584.42 0.0 +494 OR10K2 ELLIPSE 20.0 #ffcccc 83.59 -864.42 0.0 +495 PHF21B ELLIPSE 20.0 #ffcccc -552.84 779.12 0.0 +496 RTN4IP1 ELLIPSE 20.0 #ffcccc 458.29 258.23 0.0 +497 SRPK3 ELLIPSE 20.0 #ffcccc -502.31 -479.67 0.0 +498 PRKCH ELLIPSE 20.0 #ffcccc -291.94 1519.81 0.0 +499 ADRA2B ELLIPSE 20.0 #ffcccc -283.04 1272.3 0.0 +500 ATP11C ELLIPSE 20.0 #ffcccc 1588.46 38.64 0.0 +501 TENM1 ELLIPSE 20.0 #ffcccc 1536.75 -49.59 0.0 +502 OR3A2 ELLIPSE 20.0 #ffcccc -125.85 -802.98 0.0 +503 OR11G2 ELLIPSE 20.0 #ffcccc -29.94 -879.54 0.0 +504 OR2T7 ELLIPSE 20.0 #ffcccc 29.62 -884.97 0.0 +505 TRAPPC11 ELLIPSE 20.0 #ffcccc 800.87 -132.57 0.0 +506 LIPA ELLIPSE 20.0 #ffcccc 1424.5 -2652.47 0.0 +507 EBAG9 ELLIPSE 20.0 #ffcccc -35.49 705.69 0.0 +508 ADA ELLIPSE 20.0 #ffcccc -174.99 -139.57 0.0 +509 ZNF385A ELLIPSE 20.0 #ffcccc 305.48 995.22 0.0 +510 IFNAR2 ELLIPSE 20.0 #ffcccc 265.92 345.39 0.0 +511 TREM2 ELLIPSE 20.0 #ffcccc 826.95 472.66 0.0 +512 ARL4C ELLIPSE 20.0 #ffcccc -464.87 782.74 0.0 +513 TNRC6B ELLIPSE 20.0 #ffcccc -388.19 724.82 0.0 +514 AGO4 ELLIPSE 20.0 #ffcccc -367.03 490.07 0.0 +515 CDH18 ELLIPSE 20.0 #ffcccc 139.37 890.55 0.0 +516 ADGRA2 ELLIPSE 20.0 #ffcccc 94.22 946.2 0.0 +517 CRYAB ELLIPSE 20.0 #ffcccc 108.66 529.92 0.0 +518 MAP3K15 ELLIPSE 20.0 #ffcccc 966.02 622.33 0.0 +519 TNFSF13B ELLIPSE 20.0 #ffcccc 648.98 598.03 0.0 +520 STIM2 ELLIPSE 20.0 #ffcccc 1160.07 642.18 0.0 +521 LRRC41 ELLIPSE 20.0 #ffcccc -743.52 765.77 0.0 +522 BTBD6 ELLIPSE 20.0 #ffcccc -782.21 1106.95 0.0 +523 ARID5A ELLIPSE 20.0 #ffcccc -630.0 710.83 0.0 +524 DPM3 ELLIPSE 20.0 #ffcccc -868.85 1583.89 0.0 +525 ETS2 ELLIPSE 20.0 #ffcccc -405.25 863.21 0.0 +526 COA3 ELLIPSE 20.0 #ffcccc -1382.2 170.47 0.0 +527 COX14 ELLIPSE 20.0 #ffcccc -1233.32 160.61 0.0 +528 COX7B2 ELLIPSE 20.0 #ffcccc -1061.27 57.5 0.0 +529 NTPCR ELLIPSE 20.0 #ffcccc -370.59 -466.8 0.0 +530 DYRK1B ELLIPSE 20.0 #ffcccc 667.49 1195.57 0.0 +531 EGLN2 ELLIPSE 20.0 #ffcccc -1059.51 694.7 0.0 +532 VARS2 ELLIPSE 20.0 #ffcccc -1021.66 -181.25 0.0 +533 SMIM20 ELLIPSE 20.0 #ffcccc -876.02 -488.09 0.0 +534 NAXE ELLIPSE 20.0 #ffcccc 1467.31 -504.84 0.0 +535 GBE1 ELLIPSE 20.0 #ffcccc 1530.93 -585.56 0.0 +536 DOLPP1 ELLIPSE 20.0 #ffcccc -905.83 1732.78 0.0 +537 PI4KB ELLIPSE 20.0 #ffcccc -117.47 1323.8 0.0 +538 BCKDK ELLIPSE 20.0 #ffcccc -903.28 783.05 0.0 +539 TMED5 ELLIPSE 20.0 #ffcccc 59.45 1155.17 0.0 +540 WNT5B ELLIPSE 20.0 #ffcccc -3.1 1039.35 0.0 +541 ADGRL4 ELLIPSE 20.0 #ffcccc 1656.84 321.66 0.0 +542 CD63 ELLIPSE 20.0 #ffcccc 1737.63 264.0 0.0 +543 PLEKHG6 ELLIPSE 20.0 #ffcccc 183.56 -436.93 0.0 +544 FOXO6 ELLIPSE 20.0 #ffcccc -122.45 1209.79 0.0 +545 FOXP4 ELLIPSE 20.0 #ffcccc -1526.93 -2312.8 0.0 +546 FOXP2 ELLIPSE 20.0 #ffcccc -1449.27 -2375.33 0.0 +547 BAK1 ELLIPSE 20.0 #ffcccc -1037.07 -429.15 0.0 +548 LYPLA2 ELLIPSE 20.0 #ffcccc -1494.12 2.79 0.0 +549 KAZN ELLIPSE 20.0 #ffcccc 406.24 1163.51 0.0 +550 ERC1 ELLIPSE 20.0 #ffcccc 255.74 933.92 0.0 +551 SRM ELLIPSE 20.0 #ffcccc -621.43 -3.22 0.0 +552 TCOF1 ELLIPSE 20.0 #ffcccc 173.74 -245.45 0.0 +553 RAD54L2 ELLIPSE 20.0 #ffcccc -890.72 890.85 0.0 +554 C7orf50 ELLIPSE 20.0 #ffcccc -191.38 -275.47 0.0 +555 ZRSR2P1 ELLIPSE 20.0 #ffcccc -490.23 -725.97 0.0 +556 BTBD3 ELLIPSE 20.0 #ffcccc -927.86 1313.17 0.0 +557 CLDN3 ELLIPSE 20.0 #ffcccc 1436.95 -807.27 0.0 +558 CLDN2 ELLIPSE 20.0 #ffcccc 1519.17 -742.7 0.0 +559 CTSV ELLIPSE 20.0 #ffcccc 576.86 418.2 0.0 +560 SOCS4 ELLIPSE 20.0 #ffcccc -940.81 699.4 0.0 +561 GPX8 ELLIPSE 20.0 #ffcccc -1971.46 217.8 0.0 +562 NFIC ELLIPSE 20.0 #ffcccc -332.24 1113.28 0.0 +563 MAMLD1 ELLIPSE 20.0 #ffcccc -387.27 992.89 0.0 +564 ZNF638 ELLIPSE 20.0 #ffcccc -751.71 -2670.28 0.0 +565 SENP6 ELLIPSE 20.0 #ffcccc -824.3 -2602.69 0.0 +566 RWDD4 ELLIPSE 20.0 #ffcccc -895.47 -193.19 0.0 +567 ATP2B1 ELLIPSE 20.0 #ffcccc 37.45 707.27 0.0 +568 ZNF746 ELLIPSE 20.0 #ffcccc -189.29 -356.66 0.0 +569 HSPB6 ELLIPSE 20.0 #ffcccc 381.07 707.71 0.0 +570 CALU ELLIPSE 20.0 #ffcccc 1405.8 -594.06 0.0 +571 SARS2 ELLIPSE 20.0 #ffcccc 1470.02 -669.57 0.0 +572 CIC ELLIPSE 20.0 #ffcccc -965.79 907.27 0.0 diff --git a/results/networks/nodes2 b/results/networks/nodes2 deleted file mode 100644 index 2657779..0000000 --- a/results/networks/nodes2 +++ /dev/null @@ -1,661 +0,0 @@ -node_id alias shape size color x y weight -0 ARF5 ELLIPSE 20.0 #ffcccc 841.61 287.3 0.0 -1 UNK ELLIPSE 20.0 #ffcccc 696.11 -13.41 0.0 -2 AP1B1 ELLIPSE 20.0 #ffcccc 883.35 495.1 0.0 -3 SYNGAP1 ELLIPSE 20.0 #ffcccc 1111.97 410.88 0.0 -4 ANK2 ELLIPSE 20.0 #ffcccc 746.61 447.89 0.0 -5 BET1 ELLIPSE 20.0 #ffcccc 906.74 364.24 0.0 -6 COPZ1 ELLIPSE 20.0 #ffcccc 718.75 337.52 0.0 -7 ARCN1 ELLIPSE 20.0 #ffcccc 597.73 320.92 0.0 -8 COPB2 ELLIPSE 20.0 #ffcccc 793.91 356.14 0.0 -9 ARFGAP3 ELLIPSE 20.0 #ffcccc 867.64 401.51 0.0 -10 ARFGAP1 ELLIPSE 20.0 #ffcccc 844.23 494.3 0.0 -11 INMT ELLIPSE 20.0 #ffcccc 2085.4 -322.65 0.0 -12 IDO2 ELLIPSE 20.0 #ffcccc 2152.15 -289.13 0.0 -13 ERCC1 ELLIPSE 20.0 #ffcccc 138.61 860.95 0.0 -14 POLR2K ELLIPSE 20.0 #ffcccc -61.26 748.31 0.0 -15 UBB ELLIPSE 20.0 #ffcccc 588.13 578.51 0.0 -16 POLR2F ELLIPSE 20.0 #ffcccc -87.56 675.71 0.0 -17 CHD1L ELLIPSE 20.0 #ffcccc 171.64 381.95 0.0 -18 HMGN1 ELLIPSE 20.0 #ffcccc 28.26 878.23 0.0 -19 GTF2H3 ELLIPSE 20.0 #ffcccc 46.62 685.12 0.0 -20 FANCF ELLIPSE 20.0 #ffcccc 189.93 1014.11 0.0 -21 PMS1 ELLIPSE 20.0 #ffcccc 62.3 769.35 0.0 -22 FANCC ELLIPSE 20.0 #ffcccc 257.72 1031.73 0.0 -23 DDB2 ELLIPSE 20.0 #ffcccc 161.05 694.89 0.0 -24 RHNO1 ELLIPSE 20.0 #ffcccc 311.68 993.67 0.0 -25 RAD1 ELLIPSE 20.0 #ffcccc 255.14 930.89 0.0 -26 SLX1A ELLIPSE 20.0 #ffcccc -29.21 1092.19 0.0 -27 CETN2 ELLIPSE 20.0 #ffcccc 156.78 623.39 0.0 -28 USP45 ELLIPSE 20.0 #ffcccc 212.98 1058.68 0.0 -29 TARBP1 ELLIPSE 20.0 #ffcccc -443.39 -8.51 0.0 -30 NOL6 ELLIPSE 20.0 #ffcccc -209.48 117.9 0.0 -31 RTN4R ELLIPSE 20.0 #ffcccc 1589.89 1819.99 0.0 -32 RTN4 ELLIPSE 20.0 #ffcccc 1668.11 1821.99 0.0 -33 RCN1 ELLIPSE 20.0 #ffcccc 1462.1 758.32 0.0 -34 MYL6 ELLIPSE 20.0 #ffcccc 1263.46 692.14 0.0 -35 PKP2 ELLIPSE 20.0 #ffcccc 2823.51 -460.09 0.0 -36 KRT18 ELLIPSE 20.0 #ffcccc 2789.84 -390.77 0.0 -37 NDUFB4 ELLIPSE 20.0 #ffcccc -198.57 -363.51 0.0 -38 COX6C ELLIPSE 20.0 #ffcccc -220.11 -211.94 0.0 -39 ATP5F1E ELLIPSE 20.0 #ffcccc -19.83 -283.42 0.0 -40 COX7C ELLIPSE 20.0 #ffcccc -54.13 -151.49 0.0 -41 ATP5MF ELLIPSE 20.0 #ffcccc -36.9 -368.58 0.0 -42 TIMMDC1 ELLIPSE 20.0 #ffcccc -246.79 -464.18 0.0 -43 UQCR11 ELLIPSE 20.0 #ffcccc -172.92 -281.26 0.0 -44 UQCRQ ELLIPSE 20.0 #ffcccc -122.89 -167.91 0.0 -45 NDUFB10 ELLIPSE 20.0 #ffcccc -81.04 -246.71 0.0 -46 SLC22A4 ELLIPSE 20.0 #ffcccc 439.38 1626.13 0.0 -47 PDZK1 ELLIPSE 20.0 #ffcccc 449.48 1481.8 0.0 -48 VCL ELLIPSE 20.0 #ffcccc 990.04 661.6 0.0 -49 ARRB2 ELLIPSE 20.0 #ffcccc 940.15 830.98 0.0 -50 SCAF4 ELLIPSE 20.0 #ffcccc 696.46 1132.1 0.0 -51 DAG1 ELLIPSE 20.0 #ffcccc 1222.33 657.83 0.0 -52 PICALM ELLIPSE 20.0 #ffcccc 757.58 531.81 0.0 -53 MYL12A ELLIPSE 20.0 #ffcccc 1163.8 666.73 0.0 -54 MANF ELLIPSE 20.0 #ffcccc 713.2 407.35 0.0 -55 ACTG1 ELLIPSE 20.0 #ffcccc 1061.39 550.63 0.0 -56 CTNND1 ELLIPSE 20.0 #ffcccc 1256.47 626.39 0.0 -57 ZYX ELLIPSE 20.0 #ffcccc 1060.68 412.73 0.0 -58 MIF ELLIPSE 20.0 #ffcccc 184.74 -80.38 0.0 -59 RPS28 ELLIPSE 20.0 #ffcccc 347.42 140.89 0.0 -60 NME2 ELLIPSE 20.0 #ffcccc 321.59 8.65 0.0 -61 PARK7 ELLIPSE 20.0 #ffcccc 212.3 149.2 0.0 -62 HSCB ELLIPSE 20.0 #ffcccc -60.44 -75.36 0.0 -63 SDHB ELLIPSE 20.0 #ffcccc 28.9 -193.7 0.0 -64 ISCA1 ELLIPSE 20.0 #ffcccc -164.65 -110.94 0.0 -65 HSPA9 ELLIPSE 20.0 #ffcccc 167.38 166.28 0.0 -66 ST13 ELLIPSE 20.0 #ffcccc 597.2 370.91 0.0 -67 PDIA4 ELLIPSE 20.0 #ffcccc 801.92 518.82 0.0 -68 TFG ELLIPSE 20.0 #ffcccc 893.75 312.98 0.0 -69 HSPA8 ELLIPSE 20.0 #ffcccc 275.73 461.19 0.0 -70 PNN ELLIPSE 20.0 #ffcccc -366.98 613.33 0.0 -71 RSRC2 ELLIPSE 20.0 #ffcccc -605.25 700.17 0.0 -72 SMG6 ELLIPSE 20.0 #ffcccc -69.88 538.55 0.0 -73 HNRNPA2B1 ELLIPSE 20.0 #ffcccc 1.97 421.11 0.0 -74 U2AF2 ELLIPSE 20.0 #ffcccc -363.02 509.85 0.0 -75 HNRNPH3 ELLIPSE 20.0 #ffcccc -334.97 435.87 0.0 -76 ARGLU1 ELLIPSE 20.0 #ffcccc -461.16 556.22 0.0 -77 CASC3 ELLIPSE 20.0 #ffcccc -248.57 667.24 0.0 -78 PNISR ELLIPSE 20.0 #ffcccc -572.7 572.77 0.0 -79 RNPS1 ELLIPSE 20.0 #ffcccc -141.45 663.9 0.0 -80 ACOT8 ELLIPSE 20.0 #ffcccc -475.26 1031.22 0.0 -81 PEX7 ELLIPSE 20.0 #ffcccc -0.36 682.64 0.0 -82 PAOX ELLIPSE 20.0 #ffcccc -581.65 1168.91 0.0 -83 SCP2 ELLIPSE 20.0 #ffcccc -672.82 1158.48 0.0 -84 SLC27A2 ELLIPSE 20.0 #ffcccc -631.26 1084.53 0.0 -85 GNPAT ELLIPSE 20.0 #ffcccc -575.39 1110.65 0.0 -86 RAC1 ELLIPSE 20.0 #ffcccc 1283.67 472.38 0.0 -87 PAK3 ELLIPSE 20.0 #ffcccc 1218.51 791.08 0.0 -88 PSMD10 ELLIPSE 20.0 #ffcccc 356.61 189.06 0.0 -89 UBE3A ELLIPSE 20.0 #ffcccc 530.92 197.56 0.0 -90 SRP9 ELLIPSE 20.0 #ffcccc 65.29 278.32 0.0 -91 PSMF1 ELLIPSE 20.0 #ffcccc 509.36 134.56 0.0 -92 PSME3 ELLIPSE 20.0 #ffcccc 259.31 309.38 0.0 -93 PSMB10 ELLIPSE 20.0 #ffcccc 477.28 190.96 0.0 -94 OAZ1 ELLIPSE 20.0 #ffcccc 431.04 63.75 0.0 -95 OAZ3 ELLIPSE 20.0 #ffcccc 369.99 73.0 0.0 -96 GLI1 ELLIPSE 20.0 #ffcccc 532.16 374.26 0.0 -97 PSMB5 ELLIPSE 20.0 #ffcccc 417.29 193.41 0.0 -98 SEM1 ELLIPSE 20.0 #ffcccc 451.99 123.82 0.0 -99 STAG2 ELLIPSE 20.0 #ffcccc 277.93 872.88 0.0 -100 WDR44 ELLIPSE 20.0 #ffcccc 255.7 190.79 0.0 -101 JUND ELLIPSE 20.0 #ffcccc 431.21 979.55 0.0 -102 HIST1H2AC ELLIPSE 20.0 #ffcccc 385.46 805.05 0.0 -103 TERF2 ELLIPSE 20.0 #ffcccc 227.69 1125.9 0.0 -104 CCNB1 ELLIPSE 20.0 #ffcccc 519.34 922.16 0.0 -105 SMC5 ELLIPSE 20.0 #ffcccc 149.36 1117.63 0.0 -106 SMC1A ELLIPSE 20.0 #ffcccc 195.14 876.34 0.0 -107 TIMP1 ELLIPSE 20.0 #ffcccc 2913.78 241.28 0.0 -108 CD63 ELLIPSE 20.0 #ffcccc 2947.22 318.55 0.0 -109 CORO1A ELLIPSE 20.0 #ffcccc 1416.58 221.31 0.0 -110 AKTIP ELLIPSE 20.0 #ffcccc 1450.14 450.03 0.0 -111 CD37 ELLIPSE 20.0 #ffcccc 1571.88 112.15 0.0 -112 POC1A ELLIPSE 20.0 #ffcccc 986.91 234.0 0.0 -113 DOCK2 ELLIPSE 20.0 #ffcccc 1585.86 232.12 0.0 -114 NME3 ELLIPSE 20.0 #ffcccc 438.91 -230.18 0.0 -115 BBS2 ELLIPSE 20.0 #ffcccc 403.92 -25.03 0.0 -116 NME7 ELLIPSE 20.0 #ffcccc 445.26 -303.64 0.0 -117 NUDT2 ELLIPSE 20.0 #ffcccc 375.33 -283.2 0.0 -118 GUK1 ELLIPSE 20.0 #ffcccc 543.88 -368.29 0.0 -119 ARHGDIG ELLIPSE 20.0 #ffcccc 1581.54 421.34 0.0 -120 STUB1 ELLIPSE 20.0 #ffcccc 573.18 109.97 0.0 -121 JOSD2 ELLIPSE 20.0 #ffcccc 733.27 31.24 0.0 -122 CLPP ELLIPSE 20.0 #ffcccc 322.16 -131.3 0.0 -123 CCT8 ELLIPSE 20.0 #ffcccc 326.04 298.39 0.0 -124 CCT3 ELLIPSE 20.0 #ffcccc 295.85 256.82 0.0 -125 TWIST1 ELLIPSE 20.0 #ffcccc 623.34 504.52 0.0 -126 KCNH2 ELLIPSE 20.0 #ffcccc 507.31 258.13 0.0 -127 UBE2E1 ELLIPSE 20.0 #ffcccc 547.14 284.82 0.0 -128 UBE2E2 ELLIPSE 20.0 #ffcccc 681.2 63.04 0.0 -129 B4GAT1 ELLIPSE 20.0 #ffcccc 675.1 -114.52 0.0 -130 PEDS1-UBE2V1 ELLIPSE 20.0 #ffcccc 868.19 -157.66 0.0 -131 RIPK1 ELLIPSE 20.0 #ffcccc 930.37 252.74 0.0 -132 UBE2V1 ELLIPSE 20.0 #ffcccc 775.94 190.22 0.0 -133 MGA ELLIPSE 20.0 #ffcccc 242.85 -311.82 0.0 -134 ZMYND8 ELLIPSE 20.0 #ffcccc 244.01 -543.43 0.0 -135 BOLA2-SMG1P6 ELLIPSE 20.0 #ffcccc 500.99 -22.68 0.0 -136 PELP1 ELLIPSE 20.0 #ffcccc -61.3 -206.45 0.0 -137 AQP9 ELLIPSE 20.0 #ffcccc 2438.54 1674.86 0.0 -138 AQP7 ELLIPSE 20.0 #ffcccc 2363.34 1677.46 0.0 -139 EIF3E ELLIPSE 20.0 #ffcccc 59.65 339.11 0.0 -140 MPND ELLIPSE 20.0 #ffcccc 380.1 285.66 0.0 -141 MYSM1 ELLIPSE 20.0 #ffcccc 482.44 319.38 0.0 -142 RPL34 ELLIPSE 20.0 #ffcccc 188.32 113.77 0.0 -143 RPL13A ELLIPSE 20.0 #ffcccc 26.69 -23.87 0.0 -144 GTPBP4 ELLIPSE 20.0 #ffcccc -183.81 345.13 0.0 -145 RPL31 ELLIPSE 20.0 #ffcccc 248.8 99.18 0.0 -146 RPL26 ELLIPSE 20.0 #ffcccc 230.15 -8.52 0.0 -147 RPL3L ELLIPSE 20.0 #ffcccc 138.47 246.63 0.0 -148 RPL7A ELLIPSE 20.0 #ffcccc 115.25 -2.49 0.0 -149 RPL27 ELLIPSE 20.0 #ffcccc -43.78 15.66 0.0 -150 RPL24 ELLIPSE 20.0 #ffcccc -99.7 61.47 0.0 -151 RPL7 ELLIPSE 20.0 #ffcccc 76.94 80.81 0.0 -152 RPL18 ELLIPSE 20.0 #ffcccc 122.91 479.94 0.0 -153 EIF1 ELLIPSE 20.0 #ffcccc 76.91 169.82 0.0 -154 RPS20 ELLIPSE 20.0 #ffcccc -222.97 247.33 0.0 -155 RPS10 ELLIPSE 20.0 #ffcccc -124.58 210.16 0.0 -156 RPS19 ELLIPSE 20.0 #ffcccc 222.26 456.75 0.0 -157 RACK1 ELLIPSE 20.0 #ffcccc 473.17 369.09 0.0 -158 RPS3 ELLIPSE 20.0 #ffcccc 38.0 577.82 0.0 -159 EIF4G1 ELLIPSE 20.0 #ffcccc 77.64 441.43 0.0 -160 EIF3L ELLIPSE 20.0 #ffcccc 13.09 264.17 0.0 -161 EIF3CL ELLIPSE 20.0 #ffcccc 127.6 206.22 0.0 -162 EIF3C ELLIPSE 20.0 #ffcccc 176.52 260.84 0.0 -163 GSR ELLIPSE 20.0 #ffcccc 457.28 -647.78 0.0 -164 PDHB ELLIPSE 20.0 #ffcccc 208.51 -267.82 0.0 -165 GSTP1 ELLIPSE 20.0 #ffcccc 601.85 -819.73 0.0 -166 GGT5 ELLIPSE 20.0 #ffcccc 596.84 -755.2 0.0 -167 SNAPC2 ELLIPSE 20.0 #ffcccc -190.69 959.25 0.0 -168 GTF2E2 ELLIPSE 20.0 #ffcccc -148.25 885.22 0.0 -169 ZNF143 ELLIPSE 20.0 #ffcccc -237.8 928.15 0.0 -170 APLP1 ELLIPSE 20.0 #ffcccc 1536.39 1078.01 0.0 -171 KIF5A ELLIPSE 20.0 #ffcccc 1293.14 897.8 0.0 -172 APBB3 ELLIPSE 20.0 #ffcccc 1663.38 1170.77 0.0 -173 RABAC1 ELLIPSE 20.0 #ffcccc 1746.17 1822.48 0.0 -174 GCDH ELLIPSE 20.0 #ffcccc 85.37 -755.26 0.0 -175 ETFDH ELLIPSE 20.0 #ffcccc 130.15 -598.06 0.0 -176 COMP ELLIPSE 20.0 #ffcccc 1759.79 598.65 0.0 -177 ITGA9 ELLIPSE 20.0 #ffcccc 1565.99 560.48 0.0 -178 SNAP47 ELLIPSE 20.0 #ffcccc 1058.12 344.06 0.0 -179 GRIA1 ELLIPSE 20.0 #ffcccc 1018.9 583.83 0.0 -180 SEC22A ELLIPSE 20.0 #ffcccc 908.62 437.16 0.0 -181 STX5 ELLIPSE 20.0 #ffcccc 1005.26 418.21 0.0 -182 CHN2 ELLIPSE 20.0 #ffcccc 1301.16 299.39 0.0 -183 RBM28 ELLIPSE 20.0 #ffcccc -321.69 189.26 0.0 -184 IFI16 ELLIPSE 20.0 #ffcccc -283.37 31.15 0.0 -185 FTSJ1 ELLIPSE 20.0 #ffcccc -396.54 117.48 0.0 -186 C7orf50 ELLIPSE 20.0 #ffcccc -347.32 323.95 0.0 -187 DHX32 ELLIPSE 20.0 #ffcccc -392.58 327.97 0.0 -188 GPATCH4 ELLIPSE 20.0 #ffcccc -90.78 430.57 0.0 -189 GNL1 ELLIPSE 20.0 #ffcccc -219.58 170.35 0.0 -190 NVL ELLIPSE 20.0 #ffcccc -330.52 262.57 0.0 -191 SNU13 ELLIPSE 20.0 #ffcccc -206.26 460.06 0.0 -192 BRIX1 ELLIPSE 20.0 #ffcccc -165.28 232.55 0.0 -193 DDX47 ELLIPSE 20.0 #ffcccc -83.94 305.04 0.0 -194 FIS1 ELLIPSE 20.0 #ffcccc 301.03 -379.2 0.0 -195 MAF1 ELLIPSE 20.0 #ffcccc 264.02 -159.01 0.0 -196 SFXN3 ELLIPSE 20.0 #ffcccc -369.62 -313.93 0.0 -197 SUPT4H1 ELLIPSE 20.0 #ffcccc -165.53 555.5 0.0 -198 ELOC ELLIPSE 20.0 #ffcccc 14.7 467.18 0.0 -199 TCEANC2 ELLIPSE 20.0 #ffcccc -278.53 730.48 0.0 -200 NCL ELLIPSE 20.0 #ffcccc -250.3 328.88 0.0 -201 WDR61 ELLIPSE 20.0 #ffcccc 5.42 339.39 0.0 -202 C1QBP ELLIPSE 20.0 #ffcccc 172.22 485.55 0.0 -203 MRPS27 ELLIPSE 20.0 #ffcccc -97.34 373.64 0.0 -204 FMR1 ELLIPSE 20.0 #ffcccc -111.85 613.78 0.0 -205 UBAP2L ELLIPSE 20.0 #ffcccc 107.64 608.79 0.0 -206 MAGED2 ELLIPSE 20.0 #ffcccc 555.43 808.17 0.0 -207 SSBP1 ELLIPSE 20.0 #ffcccc -36.12 504.5 0.0 -208 GP1BB ELLIPSE 20.0 #ffcccc 584.78 917.5 0.0 -209 TOMM40 ELLIPSE 20.0 #ffcccc 174.33 1.35 0.0 -210 MCM9 ELLIPSE 20.0 #ffcccc 105.43 688.12 0.0 -211 DDX39B ELLIPSE 20.0 #ffcccc -37.55 448.77 0.0 -212 AKAP10 ELLIPSE 20.0 #ffcccc 433.35 1282.12 0.0 -213 PRKAR1B ELLIPSE 20.0 #ffcccc 461.27 926.74 0.0 -214 TMEM97 ELLIPSE 20.0 #ffcccc 632.75 -546.8 0.0 -215 JADE1 ELLIPSE 20.0 #ffcccc -747.13 468.51 0.0 -216 YJU2 ELLIPSE 20.0 #ffcccc -536.75 472.27 0.0 -217 ZPR1 ELLIPSE 20.0 #ffcccc 1239.7 381.39 0.0 -218 IL10RA ELLIPSE 20.0 #ffcccc 1756.65 172.73 0.0 -219 PTCH2 ELLIPSE 20.0 #ffcccc 680.04 291.37 0.0 -220 MAPK14 ELLIPSE 20.0 #ffcccc 832.72 584.87 0.0 -221 TCF4 ELLIPSE 20.0 #ffcccc 665.07 565.26 0.0 -222 FOXO3 ELLIPSE 20.0 #ffcccc 640.43 846.71 0.0 -223 ESR2 ELLIPSE 20.0 #ffcccc 667.93 612.41 0.0 -224 CBX8 ELLIPSE 20.0 #ffcccc 365.87 486.91 0.0 -225 NCOR2 ELLIPSE 20.0 #ffcccc 651.33 445.76 0.0 -226 ETS2 ELLIPSE 20.0 #ffcccc 602.69 786.56 0.0 -227 BLK ELLIPSE 20.0 #ffcccc 1118.72 357.3 0.0 -228 KDR ELLIPSE 20.0 #ffcccc 1125.67 586.11 0.0 -229 CD40LG ELLIPSE 20.0 #ffcccc 1195.38 255.62 0.0 -230 MEF2C ELLIPSE 20.0 #ffcccc 548.04 614.04 0.0 -231 MAP2K3 ELLIPSE 20.0 #ffcccc 1080.71 235.14 0.0 -232 ZFAND5 ELLIPSE 20.0 #ffcccc 607.66 -22.62 0.0 -233 PATJ ELLIPSE 20.0 #ffcccc 986.83 2.31 0.0 -234 TTC31 ELLIPSE 20.0 #ffcccc -443.84 -166.87 0.0 -235 PTGES3L-AARSD1 ELLIPSE 20.0 #ffcccc -257.0 -67.12 0.0 -236 FGF23 ELLIPSE 20.0 #ffcccc 1160.17 730.94 0.0 -237 CNTRL ELLIPSE 20.0 #ffcccc 1203.86 996.58 0.0 -238 MET ELLIPSE 20.0 #ffcccc 1204.54 460.44 0.0 -239 GDA ELLIPSE 20.0 #ffcccc 708.32 487.54 0.0 -240 LARS1 ELLIPSE 20.0 #ffcccc 251.98 379.28 0.0 -241 LCMT2 ELLIPSE 20.0 #ffcccc 740.19 698.61 0.0 -242 UPB1 ELLIPSE 20.0 #ffcccc 991.24 -137.98 0.0 -243 IFT81 ELLIPSE 20.0 #ffcccc 1646.75 -135.42 0.0 -244 TRAF3IP1 ELLIPSE 20.0 #ffcccc 1547.29 -23.16 0.0 -245 IFT46 ELLIPSE 20.0 #ffcccc 1684.65 -83.54 0.0 -246 SNRPA ELLIPSE 20.0 #ffcccc -399.07 381.54 0.0 -247 HNRNPA3 ELLIPSE 20.0 #ffcccc -232.62 585.64 0.0 -248 MBNL2 ELLIPSE 20.0 #ffcccc -646.67 303.96 0.0 -249 FMC1-LUC7L2 ELLIPSE 20.0 #ffcccc -592.7 465.55 0.0 -250 HNRNPA1 ELLIPSE 20.0 #ffcccc -45.36 332.23 0.0 -251 SF1 ELLIPSE 20.0 #ffcccc -268.89 403.47 0.0 -252 SFPQ ELLIPSE 20.0 #ffcccc -141.4 497.24 0.0 -253 SART1 ELLIPSE 20.0 #ffcccc -537.3 381.0 0.0 -254 C4BPB ELLIPSE 20.0 #ffcccc 1620.53 926.93 0.0 -255 DCTN4 ELLIPSE 20.0 #ffcccc 1459.69 830.36 0.0 -256 MT-CO3 ELLIPSE 20.0 #ffcccc -258.06 -329.35 0.0 -257 RPL39 ELLIPSE 20.0 #ffcccc -21.74 139.86 0.0 -258 PPA1 ELLIPSE 20.0 #ffcccc 128.71 -147.82 0.0 -259 LHPP ELLIPSE 20.0 #ffcccc 89.47 -281.09 0.0 -260 ATP6V0B ELLIPSE 20.0 #ffcccc 150.1 -374.18 0.0 -261 ATP6AP1 ELLIPSE 20.0 #ffcccc 86.02 -358.46 0.0 -262 PPA2 ELLIPSE 20.0 #ffcccc 70.49 -127.11 0.0 -263 ATP6V1H ELLIPSE 20.0 #ffcccc 239.25 -230.65 0.0 -264 CFP ELLIPSE 20.0 #ffcccc -1443.31 284.32 0.0 -265 ADAMTS18 ELLIPSE 20.0 #ffcccc -1406.65 226.71 0.0 -266 ADAMTS3 ELLIPSE 20.0 #ffcccc -1465.25 189.62 0.0 -267 ADAMTSL2 ELLIPSE 20.0 #ffcccc -1502.33 247.83 0.0 -268 CANX ELLIPSE 20.0 #ffcccc 603.98 149.28 0.0 -269 RAB40A ELLIPSE 20.0 #ffcccc 132.38 85.51 0.0 -270 RAB12 ELLIPSE 20.0 #ffcccc 515.5 72.69 0.0 -271 HLA-DRA ELLIPSE 20.0 #ffcccc 979.61 172.73 0.0 -272 HLA-E ELLIPSE 20.0 #ffcccc 1060.96 149.16 0.0 -273 TAP2 ELLIPSE 20.0 #ffcccc 842.68 115.98 0.0 -274 VDAC1 ELLIPSE 20.0 #ffcccc 361.5 -170.8 0.0 -275 PIN1 ELLIPSE 20.0 #ffcccc 805.35 678.7 0.0 -276 PPP2R2A ELLIPSE 20.0 #ffcccc 599.93 692.94 0.0 -277 PPP2R5A ELLIPSE 20.0 #ffcccc 865.12 830.11 0.0 -278 PRKCD ELLIPSE 20.0 #ffcccc 1006.95 494.71 0.0 -279 AXIN1 ELLIPSE 20.0 #ffcccc 1020.18 715.62 0.0 -280 JPT2 ELLIPSE 20.0 #ffcccc 303.79 1208.48 0.0 -281 STMN1 ELLIPSE 20.0 #ffcccc 359.23 977.94 0.0 -282 PEX1 ELLIPSE 20.0 #ffcccc 75.57 831.74 0.0 -283 MLLT6 ELLIPSE 20.0 #ffcccc 337.81 1311.64 0.0 -284 ZC3H4 ELLIPSE 20.0 #ffcccc 319.52 1093.16 0.0 -285 CLP1 ELLIPSE 20.0 #ffcccc -46.07 840.04 0.0 -286 PDXDC1 ELLIPSE 20.0 #ffcccc 253.03 -68.65 0.0 -287 TNS4 ELLIPSE 20.0 #ffcccc 1417.77 388.04 0.0 -288 FUS ELLIPSE 20.0 #ffcccc -54.62 612.12 0.0 -289 YEATS2 ELLIPSE 20.0 #ffcccc -118.9 965.16 0.0 -290 HNRNPA1L2 ELLIPSE 20.0 #ffcccc -254.05 472.81 0.0 -291 RXRA ELLIPSE 20.0 #ffcccc 286.39 530.79 0.0 -292 HNRNPUL1 ELLIPSE 20.0 #ffcccc -343.55 559.36 0.0 -293 SMARCA4 ELLIPSE 20.0 #ffcccc 340.06 553.1 0.0 -294 HSD17B7 ELLIPSE 20.0 #ffcccc 1101.06 1706.19 0.0 -295 TM7SF2 ELLIPSE 20.0 #ffcccc 1136.86 1643.97 0.0 -296 HSD17B12 ELLIPSE 20.0 #ffcccc 1107.79 1815.94 0.0 -297 DHCR24 ELLIPSE 20.0 #ffcccc 1075.46 1533.81 0.0 -298 EEFSEC ELLIPSE 20.0 #ffcccc 21.39 163.92 0.0 -299 MRPL20 ELLIPSE 20.0 #ffcccc -65.6 219.42 0.0 -300 DERPC ELLIPSE 20.0 #ffcccc 161.31 1310.08 0.0 -301 PPP6R3 ELLIPSE 20.0 #ffcccc 207.82 1349.2 0.0 -302 PDE6A ELLIPSE 20.0 #ffcccc 563.84 -564.58 0.0 -303 BTG1 ELLIPSE 20.0 #ffcccc 754.96 1042.73 0.0 -304 CCNJ ELLIPSE 20.0 #ffcccc 557.64 1224.59 0.0 -305 MIS18BP1 ELLIPSE 20.0 #ffcccc 488.89 1149.82 0.0 -306 DNMT1 ELLIPSE 20.0 #ffcccc 228.85 834.0 0.0 -307 CNPPD1 ELLIPSE 20.0 #ffcccc 589.43 1149.92 0.0 -308 STIL ELLIPSE 20.0 #ffcccc 619.76 1221.93 0.0 -309 CDK16 ELLIPSE 20.0 #ffcccc 614.55 1012.06 0.0 -310 RCC1 ELLIPSE 20.0 #ffcccc 391.74 687.14 0.0 -311 CENPU ELLIPSE 20.0 #ffcccc 435.03 1107.41 0.0 -312 HJURP ELLIPSE 20.0 #ffcccc 636.68 1080.76 0.0 -313 KIFC1 ELLIPSE 20.0 #ffcccc 1113.78 972.51 0.0 -314 CKAP2 ELLIPSE 20.0 #ffcccc 482.06 1091.36 0.0 -315 NUP42 ELLIPSE 20.0 #ffcccc 17.05 635.47 0.0 -316 SKA3 ELLIPSE 20.0 #ffcccc 529.79 1122.95 0.0 -317 KPNA2 ELLIPSE 20.0 #ffcccc 422.61 867.75 0.0 -318 KIDINS220 ELLIPSE 20.0 #ffcccc 1593.7 648.43 0.0 -319 BDNF ELLIPSE 20.0 #ffcccc 1381.45 610.98 0.0 -320 ARHGAP9 ELLIPSE 20.0 #ffcccc 1608.68 301.6 0.0 -321 COMMD6 ELLIPSE 20.0 #ffcccc 98.24 909.04 0.0 -322 DCUN1D2 ELLIPSE 20.0 #ffcccc 225.83 789.75 0.0 -323 DCAF17 ELLIPSE 20.0 #ffcccc 173.21 927.21 0.0 -324 H2AC8 ELLIPSE 20.0 #ffcccc 295.46 660.97 0.0 -325 DOCK10 ELLIPSE 20.0 #ffcccc 1639.81 370.69 0.0 -326 NXF1 ELLIPSE 20.0 #ffcccc -224.37 546.0 0.0 -327 XPOT ELLIPSE 20.0 #ffcccc -168.05 798.34 0.0 -328 TBRG4 ELLIPSE 20.0 #ffcccc 95.44 -202.42 0.0 -329 ABHD17C ELLIPSE 20.0 #ffcccc 1196.17 -686.3 0.0 -330 LYPLA1 ELLIPSE 20.0 #ffcccc 1120.44 -579.18 0.0 -331 MARCHF7 ELLIPSE 20.0 #ffcccc 1060.84 50.78 0.0 -332 USP9X ELLIPSE 20.0 #ffcccc 927.45 207.01 0.0 -333 ITK ELLIPSE 20.0 #ffcccc 1262.68 63.3 0.0 -334 RASA1 ELLIPSE 20.0 #ffcccc 1138.39 477.47 0.0 -335 RNF38 ELLIPSE 20.0 #ffcccc 794.11 970.55 0.0 -336 TP63 ELLIPSE 20.0 #ffcccc 716.61 785.78 0.0 -337 HINT2 ELLIPSE 20.0 #ffcccc -183.15 -439.3 0.0 -338 MAP4K2 ELLIPSE 20.0 #ffcccc 1142.89 228.21 0.0 -339 TRAF3 ELLIPSE 20.0 #ffcccc 1239.45 196.44 0.0 -340 IKBKG ELLIPSE 20.0 #ffcccc 932.88 90.82 0.0 -341 CHRNA1 ELLIPSE 20.0 #ffcccc 1414.7 915.31 0.0 -342 CHRNA7 ELLIPSE 20.0 #ffcccc 1651.88 1029.76 0.0 -343 CHRM1 ELLIPSE 20.0 #ffcccc 1259.41 1066.85 0.0 -344 CACNG8 ELLIPSE 20.0 #ffcccc 898.7 730.59 0.0 -345 CACNB2 ELLIPSE 20.0 #ffcccc 903.89 628.35 0.0 -346 CNEP1R1 ELLIPSE 20.0 #ffcccc 747.07 886.87 0.0 -347 WNT8A ELLIPSE 20.0 #ffcccc 1057.3 840.6 0.0 -348 DVL1 ELLIPSE 20.0 #ffcccc 1016.37 907.63 0.0 -349 PPP4R4 ELLIPSE 20.0 #ffcccc 757.3 822.64 0.0 -350 POMT2 ELLIPSE 20.0 #ffcccc 1646.79 745.42 0.0 -351 DPM3 ELLIPSE 20.0 #ffcccc 1900.58 786.84 0.0 -352 KCNQ3 ELLIPSE 20.0 #ffcccc 500.23 430.69 0.0 -353 KCNAB1 ELLIPSE 20.0 #ffcccc 453.24 283.91 0.0 -354 KCNQ4 ELLIPSE 20.0 #ffcccc 388.23 351.83 0.0 -355 RHEB ELLIPSE 20.0 #ffcccc 233.9 -373.66 0.0 -356 LAMTOR4 ELLIPSE 20.0 #ffcccc 119.38 -328.52 0.0 -357 SCPEP1 ELLIPSE 20.0 #ffcccc -91.22 -329.26 0.0 -358 GAPVD1 ELLIPSE 20.0 #ffcccc 1144.69 859.15 0.0 -359 CTNNBIP1 ELLIPSE 20.0 #ffcccc 1199.45 875.01 0.0 -360 CSNK1G1 ELLIPSE 20.0 #ffcccc 1105.13 899.74 0.0 -361 CHST8 ELLIPSE 20.0 #ffcccc 2793.9 1678.52 0.0 -362 B4GALNT3 ELLIPSE 20.0 #ffcccc 2718.02 1678.93 0.0 -363 MYH7B ELLIPSE 20.0 #ffcccc 641.55 -325.63 0.0 -364 ALDOA ELLIPSE 20.0 #ffcccc 589.21 -170.61 0.0 -365 RPL38 ELLIPSE 20.0 #ffcccc 216.75 331.92 0.0 -366 DNAJC5G ELLIPSE 20.0 #ffcccc -611.9 370.92 0.0 -367 MED15 ELLIPSE 20.0 #ffcccc 239.55 668.89 0.0 -368 ANGPTL4 ELLIPSE 20.0 #ffcccc 344.88 624.39 0.0 -369 CDK19 ELLIPSE 20.0 #ffcccc 313.94 712.44 0.0 -370 WDR76 ELLIPSE 20.0 #ffcccc 334.85 -57.17 0.0 -371 GOLGA4 ELLIPSE 20.0 #ffcccc 945.23 767.17 0.0 -372 PLCB4 ELLIPSE 20.0 #ffcccc 1090.6 288.69 0.0 -373 SHC2 ELLIPSE 20.0 #ffcccc 1316.45 549.84 0.0 -374 KIF1B ELLIPSE 20.0 #ffcccc 1356.08 807.65 0.0 -375 KIF9 ELLIPSE 20.0 #ffcccc 1293.92 979.81 0.0 -376 KIF2A ELLIPSE 20.0 #ffcccc 1364.27 972.87 0.0 -377 KLC2 ELLIPSE 20.0 #ffcccc 1354.29 882.66 0.0 -378 THOC3 ELLIPSE 20.0 #ffcccc -324.72 679.6 0.0 -379 SRSF5 ELLIPSE 20.0 #ffcccc -293.81 607.62 0.0 -380 GAS8 ELLIPSE 20.0 #ffcccc 463.84 711.36 0.0 -381 FLNC ELLIPSE 20.0 #ffcccc 1768.11 526.89 0.0 -382 SCARB2 ELLIPSE 20.0 #ffcccc 2902.45 391.15 0.0 -383 MGLL ELLIPSE 20.0 #ffcccc 724.35 1818.0 0.0 -384 AKR1A1 ELLIPSE 20.0 #ffcccc 800.52 1820.32 0.0 -385 ZCRB1 ELLIPSE 20.0 #ffcccc -273.54 792.87 0.0 -386 ATG5 ELLIPSE 20.0 #ffcccc 361.85 -536.47 0.0 -387 BAK1 ELLIPSE 20.0 #ffcccc 164.69 -226.68 0.0 -388 FKBP8 ELLIPSE 20.0 #ffcccc 368.97 -428.1 0.0 -389 TSPO ELLIPSE 20.0 #ffcccc 407.86 -383.77 0.0 -390 ALDH8A1 ELLIPSE 20.0 #ffcccc -716.44 -6.22 0.0 -391 PAH ELLIPSE 20.0 #ffcccc -562.12 49.79 0.0 -392 R3HCC1 ELLIPSE 20.0 #ffcccc 2458.77 -235.16 0.0 -393 FAM214B ELLIPSE 20.0 #ffcccc 2383.36 -239.54 0.0 -394 ARNTL2 ELLIPSE 20.0 #ffcccc -909.97 -845.97 0.0 -395 NPAS4 ELLIPSE 20.0 #ffcccc -946.63 -779.53 0.0 -396 SNRNP25 ELLIPSE 20.0 #ffcccc -316.08 851.23 0.0 -397 UBE2Q2 ELLIPSE 20.0 #ffcccc 648.36 111.32 0.0 -398 UBE2G1 ELLIPSE 20.0 #ffcccc 725.95 115.12 0.0 -399 UBE2F ELLIPSE 20.0 #ffcccc 621.21 201.36 0.0 -400 SEPTIN12 ELLIPSE 20.0 #ffcccc -939.77 1773.55 0.0 -401 TMEM250 ELLIPSE 20.0 #ffcccc -879.76 1817.13 0.0 -402 MTRF1L ELLIPSE 20.0 #ffcccc -70.49 135.01 0.0 -403 OSTC ELLIPSE 20.0 #ffcccc 343.36 244.06 0.0 -404 C18orf32 ELLIPSE 20.0 #ffcccc 99.63 352.69 0.0 -405 RPL36A ELLIPSE 20.0 #ffcccc -17.39 371.53 0.0 -406 EIF6 ELLIPSE 20.0 #ffcccc -46.25 272.37 0.0 -407 APOBEC3A ELLIPSE 20.0 #ffcccc -181.42 -34.86 0.0 -408 APOBEC3G ELLIPSE 20.0 #ffcccc -138.0 -27.41 0.0 -409 CHCHD6 ELLIPSE 20.0 #ffcccc 33.31 -84.1 0.0 -410 SDHD ELLIPSE 20.0 #ffcccc 28.98 -400.29 0.0 -411 CFAP45 ELLIPSE 20.0 #ffcccc 179.64 538.19 0.0 -412 H1-10 ELLIPSE 20.0 #ffcccc 400.43 611.17 0.0 -413 CASP8AP2 ELLIPSE 20.0 #ffcccc 467.55 567.24 0.0 -414 LRRC56 ELLIPSE 20.0 #ffcccc 1070.55 1360.02 0.0 -415 SUOX ELLIPSE 20.0 #ffcccc 1026.63 1173.24 0.0 -416 CACNA1G ELLIPSE 20.0 #ffcccc 799.4 733.12 0.0 -417 GRIK1 ELLIPSE 20.0 #ffcccc 865.34 656.14 0.0 -418 GRID2 ELLIPSE 20.0 #ffcccc 972.63 714.33 0.0 -419 EPB41L1 ELLIPSE 20.0 #ffcccc 1044.27 761.31 0.0 -420 POGZ ELLIPSE 20.0 #ffcccc 706.61 1457.43 0.0 -421 NRF1 ELLIPSE 20.0 #ffcccc 670.89 1598.49 0.0 -422 CHAMP1 ELLIPSE 20.0 #ffcccc 743.26 1594.18 0.0 -423 PELO ELLIPSE 20.0 #ffcccc 106.87 295.64 0.0 -424 ANXA6 ELLIPSE 20.0 #ffcccc 1345.89 457.17 0.0 -425 GPR174 ELLIPSE 20.0 #ffcccc 1198.32 -9.34 0.0 -426 INPPL1 ELLIPSE 20.0 #ffcccc 1188.91 152.98 0.0 -427 PLD4 ELLIPSE 20.0 #ffcccc 1067.93 -311.96 0.0 -428 GRAP2 ELLIPSE 20.0 #ffcccc 1150.99 122.48 0.0 -429 GNRH1 ELLIPSE 20.0 #ffcccc 1493.8 1325.1 0.0 -430 CCK ELLIPSE 20.0 #ffcccc 1361.98 1272.42 0.0 -431 EDN3 ELLIPSE 20.0 #ffcccc 1442.58 1234.6 0.0 -432 LRP12 ELLIPSE 20.0 #ffcccc -1516.95 -474.15 0.0 -433 GPC2 ELLIPSE 20.0 #ffcccc -1595.68 -461.09 0.0 -434 LIN7C ELLIPSE 20.0 #ffcccc 1095.27 -180.07 0.0 -435 IBTK ELLIPSE 20.0 #ffcccc -479.33 798.85 0.0 -436 DNAJC1 ELLIPSE 20.0 #ffcccc 80.33 233.6 0.0 -437 GPM6A ELLIPSE 20.0 #ffcccc 931.05 1190.73 0.0 -438 SYNPR ELLIPSE 20.0 #ffcccc 1183.12 1216.87 0.0 -439 SLC6A1 ELLIPSE 20.0 #ffcccc 1130.84 1263.56 0.0 -440 NGLY1 ELLIPSE 20.0 #ffcccc 878.3 -52.34 0.0 -441 ITM2B ELLIPSE 20.0 #ffcccc 970.99 -226.53 0.0 -442 UBXN1 ELLIPSE 20.0 #ffcccc 810.44 -66.79 0.0 -443 AMFR ELLIPSE 20.0 #ffcccc 795.18 64.19 0.0 -444 FER ELLIPSE 20.0 #ffcccc 1477.71 619.4 0.0 -445 SCLT1 ELLIPSE 20.0 #ffcccc -580.81 1822.61 0.0 -446 FBF1 ELLIPSE 20.0 #ffcccc -505.44 1822.82 0.0 -447 DONSON ELLIPSE 20.0 #ffcccc 400.08 1353.49 0.0 -448 GADL1 ELLIPSE 20.0 #ffcccc 1175.04 -270.27 0.0 -449 CARNS1 ELLIPSE 20.0 #ffcccc 1130.21 -308.06 0.0 -450 SCN3A ELLIPSE 20.0 #ffcccc 777.97 591.17 0.0 -451 SCN3B ELLIPSE 20.0 #ffcccc 722.18 628.16 0.0 -452 SCN1B ELLIPSE 20.0 #ffcccc 722.1 571.91 0.0 -453 LPCAT1 ELLIPSE 20.0 #ffcccc 1116.31 -469.9 0.0 -454 PLA2G4E ELLIPSE 20.0 #ffcccc 992.89 -468.76 0.0 -455 PLD3 ELLIPSE 20.0 #ffcccc 1012.82 -375.36 0.0 -456 PLA2G10 ELLIPSE 20.0 #ffcccc 1032.59 -467.76 0.0 -457 RBM10 ELLIPSE 20.0 #ffcccc -431.6 264.85 0.0 -458 TSEN2 ELLIPSE 20.0 #ffcccc 24.26 815.59 0.0 -459 PRKRA ELLIPSE 20.0 #ffcccc 47.09 957.09 0.0 -460 AGO4 ELLIPSE 20.0 #ffcccc 300.85 816.14 0.0 -461 ERN1 ELLIPSE 20.0 #ffcccc 121.64 945.78 0.0 -462 ODF1 ELLIPSE 20.0 #ffcccc 402.14 -79.55 0.0 -463 BUB3 ELLIPSE 20.0 #ffcccc 119.88 552.21 0.0 -464 FKBP9 ELLIPSE 20.0 #ffcccc 492.58 -91.9 0.0 -465 GBA ELLIPSE 20.0 #ffcccc 480.83 -197.61 0.0 -466 CPNE6 ELLIPSE 20.0 #ffcccc 1279.48 1312.08 0.0 -467 SNAP91 ELLIPSE 20.0 #ffcccc 1147.66 1070.13 0.0 -468 SNCB ELLIPSE 20.0 #ffcccc 1308.13 1205.51 0.0 -469 LY6H ELLIPSE 20.0 #ffcccc 1227.4 1280.05 0.0 -470 BRWD3 ELLIPSE 20.0 #ffcccc 837.95 166.31 0.0 -471 HM13 ELLIPSE 20.0 #ffcccc 652.84 247.19 0.0 -472 CSPG5 ELLIPSE 20.0 #ffcccc -1675.38 -452.07 0.0 -473 TMEM14C ELLIPSE 20.0 #ffcccc -43.6 -497.87 0.0 -474 TMEM256 ELLIPSE 20.0 #ffcccc -86.58 -458.54 0.0 -475 COX14 ELLIPSE 20.0 #ffcccc -272.42 -396.15 0.0 -476 MAML1 ELLIPSE 20.0 #ffcccc 607.47 628.97 0.0 -477 HDAC9 ELLIPSE 20.0 #ffcccc 464.0 646.0 0.0 -478 SHLD3 ELLIPSE 20.0 #ffcccc 263.72 43.07 0.0 -479 FBXL19 ELLIPSE 20.0 #ffcccc 228.83 230.46 0.0 -480 BTBD9 ELLIPSE 20.0 #ffcccc 882.77 -254.59 0.0 -481 UBXN6 ELLIPSE 20.0 #ffcccc 732.62 -302.01 0.0 -482 TRAPPC1 ELLIPSE 20.0 #ffcccc 1064.09 480.46 0.0 -483 DNAI3 ELLIPSE 20.0 #ffcccc -187.82 632.66 0.0 -484 CCDC114 ELLIPSE 20.0 #ffcccc 14.64 509.68 0.0 -485 FABP1 ELLIPSE 20.0 #ffcccc 498.67 494.63 0.0 -486 RGL1 ELLIPSE 20.0 #ffcccc 438.61 516.58 0.0 -487 CHD9 ELLIPSE 20.0 #ffcccc 391.33 432.01 0.0 -488 ADH5 ELLIPSE 20.0 #ffcccc 618.8 -938.98 0.0 -489 NKD2 ELLIPSE 20.0 #ffcccc 1076.69 1117.99 0.0 -490 RP9 ELLIPSE 20.0 #ffcccc -749.29 345.18 0.0 -491 RPP25L ELLIPSE 20.0 #ffcccc -523.51 719.25 0.0 -492 ELP2 ELLIPSE 20.0 #ffcccc -530.47 -63.07 0.0 -493 MINPP1 ELLIPSE 20.0 #ffcccc 987.63 87.97 0.0 -494 RXFP2 ELLIPSE 20.0 #ffcccc 1921.95 -662.91 0.0 -495 RXFP1 ELLIPSE 20.0 #ffcccc 1957.38 -731.24 0.0 -496 STAT6 ELLIPSE 20.0 #ffcccc 1110.7 -14.55 0.0 -497 KCTD5 ELLIPSE 20.0 #ffcccc 497.22 1352.14 0.0 -498 KCTD2 ELLIPSE 20.0 #ffcccc 535.04 1303.12 0.0 -499 KLHL12 ELLIPSE 20.0 #ffcccc 645.46 1176.16 0.0 -500 KLHL2 ELLIPSE 20.0 #ffcccc 382.35 1147.31 0.0 -501 TONSL ELLIPSE 20.0 #ffcccc 335.56 895.85 0.0 -502 H2BC8 ELLIPSE 20.0 #ffcccc 277.06 775.26 0.0 -503 OR52A5 ELLIPSE 20.0 #ffcccc 883.04 1055.03 0.0 -504 GNAL ELLIPSE 20.0 #ffcccc 914.07 965.4 0.0 -505 CNOT4 ELLIPSE 20.0 #ffcccc 335.86 383.54 0.0 -506 IPO11 ELLIPSE 20.0 #ffcccc 610.35 46.34 0.0 -507 TRIM32 ELLIPSE 20.0 #ffcccc 688.34 148.76 0.0 -508 ABR ELLIPSE 20.0 #ffcccc 1608.35 489.95 0.0 -509 REV3L ELLIPSE 20.0 #ffcccc 746.09 274.53 0.0 -510 CHMP7 ELLIPSE 20.0 #ffcccc 309.17 192.43 0.0 -511 CHMP6 ELLIPSE 20.0 #ffcccc 307.92 129.37 0.0 -512 ZUP1 ELLIPSE 20.0 #ffcccc 761.37 1193.29 0.0 -513 RAD51B ELLIPSE 20.0 #ffcccc 477.94 844.68 0.0 -514 XRCC3 ELLIPSE 20.0 #ffcccc 511.29 1030.69 0.0 -515 GAA ELLIPSE 20.0 #ffcccc 679.16 -363.84 0.0 -516 ASAH1 ELLIPSE 20.0 #ffcccc 602.23 -405.11 0.0 -517 AMY2B ELLIPSE 20.0 #ffcccc 815.59 -440.94 0.0 -518 GKAP1 ELLIPSE 20.0 #ffcccc -643.18 868.68 0.0 -519 LPAR4 ELLIPSE 20.0 #ffcccc 1140.34 1151.58 0.0 -520 LPAR1 ELLIPSE 20.0 #ffcccc 1251.55 1206.74 0.0 -521 KANSL2 ELLIPSE 20.0 #ffcccc -284.68 1140.08 0.0 -522 MBIP ELLIPSE 20.0 #ffcccc -232.04 1175.23 0.0 -523 SGF29 ELLIPSE 20.0 #ffcccc -299.21 1240.53 0.0 -524 MLLT10 ELLIPSE 20.0 #ffcccc 297.31 1488.39 0.0 -525 SRPK3 ELLIPSE 20.0 #ffcccc -508.01 640.08 0.0 -526 HTATSF1 ELLIPSE 20.0 #ffcccc -664.0 595.35 0.0 -527 ZRSR2P1 ELLIPSE 20.0 #ffcccc -669.84 520.44 0.0 -528 VSNL1 ELLIPSE 20.0 #ffcccc 1421.3 1364.16 0.0 -529 CEND1 ELLIPSE 20.0 #ffcccc 1344.91 1388.6 0.0 -530 MAP3K11 ELLIPSE 20.0 #ffcccc 1307.49 215.34 0.0 -531 ECT2L ELLIPSE 20.0 #ffcccc 489.02 1245.04 0.0 -532 ARR3 ELLIPSE 20.0 #ffcccc 1653.32 438.99 0.0 -533 ZMIZ2 ELLIPSE 20.0 #ffcccc 359.49 754.62 0.0 -534 LCN15 ELLIPSE 20.0 #ffcccc 3031.1 1488.88 0.0 -535 ATG4A ELLIPSE 20.0 #ffcccc 3080.22 1548.69 0.0 -536 CERS5 ELLIPSE 20.0 #ffcccc 546.09 -439.23 0.0 -537 PSAP ELLIPSE 20.0 #ffcccc 484.97 -422.96 0.0 -538 ARL4C ELLIPSE 20.0 #ffcccc 521.06 673.66 0.0 -539 SGIP1 ELLIPSE 20.0 #ffcccc 1079.59 688.02 0.0 -540 C1orf122 ELLIPSE 20.0 #ffcccc -402.87 1341.46 0.0 -541 ATXN7L1 ELLIPSE 20.0 #ffcccc -338.79 1382.7 0.0 -542 DLGAP1 ELLIPSE 20.0 #ffcccc 1321.04 370.47 0.0 -543 ANP32B ELLIPSE 20.0 #ffcccc -615.04 205.8 0.0 -544 CFAP299 ELLIPSE 20.0 #ffcccc -5.08 586.0 0.0 -545 CD6 ELLIPSE 20.0 #ffcccc 1398.77 -103.07 0.0 -546 OR10K2 ELLIPSE 20.0 #ffcccc 972.41 1089.86 0.0 -547 CPVL ELLIPSE 20.0 #ffcccc 721.76 -164.18 0.0 -548 PHF21B ELLIPSE 20.0 #ffcccc 398.64 146.79 0.0 -549 ENSA ELLIPSE 20.0 #ffcccc 673.73 912.72 0.0 -550 FBN1 ELLIPSE 20.0 #ffcccc 2114.43 1674.94 0.0 -551 MFAP5 ELLIPSE 20.0 #ffcccc 2044.6 1712.75 0.0 -552 ELN ELLIPSE 20.0 #ffcccc 2049.23 1633.69 0.0 -553 SETD3 ELLIPSE 20.0 #ffcccc 1444.43 551.0 0.0 -554 BPHL ELLIPSE 20.0 #ffcccc 1652.93 571.56 0.0 -555 MYO9B ELLIPSE 20.0 #ffcccc 583.19 -105.46 0.0 -556 EIF4G2 ELLIPSE 20.0 #ffcccc -20.23 211.6 0.0 -557 ATP11C ELLIPSE 20.0 #ffcccc 930.23 -21.5 0.0 -558 KIF19 ELLIPSE 20.0 #ffcccc 1325.62 1039.63 0.0 -559 OR3A2 ELLIPSE 20.0 #ffcccc 1015.35 991.53 0.0 -560 OR8G1 ELLIPSE 20.0 #ffcccc 949.51 1037.64 0.0 -561 OR2T5 ELLIPSE 20.0 #ffcccc 915.31 1096.27 0.0 -562 OR2T7 ELLIPSE 20.0 #ffcccc 1007.31 1046.81 0.0 -563 LIMK1 ELLIPSE 20.0 #ffcccc 1388.07 724.56 0.0 -564 LIPA ELLIPSE 20.0 #ffcccc 1037.48 1646.86 0.0 -565 SUV39H1 ELLIPSE 20.0 #ffcccc 220.78 627.02 0.0 -566 KDM2B ELLIPSE 20.0 #ffcccc 140.7 786.19 0.0 -567 PBDC1 ELLIPSE 20.0 #ffcccc -282.71 130.23 0.0 -568 ADA ELLIPSE 20.0 #ffcccc -445.98 186.69 0.0 -569 IFNAR2 ELLIPSE 20.0 #ffcccc 929.53 145.15 0.0 -570 TREM2 ELLIPSE 20.0 #ffcccc 1268.28 149.68 0.0 -571 TNRC6A ELLIPSE 20.0 #ffcccc 538.86 730.43 0.0 -572 TNRC6B ELLIPSE 20.0 #ffcccc 487.93 784.92 0.0 -573 GTF3A ELLIPSE 20.0 #ffcccc 228.85 708.04 0.0 -574 COL17A1 ELLIPSE 20.0 #ffcccc -1365.74 852.5 0.0 -575 P4HA3 ELLIPSE 20.0 #ffcccc -1366.9 928.46 0.0 -576 NABP1 ELLIPSE 20.0 #ffcccc -286.72 901.12 0.0 -577 NFIA ELLIPSE 20.0 #ffcccc -241.77 869.47 0.0 -578 FNIP1 ELLIPSE 20.0 #ffcccc 197.05 -456.05 0.0 -579 TAOK3 ELLIPSE 20.0 #ffcccc 1318.64 101.75 0.0 -580 MAP3K15 ELLIPSE 20.0 #ffcccc 1459.95 267.05 0.0 -581 TNFSF13B ELLIPSE 20.0 #ffcccc 1382.26 280.81 0.0 -582 STIM2 ELLIPSE 20.0 #ffcccc 1646.37 176.7 0.0 -583 ANP32A ELLIPSE 20.0 #ffcccc -773.66 159.99 0.0 -584 SYNJ2 ELLIPSE 20.0 #ffcccc 1012.94 317.42 0.0 -585 PIP5KL1 ELLIPSE 20.0 #ffcccc 1177.06 304.23 0.0 -586 WSB2 ELLIPSE 20.0 #ffcccc -69.71 795.54 0.0 -587 BTBD6 ELLIPSE 20.0 #ffcccc 56.17 1079.22 0.0 -588 CCDC93 ELLIPSE 20.0 #ffcccc 3.47 1155.38 0.0 -589 MCF2L ELLIPSE 20.0 #ffcccc 1562.74 349.45 0.0 -590 WNT5B ELLIPSE 20.0 #ffcccc 1156.91 795.88 0.0 -591 ARID5A ELLIPSE 20.0 #ffcccc 419.76 754.35 0.0 -592 GMPPA ELLIPSE 20.0 #ffcccc 2010.06 846.0 0.0 -593 LOXL2 ELLIPSE 20.0 #ffcccc 1979.43 1669.62 0.0 -594 TRPC4 ELLIPSE 20.0 #ffcccc 854.47 903.92 0.0 -595 RNASEK ELLIPSE 20.0 #ffcccc 140.28 -478.56 0.0 -596 TOPORS ELLIPSE 20.0 #ffcccc -1096.03 -382.92 0.0 -597 BLOC1S2 ELLIPSE 20.0 #ffcccc -1135.85 -317.18 0.0 -598 GBE1 ELLIPSE 20.0 #ffcccc 895.94 -320.38 0.0 -599 COA3 ELLIPSE 20.0 #ffcccc -371.88 -450.78 0.0 -600 SENP6 ELLIPSE 20.0 #ffcccc 79.14 1319.33 0.0 -601 SIPA1L2 ELLIPSE 20.0 #ffcccc 3377.62 -247.61 0.0 -602 DYRK1B ELLIPSE 20.0 #ffcccc 3449.34 -222.62 0.0 -603 IBA57 ELLIPSE 20.0 #ffcccc -349.85 -210.3 0.0 -604 PSEN2 ELLIPSE 20.0 #ffcccc 11.54 1258.68 0.0 -605 RYR3 ELLIPSE 20.0 #ffcccc -49.05 1419.22 0.0 -606 DYNLT1 ELLIPSE 20.0 #ffcccc 1550.9 740.89 0.0 -607 PTGS2 ELLIPSE 20.0 #ffcccc 1023.27 -601.6 0.0 -608 ALOX15B ELLIPSE 20.0 #ffcccc 932.04 -632.59 0.0 -609 NAXE ELLIPSE 20.0 #ffcccc 920.72 -494.94 0.0 -610 DOLPP1 ELLIPSE 20.0 #ffcccc 2024.35 765.59 0.0 -611 KCTD20 ELLIPSE 20.0 #ffcccc -9.13 748.0 0.0 -612 TECPR1 ELLIPSE 20.0 #ffcccc 349.43 -715.71 0.0 -613 STRIP1 ELLIPSE 20.0 #ffcccc 3444.39 925.38 0.0 -614 STK26 ELLIPSE 20.0 #ffcccc 3396.27 988.22 0.0 -615 CPEB3 ELLIPSE 20.0 #ffcccc -361.53 744.46 0.0 -616 ADGRL4 ELLIPSE 20.0 #ffcccc 3031.49 319.55 0.0 -617 BAIAP2L2 ELLIPSE 20.0 #ffcccc 1266.61 760.74 0.0 -618 PLEKHG5 ELLIPSE 20.0 #ffcccc 1158.3 -152.63 0.0 -619 HTD2 ELLIPSE 20.0 #ffcccc -750.92 1250.47 0.0 -620 HADH ELLIPSE 20.0 #ffcccc -795.21 1177.41 0.0 -621 FOXO6 ELLIPSE 20.0 #ffcccc 700.67 1062.6 0.0 -622 CLNS1A ELLIPSE 20.0 #ffcccc 69.33 -436.77 0.0 -623 NFKBIL1 ELLIPSE 20.0 #ffcccc 1071.67 1032.96 0.0 -624 IFITM3 ELLIPSE 20.0 #ffcccc 1240.84 -58.69 0.0 -625 IFITM1 ELLIPSE 20.0 #ffcccc 1281.16 -11.07 0.0 -626 SRM ELLIPSE 20.0 #ffcccc 113.89 147.56 0.0 -627 GPX8 ELLIPSE 20.0 #ffcccc 743.84 -765.04 0.0 -628 BTBD3 ELLIPSE 20.0 #ffcccc -57.56 1264.15 0.0 -629 PGM5 ELLIPSE 20.0 #ffcccc 870.48 69.19 0.0 -630 MON2 ELLIPSE 20.0 #ffcccc 573.84 -231.54 0.0 -631 ONECUT2 ELLIPSE 20.0 #ffcccc 1000.17 1353.78 0.0 -632 SYNPO ELLIPSE 20.0 #ffcccc 1244.79 552.53 0.0 -633 CAB39L ELLIPSE 20.0 #ffcccc 3336.78 1040.25 0.0 -634 VARS2 ELLIPSE 20.0 #ffcccc 239.81 509.76 0.0 -635 PBRM1 ELLIPSE 20.0 #ffcccc 651.85 340.97 0.0 -636 CLDN3 ELLIPSE 20.0 #ffcccc -190.06 1816.72 0.0 -637 CLDN2 ELLIPSE 20.0 #ffcccc -264.83 1820.16 0.0 -638 CTSV ELLIPSE 20.0 #ffcccc 1143.06 38.64 0.0 -639 SOCS4 ELLIPSE 20.0 #ffcccc -289.62 507.61 0.0 -640 ELP5 ELLIPSE 20.0 #ffcccc -668.15 -146.43 0.0 -641 CDH18 ELLIPSE 20.0 #ffcccc 1464.48 679.0 0.0 -642 PCBP4 ELLIPSE 20.0 #ffcccc 697.59 1002.21 0.0 -643 SFTPB ELLIPSE 20.0 #ffcccc -1611.26 1541.49 0.0 -644 SFTA3 ELLIPSE 20.0 #ffcccc -1648.18 1608.67 0.0 -645 AMDHD2 ELLIPSE 20.0 #ffcccc -1205.11 1681.73 0.0 -646 NAGK ELLIPSE 20.0 #ffcccc -1279.88 1695.68 0.0 -647 ANKRD36 ELLIPSE 20.0 #ffcccc 148.17 1820.36 0.0 -648 ANKRD36C ELLIPSE 20.0 #ffcccc 71.96 1821.19 0.0 -649 ATP2B1 ELLIPSE 20.0 #ffcccc 780.09 -207.44 0.0 -650 PRRT2 ELLIPSE 20.0 #ffcccc 1432.93 -41.02 0.0 -651 LYNX1 ELLIPSE 20.0 #ffcccc 1783.89 1090.27 0.0 -652 ZNF598 ELLIPSE 20.0 #ffcccc 665.56 709.0 0.0 -653 GLRA1 ELLIPSE 20.0 #ffcccc 1716.95 -850.49 0.0 -654 GABRR3 ELLIPSE 20.0 #ffcccc 1657.88 -896.67 0.0 -655 DNAH11 ELLIPSE 20.0 #ffcccc 1660.73 871.79 0.0 -656 AZI2 ELLIPSE 20.0 #ffcccc 1033.33 -87.28 0.0 -657 CRYAB ELLIPSE 20.0 #ffcccc -30.87 953.53 0.0 -658 HSPB6 ELLIPSE 20.0 #ffcccc -139.23 1136.78 0.0 -659 ERC1 ELLIPSE 20.0 #ffcccc 1094.38 -85.79 0.0 \ No newline at end of file diff --git a/results/plots_paper/Table_1.ods b/results/plots_paper/Table_1.ods new file mode 100644 index 0000000000000000000000000000000000000000..124fc10808408188ba7561b4f36c2b49af1fba3d GIT binary patch literal 55339 zcmb5V1CS;`vnV>;vAtv4wr$(Y}>YXX72vyy?Y~G#EJ9bR&+&Ybaz%} zR(7JYx)r2B!BByKAc24oZL-xutT`j;fPjGh)BjxpvazrMID6Ow4DIc$EsPDFE$nRR zU2RS1>cf8S~#T|EFR8gM{sDO)bn^ z9RF)HCnkDlJ3DJ5Lr41mJ1kRcJ40u{|Ah7XzoBJsXYXSFk6oAlOKSf?`JZ{j`ERHh z8XE(w0sjQG`@iM$KXYPlXbZ6ZANc(5DB3&PnK=TSoc?EC|GSxSayE2!`TxPg|8Hcp zurV|PIMEAPINKQ7JN>`xLPA3R*X#7}`Tx^k|3Nl}wic!UCucfG6VvIWY1<$M#Nb<= z5Wviu06jRkBgLN%%e;QpPz`YUhfL(1-q<8H#p23~yrsihG3MRa=B#T&objl}@&OeV zV@lFL66P)E)LdP39VMGw8*8o9_?fu(mO&+XRGn_NRGj*$A++qU*0W886z-XiJo4Q{ z1Iru^60oDqv5-)BF+vv4N8Z0VXAYoD)fJsD^W!~U33#KnxhnD-p$%J=dcs->5&{Hb zpk)38I|t!(%1Mtfr#>oj4isD;j2ZMS1{Lxc+)>BQuI+@wmLBWv_0-?!1nqjKn0wwB zd%7%+-0u=68)P%x$X|4Ed;FY!)6M>19n>|uidYNG6q$X*pEf_>tBThtNJBt2znU+A z0|NmCfdT>jKQ{2+P2Yc6Bf!~^&fUg3MtRb9lL4{&l^TpqJp#4jLU0^Fcqp6vh#PVxeQf%&k2Vfe$1WFJI)3AhT8=m)ue}uHt zZfE)BToP(;A@UoHY?vIvb}kNa2ItTaGcka4#U&ki&^`=+z44|waEDhD z9nme^!@Sk1=V7~n;*JN_X2y^O<~Q)*QB#t7K;?3ilN(appKnOykxfRqQ;$(IRi~X* zqN=+8?i{3LRo8D3HF9f8JS6QSI=lR%rO}inTfJKcVphJskkiffe5Ju*J`^54_LN@` z+?Z~{Nc&2;pL`!pT8(o!z1UrS4<|+o-X}N>X~t3@n&L-6L221NfUX)(6^(&Exij6A zS@+5EldZa|7UMUwyD)55Fu?vq|Fof3kBf;pvBHXQake*kg@XYl9T~jCOR=aAzdQLi z-fW(_fB))A9ub(?@wGu+Ycy+ovK#RI9P+_XdlrN|zlCtEC`@B*H<-?)l?l?k;|XYC zyLM38*Z|uv9kru_-2K4HVMQH^gnZOa`vzWIQ>VXBU+cXn{24x zePxI$20y41u3e;h2L@KF+ZzVv+*f9T%E>ax$l!^wIla@l0Q%OUESibLLJpf!5ZRH( z9PHVUFe&=FS8y2Hi1_3*_5CXvC{QJ%+y$mS=%0@}E-r*R^!3& zTw*4m6D2xoK@u7wfQhwe$B~3m2aTfOk?(Mqi`CB_BS7KJM9p?lkA z&NaH3&e46CTSKX6EO$io@x>YgQadO!&WS+x0(2@iMH za^n3jDAr{xP+LzzyT^)dpcn>vsj5L7Ihgs3r;R^}vdoP19+ls$yd1^@T2nfi=>jmLez%tj0S@=zeGfAUG%H10+CN1t6pl=DNhv%iM52b zA1v4RY^mtuH(*f@J^rGHpVYP4!IM%(R!|l;)c8h&*O0jhN7=f>#!z_{0l33TLjyMB zM-4k6)xVFXII=Ub21%r#OdVY;VDk0gue#VSsl0^?GG%0fUdw}l`U&?7zyWUR`)%b1 z4`J{#bfJRM&7q06jhT%iB$V*2~-fw zk~NLXr`jmON@hQMGzaE_lYxq)^%Co;IRhhw0d~&t0yRURHDuCHe|WARN0qac zWh#>nh!mBJmm)kj1gfv(+H*`C7@p`uEnoy9o#e~SeYhgFpdkPXCh$fL-Q82u%d%V_ zPwB3&GI80Y&F{i-Q{943u+8tRW)=pT8xu1{jLV8V6W}^iE`YxpFYgc}>duEAtitE* z#|ylKE(#wUa=o)X8Wg_JgxwTjkf!7!v*SJ_jxx9RyDxp4^1UL$5*Lq@|K`Sh^7=vd zof`YTA|v?D;vc+1)E_F6awzT3Wll&o#wb3^E#u^TX%YXW#PC##@oq4?Gw=?_|Kky% z(QKN4eC-OXOZ|W(@E7gBj-2U zpY`2qcT_T~$gs^-f}R<+uyj2$H-nrWR6kKSmr3&H*xv-j5sEV1w`7f=@wl?jydXAc z_yW!>vM)b9LYCBhY9n8R9-fKTW-FAeVGR`>lqCryyFO_oi|m)7)+y#VcJfCFmqf}u zo$c=F;`{~Vad9tzLUzn7O^Zf$KVrpPu0a>x4@b2x8ZZobeej)eudj(IX2Yp&GbQh> z{8!@9z3-Qx_&*T?!Xi@Aa;I0UfR|wKMd` zxu!p3-k14tYgG^|N;99knlg9Y`Sc-L#V_l6_(@o!sQokzOLN=T&KR-VMwsf7TRmov< zrdPOEZvqs8!X+J(6|m4A_{z6OH|F?%z93q0z;AT9E%*^?O?Ns+HxdT)w5UZ;U|q)@ zf)0y-aE-R009!x1aB4rm{|Ph3P0*qAzkq;h3I33%dLJXl?hFbwLDyX--)uV#$~>eo9FLqA;bF5|iV;o~1A90d2>rn~eux@bNe3 znyS@@RR^S>`(-X7^T_Q4G`?4yrQ5=YpELyb2Mw>c^!U*Zw`FC0y!G$dZwzqhd18pt zLuL&seF+D#BP{y_ODL%s@yTP#q2Nf1nBoMb3we!T2Z?SUiDsEGS#6&}?hg$ZQW-L| zRxMf?)UzhuhCc5@3qGO2EzMFF;0Pd|(Hku`vsxO!scRa@8ea;I)xub~$M$4N5h>59 z#ZIF|E{1VT`FDc0sMRQYBAY?y$&4cg^#-J=11h(U8t>mG1V6gk=t)1E;D&yOQx%91J?z2lA;#cR0 zT_l@iUrD;}M$h+TtE0;^tI4r&HWye(c>#6`osb@)gL-e8D%wIWNTDUQj@rQ}`GQT* zGtm+_sdm#n`h7vGm#=IQ4X{=Z_SQa1IqPxq_*G4^%FZ})G=rxk7CMkl7raBw0*c02 zR>#}CDsOd-I(MG(#~TD`RMj>^IyFeqoG$~A{bdK|gz{lF%zyG)O5=LsM2^)$p`N0R zSyMBaq!z;Grj2iJISdcRKs&n|!d^tIJdJ@HpzEmaj6{RiiX_6HRLxV_3TG&{w`!fSvy%2RIz4pHPtu3>k9f8}a7Ukb`tG^99a^~*WLi{O z{&YDTLz*B}E?8xK1yudwud%1@A?&Gx8Swq#)&{K#sN|LqC+yPV%eN1PME^M5iwD)I=9reUqzyGpF@pP{rCt+fvX{Hm!;Og{bgl zAf-ddA`}CMd|#02I&_KbVtFQ({Bo0gR_dcN{5g8wz>aR58@6Sq-@&JChebgH1I!F8 zzjmh;2?)-06coG_D@m!2(imO1Zb8nFPQUem$wKT)glK>QY7W8mrA~@WQ%TslX{RC3D3s+g|(&&IK-chGUE ztVBzeebOz>{>F2xu^;yhr^)xP%Q&ZLpWzgzwvNwDVY9ZX@5`>LaIS1);3VGp2)64GXL5aL82L@M= z7OtjR*?~ujGl!kxMQTTC#vZny9!bnc9<-B}?D1s}M*;+9Rm2NVPOTx!r8x6fgSL@G)hUp957GZ2?^gEpoNDZz-C^w#`yZ2Zv+&>mxV zS}Pcr1{474Nk#kJ-yt>FKkwKd$3CE|-G$@-OlL>f7qCL3q^^G2r+IpudG>r&+qebck8)0 z(t{&tW&iDRQO3{r6D=YXQK$72kP3Fn0POQFlYHdutI{=YokBY&*KzQgXSpHLluSn; zz~QekUCT&7qmcc9s)3xSE;QFFO1$`py7jS(uvM!bXKlA&qa{XvpUMl2LeqJ8A^JYn2U?5G$ka#HSn*s7cSf*3=ehbMFU8wUJ1tI}4mh=$Y8O0nc zYiBPu)f8oZ7|&H(p240?Ijanrb=xkNr|10TX3rfB=PTgU<&vCMcsJOG)!Dt2x1*>? z^BmLb&{kU91#Xj(3gUG>aaP|~+z4e7@#(90b|F~E-h^<0(WsGh9G7t# zaq(J@gDCNxFbcGmzU=1hz4hK00oQDyB5y78OdgXSn3NFZf`8XLL>p)pr^_vzWeWu% z$2JbYnbC02oy!bGA~wRE3kd@}A8pH}T4o2I!>#t)xI~+O*%%;}{@vc3nZ~7RZUBEf zxov8W#cAy3PHc{JP7@O$5>0O}^S$~N&B7o)#BKX~Z!}{q_tg3GVDNiVbG@bD+cghM z`O~5}|0w9J^$+Z08|ICA}>U1C_<(OZXX?F5?ZI@5&>-c8Th)kV<(D!w3_lua?Ee zw=WrV#!@M0sd`v-_agqTcvzkz2AmmQy_J1DVG*K!DlDg zlse~)Pa4(rbia*CZ?3;mb7eoE|H+0nGx5Zi|J6v8RsN@J=sz_mCxElFg{|3tExWI^ zcAYjj5Pkdlh=wj@BjKQwnW1nWxjO{<*@E9nh&Mr~#}ma98IS7t*9GVb+DrVo-Posv z`x~FGEuXI~TMkYpnfftc#yJX)TJwFCpfTdxmxN7RwJ|lXCuc+GTlj6yoFjEKp3AYp z6OD zEj75Ui*?)9Cyn3jA|SsaZ0OjgBkDH;RXREa7<`+w40qe(j7P(XA%t@T4d(0XeJIrm zyd%OXmXfm$+6ef;{{oc};UAG7LHXe~d)BB)kq@~MX1;r=s;jm*`cQlWfCi;Sc-n(^ zYH2WU^-G+iO<=Wg3mKztyKz}N3=%;?w1gm^%UEOu+@6~Ko5$l&zc@_%fd$tfE`Uj_ zMWU72@^PTfL6dxb)#0?I<0s_3(v`U4G~Yls`G3}8%Tr2R+ z7Hf}2{6PN`+a#LC^duDlwC0R8vIb1!wfj+xi*@en^nou&4szl6lZ${U^U_Dm;TDdG z&6IgDJ9{et<(n7To&R|M0oEeO2=F>rs!WzHxg} zJE&#|u}%!9kqnUl;!R@iSHEp=z&Px$u_1Qvet&Ao^?bo`0(lOLM1f)1q_ql25+NzcRg2U;W3uQ9YSTU(3^wY$nBpl=rX}h|8UCa9HGD zmB&9G2#eSh%~amveQel%>EqW@ua=npkSKy83ayy3#1}`pMtPWJFX*}V8y;82LK;*F z(av@Gp{IPND6^IGcI5r8`L-_{w)_D!Gij-R^j+JP$A%TH*6;ty1mQYd7GcaRYF)Y1 zp0%{I<>|frD8A(7{oTvk=Df|GBrpHX3<`&p)B0e2G5M>au79z`NdBgoutVP+7r#rx z3U2vh$ud^T=du?tJs5&*aD_PZ%H_V_T`pYaUDqzi{q%GZa? zkZZkr{^CHa;KP0=L~cF{jMe9ft9k(2qDLHypUHK5evTPoXV7Lf7vNGRk)xM0({92) zlIe}ViR)!6e|6Wvvhhda(+k+QftJ*E??a(>Tj(OpaMfJ$z1RBjdSMMD36XzBTZ+l1 zXBl7P(9>sYMeER^$1M7*f^|V_^sdR)d8{GX1HfzHv{{H&WdhMB@BQz%9gwZ}PsIm^ z2c`%s5(nYe(_i3A{8h?>aC4-dIoXk$Ze~Gut8~f5D)GVt^XG9YBi2__z2Y)RjM!!a zr|GdvJ>`7H%`psr%PQOTI#Dx%!uN4A)M%xS&(iO|T=YDC7oG(;5D+`j|8~*;d)Mi? zPQ@d>4G8Ez{XaWID&{UWMz)3))=u=!{~M&Uw>67UkQ0Z4{{5fQDV(H)h!PMGaQVN! z4*9Rr3Uq|5p9%y7@}(f7A_@))4grG(gM^I+1Az>WgpCA)hKdG;KnR0D28+vxibIBk z#{f^nhD}6?PRdRQ2Tq0#O^S`ihy%lfhfIh^KuL(rMg-4JhC%wT(Xdi6a?3UTmD zGx00X3aW7nO0tS;a>yF;D47Y-{uX7x5uhiOU?UUZVO8R#RN!Y2;1iG(;!+c&)f8tn zl;to}TyN&{^)!W?yjoQwipErZ>yBV7z* z+)bjqEQ7sW61>g){Q~3s?IHp_Qv+=>!dwcX-AWU@Lqo$tVp1X#GLoZ1;^X2o5+ah5 zlS9%f!gCr^bBc5Fv!e@IGYTqF$~yAu`^wWoN^+7Lvcqcg<0=c%TMMI`ijx{kGg`}2 zn=7)rN)vj@le?<3dh2tFi;GKZnkyPRn`=rN>gqchE1Q~{8d^G=J9;`>8hbjLySlp4 zYX))}M~a$<3R?e^wvQHfOjWcFR<{pVbx)P|%(rw8_w;wx3@mjFPPC4%_0H|IPw)3E z91hf^k2d5?w3iI`w9NOE&koc~40bLLRIiP-z{$)?i}t;?_W_{Y@F}R-)~P`@6B8s ztUc{dy_~Im+-;woogH64-rQZDKYl!3AKl&Fy+2+&Jv}|Vyg$FaJbnCqe|h-(@$~)u z?Z6I93(T`;K|vXDZs8I0JVFr1hY zVo3=}@Y8ZBRZ>&{)!{1kHx7d&w{Bm#JcFWw0PWY)gF3Lsi?H2|jVx$_l%m22Wi{93 z=WWX@Wqx)cZj3MoeAx`o-xn>foaap|+Fx8{t42m#`hw&NIg8lf$sYXtx=5*RFMJ}W zo1XYBI}N@+H7_C1-vo;&a@}WNrDHakEC&q`j>O{HtqsKd?=Eq!wQeV%Rx>X%=j|Fx zUPFu7(5dWDv|?aqh-bUzw=9W!UX_A zK2_ipFR2N;HW}_DD7(H(sARpx`NjEPK28Ql;I$pO)mt;!K(%NX+85yM8oo|F@BtS_ z0}5q_r_+PocrrGZ*rYx(sn4D04|N&4B^_T1baUby2@SoX9KtYt61Dcf0uJ7~P;7^- zUF197su5VpbMV|OZ1~ry7sXQ;zbU{EF~yQa{WC8H!x0qor;;$mx^r)oy}hbhL~u(V z5l?<`dc(q+t!yyGvgX4XVxEVR5Ls6uoVX0WillTg zMvKF3Zc}C${*9@wk!Ml9zA_0!R&VT$yj~$kBGsLI6K9?hBpNP0ziI}gLw@m+B~~jr zY)_oqDe+4CPBEo0HBCHY0AUEDpXQ4=Y)fVtkjg!Y70PU8a4^K{rdyEVQ9M)^3Ts8Q zL0Mw)ZxCd7AfrXi=744j!ZOEI%Vobx0jC(DlsQ~3B>&++vo_v(hEzdL%8x?dK6>4- zq*a87evN@#+ND&OpYr-Flmv}6MP3T(M2$9PvV%ig?q@I^SjKeJAz(JrM@;Gm5C3t( zMgb&H%uL_>`7z`6za;!1*^S{Gcg2X&C~0zGYSl^YZiANC@*e8V}Ge0HSNUZuS87-_efZXWTTuv66p~@NCou&S( z{1KI+d^e3hy+Vp~b`YG29jRQv)OXZOrWCw9?4z8n)HOf0pVQR8KwBMUsltU(h7cCu zJ0}(H&ceWVB*H#^Nfas3W5@hhP!h*A>uzEKdr^2v*C`Fg8Q?6g|SFxDk3J<#>dZG{26Hq4Yv)py!z1gS8}TJkpfLPBKo{{ojaB@ zys|DJf`Hx280B$bgStHNa6IL2V-=_1^9XQ9TV+!;G{|+Pd;WMO(8E?zhKudg&z#ub zNJ$mC!}5C3{6+S;@6vTzX=<1(2=I z^h8WI$6<1QVj{*VsGwkoN*N-x@eCJta)#Ir2Q8yIdjPzWv5^Kw&SO}=9643f?ltZa z*4iuy?Bjs0G`?tYZ#>LhZTy`nloY{y`4Lg%b2-~>k0bI(kLbpu!igA_g^~`?qnlo# zE%aBNXd%a8kk8Vqh>AjCFS&pyX6O33V2&a!kSIxIN;MfW=?A&%b(v(GQ-N+F-QFcz zK!=w)G%EGK+mY${`qj%)AA3>6$RPq>!1Y#}BAs~c@<+o6*wR@daAvVc>xTiqN4H=J z)AERbTrwj@O5O06{ESZWMFJ9($sc0q(z4-NAkO2BCkWB=4f4+*SOh@EQ<>|sMUd_% zG-(YTl`zBVoUrgw5-1#h^2*8A)fJ72jFIQLLLxu}l!HBpn2G4?;mUzc@bs_9Y9&n$ zD#H@XVoXoUCH=qyMbH@eK7}#uaFO6dB4H4ZQM*30{SUHn-Sc5<3w5Z3x{npJVv@LmQ)JJ}Y@w^0&S2q{V-rpV($dNNwXl4CMvQo>m*}pd zON-bQ^p|Sh)Xf{*Jno48TE)h?RhyGgkZc1^nG&fO+f=7D{o4xbTSD^36v#Jmjp^%$ z?3`)Hw3hl%L&7==hk<;9;Uz;QFG-(`D8jNJ{0ApC;Z9)LgDKX_dbA%^5p78-JcLbZ zu>A)jJB6Vs6v=pyL2^(+@(_2U1WL+A<%&ZrJAPaQzWH$XPfKoe@h%#jKTxx3@+)Uqt8&j;IrJzVaWK4%5P-Ra?wPU<}N9T9^j%k z=6z`~3rB9&!OBG~>QZ4QB=}@BK7cymFWdDwq+a{msHN30U2MqfH)^|Pf0|^bJIAtH z-WzIRa=r)R@b*)ur)|kr65!!xP5%+ zeK*jjvYO?ymA>EN5kSjuqd#HQ6%EN1`bM5a-7jEYuA-x# zPQTb`zp&!^`KwmCGyE3vEX&61h{wuirDqKmj8bO5;%J_*5YoAfH?lrX&vRq1o`Y-l zWvU-S%K1jV{ne7>*qVV0F3L zmT{`G`DkUot^_jDs8Sj%z~wh2C%xAOPHY7Ggvd$aa%(pf@>y)7HRufgYVDKDi&3>1 z7Rq#&P0G!3F)L9HiSQX~BW&-QPfCo8L-6>L-(ceyM(tp;H(H%Xy#rsH4+>O&k`t?Urt2fd$LRRz$gf_AC< zunx7qa=a_%PiRz;=Y7g~xp*l8En6``>V@{GvtV7u;__yCnj z8rnpPU=;q)&aeE~3Nfu`#q$zZPm`Dk>JEe$gHMh~xPhe6JvC?Xsqg)*FqOS|SO^`_ z=T-RQ3=4gXpmRQCNl4C<=}5I~^7jRAU5Y;DGTGufu%9nJJ`Kr!tYGvg^opLTy>|A- zmfzqJLS^Jl`UhrA&aYK~LjRa;)ybztE1j?AXo@nt03!ZM$WREl?GJ@COQeVDpo}Cy z^jqSnrpjUjQV!i_Ab2@5?9f}Lhc%oL<|TED*l5ZQPGnYE3_N_pmo^_U1TqlmrnL`{GQTYKW<^k`_}axURqUsj#@!@;YH8gW>QQa$-uZOL_>y#&yhfYEFStW;=yKpfn;q{&5ZKQSjghO6p zF8Vu(@3up};o)w~=KRhr_xNY#JdKQ$*$%JnLuU4w{<;XS=Xif&>HQUB_f(Y;A_w;N z@-PF4LOw5T2I6l@@$6)~&AMK8YAmDZh_pJPe1n;VC+qq5Pb&*(Sp9WIn6!2ybK?Y2 z7rHIJ<4Lv-Ook1tM<(l{TNI z8u&!4MG~%6yLsI4;Ydim44+^3q7CGEUW1Bf#3g!Zc6l`uM2rTvuG({yK*n+n;v=s8 zh1oq$u0#FRG-b4bJ4nY`KPq3~KxI{MsDyurF;{JNe&D4It(E&0u^bx-3P{sND%-n& z2MW#O@_-Tl_TjC;x*|ix<}XYV^h9!By6jAYTyk!LA~!Wx6m;$amg{E9VRNpPV@Qv} zj9+OeK=YMa*4RTTTG)YO_3c_G;yOm8OB2du3rXZrO(2!MEe9OWE~v(T`l1>>+F}o-2+`Z6kdfm zV#%_XY|3kvsm zd|oz69*GD4CwO$THR7^=hwx|7aDh@mJi1UVjn2N_^si@_*Ju#h$04GVYaH6gI72ED zd3b@y!(li6{Mccwdy2X&=_3@c5A10|y?w)=6*SJ~L?3u`&Wtt0IQw^Nws1x7wjt~_ z2R#&CV#6wV=k~3%SE*2UndI3eSksTiJ8NNyzWWDvjTL>Q8)T>`BCF$rxM!HJ@deDe zCzaqyM}tV{kc(^@78TDWkR{fR1LC+%6ZDUUD|3j54XT`S%wrf^Y)3#N(vf~}g#;cR zRUOl-!XI{TO7dCtk!ePd4# ziDJzHjblp*NMh7{e>}(pqVv=oqr;6&GIH=>AGKSi{G7I-_svf5HzzuzyUwgcRr}!z z_AOdu$dcEI_cF>l*#7gok2umC3agTHkZg0b>e9DguDp}Adrj3nMD(_v>@u&@-Fe9tm8mMMnoI8ClCeQgX$wf`-?x>bV^$u8oou=lCn$kRV8&8VDceZX6f~%L* z$YUnSKegf${sIROIgW3j3r$(CnWW_;FggMuEFr`n#3v*m@t9(H)ScjgC_vQ5RgOz& z|JkCrGzz@lVF32ZDsTvI>A*y(g+7tX5>Y%(5F)t%0;h5y>sU^~!dkr6 z+IHN-`Ifn|bmj|HCzys-D1`N}u;68)R7mWz8(U4kC<1(cr|;ZV+oOICD zP$&*LaD3fqa(^J=WLso|UE_rfYm-nZG{y&zdfYR;XoD;U&79KD>o9# zQcm;@gl?TRhBKiN9r*}ui7;RZ*X154$K`gC`d0YN9o%1@U0ONwg?FX7S`3~9>)V`? zsM-j8fzEIw^g_5g+kC?Jl7Aqv!Y`Zjx+7f9a2V7@R3dElgD01(5h<32fR_J7TyF$o zH6(j+*K7$CQ3Pg2!iIC>Xiiu6L8X}IuXtc2l$tNDz#((nB~#pvK=1NRxSko)1^>60 zIY&snLl&(~3fHAod;g-!2dla*!vkIF ztfDR!Ni0!Ja~TQnC3_1@M;jt?0W=CTT%qVjOz!`ZEWNSZlYz{vp-x3-W5Cv84RD%a z#Lkq~X{?Rt4e1nwsV1c=tN@J5uo27@V>KIO?b14Bl>buAdjuwyLR~F-1qmi@Qblq0 zXVb~T7c}mg(ZFyomTB(#mQQrSu!fGdA}Rk!eY?0Ala5V^sML-SNlAdm8G$S)FHKF%y2KTP%D#sq+uI8pGjL| zvy%CMx|4tM#D04DmSX>xGoomvI|XF!`@mo6!8ls-99k|{%-$75$U;upIJ zw`UDg0GZZ}sBMRPy$s$mhzs$to`^bH&*d>|7uxp$r5ic#!;IUpp40P+&(fcPhkCMh zysKl@wv?P3N~qE??sZg@s2{HtTWG}GSp(}FQ8caM=QgU7B&I8Y~p z&@C&~rv@heBr=VipM%1klz|6fQIT!ioAc#ML{y}KgI~%nqB7XCzGDUZHv8yG-8`Ro zM46nUle`d0Cjud5f5TAGdPcway(V_)gJ&`N6T#NbDdQ?(a(ft*38en9Y|}jKJ|V6X zK*@NF^xS~pBkG7yEjXMis&&&ov|QuH zs;R$aef4I7t2ZQUH?ub5k)@5lvpBrlPAau!{?UTp%|;&`XOsi;b6nI?tLQQBh{X~YPPW}|<#hdZ~CyZ$2M@&`lIV=bN@vOSItnqh|&lkT>~ zW&O#{-8k5^93d|4tssmF^stR>%}eFeWP*7I`LwV&6b+0c)Xe1*)&if*UNBozA251V zUA(p;*x>c)lqFOFlRPo_9-Hq{laL>5aU;E#PcBbKL8yMi;$OlaTT;`ah4%%q&Z2oI zAGqW5zgfYCUIO5i1K=evQoU3K3)z*lMH5jJ{9q`IF;PlL1^R>6wKi`jtkr_D)3=9A z1*ZzkL6*Rg5~AWc8O}H3|9zLJ+NN$32+gDaRTJqyrQLpVskXPI&?qgA+hp%@>+nE1 zezWV9k?*wL{d1{S`&Ol9kRVO7OHBgGN6ojhpj5F5Vfw7c`u@9?<>#6jB!|xLl@^b} ziIFpR^CX|`9CA?SzE&!@n)K%_3#ER%E57}v+c?OI7(Pr~=>U;3Qd!Q7QOL5(O;P=V zt!(#g=wO^iYeX4H$AB!|U@Ztag&KQvv5z%@OMy8lhbThY@yUI6vy<8i6394ay$MFFXbocn9m zq7)i7aWI{N$hqrGBedh_rSt6GR{5_X)OoXSqIa56S&);RT)z>-!JYN(P7kvc_yI#n z4hKyOVpxX+VD27<8<2b_7Qqze-Dnkqa~%#rdJ&C#t3_~-iVT%K$(Xw!pm*{M8J|M& z`MjYaF$k@-$c>c{j~|4I>h}bKNMUM=^iT+$Y;s%h!*YYv$!*z>fZULr2LHE{EO68?X!+OaUPRTRBgoxn1aoru9Iyj>@|k!o35TPK zEhwsDFks2^FcPVTJf*I+%}=2{B*zHjdNgon6yVCxvCFYMYt{G9Yy_dNi#Y2;%ISH6 zPSD?3+<=#lk?R+1sU<8B#{~D|UYn`iifnHDkO%(f=G~aGUCTDhUDE{7LJ$-RO;KM$ zi`UTikJ2}V+Z$9g*u$Wj9E;%s^e{|X>^c7?(ge7|E+81mSG_6Wdog%OT#2mcx*X+Dqe_T!t?urP>hMHpu+$_AuU)0UEjjMG1|oz zCSL;=v!r*SAnqd)Cc9>myp{Js-q~M*`4Zi%@+_eQz-Lk6CQTra(^yrTb(I)@+!gVx z9Gj3U)X^!}AgkuOo(ITUYne5+`AuI$sfJRM$JzWa`(7RCe?L-kQs}&&gNC){2$iN& zWLxp9k9cBhGCDl0&G64YkS8mKGJ8EftegNA{XDGNs&^at>aJH0f8w_v?>Ia)KJh0F z^%~Zn#PxQ9#83ABw0Ow#d7b7#d>2PFwsm7Jx78`@^6uVJD3d$9Xi9Clh(eStUz3-(;v8izy3lyjgJAC+XUxq_8|)>UTE3KzXZV zY%6bKUwbbV@qzE)7zf7f1B7u>&8F&cg?GH-5C66-k`DH70&c7l&~(C^s3e{=emZ>6 z*lYD)l(LHKYsyfCvq1`9>Jrd}GRmGNhWCSw|HY9E51t{b*2vcbPd+q<@@p$k>-SK0 z(L!`?!^%&q9xH-T2z{xDBSf7(kYAfgXWNT~#1v#w#1(_{Z*Y37m{PzI;t3}laYa30 z6$Xy`L&N*eS9LP^VlyoVQXQLtmPS=(x0b+njaVIoL#r$ z-A||zH!pjwU9~klS~;evk!pgneXwc#Znq%lUh?bsngN7Qg7XHfCc0Fz7&`hT+ae;3 z+K%i!XpHvSLvBL+5CxU@Wq4ha6!NL^Fa2IH$m36m=w+ij5q3sr2OV8y+`iL-C~$()oN2=|3jP5Cd&61RCTy{P#<6rz^&Lnf|73DmA9y7ZhlYjSe7YVuXS zU#IEB_JYoBQ+ja;)TewW5yD4B=|bgMaqMq#%2ToiT{-=b>6c?j=4t1kqI~x7jU@0=l(n@f;hYp>*!aiNWrgkMEBFoEP3t7;k0_WCvX&BsX0_T z@*syTQEHR??yAaA_jzylqiDkd@yiu@cpqEDNh4giunX4GB|P%lHNG});UCUkwqs!> zg7(kpjdwmhau~~%!+KHp&|=_m>-HF?J8V0i1kQp)d)|CmjQdxS5OSTG8$VDdYmv2z z4Q!p7bJ*F|2yTF7L7Ssgr<(5YzyERey-_dJz@i)#3LURktJ*YC!a#Rf4ip&3kbh+9 zyWjU!YOJg+%&}UC(8bNI?eb*<5^gcEGZtR^-hvbh&G!r!!s5<~EE(k-q**a_9=BwZ z_i52!65K*CizyJpv?hRIgE-9|hj?M|Nd-eO#Lermu8qkc6&Q!9XwgV2KatQC-5L?Y z$`lG^C=}CtU@zLFzot#j{rpFl?eaW}sLx#-CFPk$Geb;S(w!$10mOd#E^9MH3gx2c_2ArMe*OkgcTT&0u!W{cC6BT-*(SsZ;GnY^ zW1chRT^z_~2y^F@UtnXnRPoK@tL~!qef(8S98`8ye-ep}EC!#RkdviQ%w!jT)*Q6e zN<`D^IVBpY)%{Sci(`D_3`yU-%JY2Ql{IDFQH{?q6r&$$Q>ax44h^krHy14@a)wWi zdAP`ttp25gWe3Q$B741x%TdRog-W|bgK$ae`8Y)kX{K&p)lohi^SqJAi;Q|Nf=>OO zr@kUGA9~7%8}pMzLwQy}zhLdm{E3ac=W@2KhJroh6<;k5J~l>Lk|bx%^LUQzgcEHN zVE$uVZENvX<6x)1AsPG^CS>)D`VPDUYiLZ?4qBm4^w$)`&;-|exu58BPd#jUYIiC? zN>i0wVRnMYFX3NcQ2gpA8xT3m{w6K6E_?m!2CZUFu0TJ0ahY5$S9N<{YWmUUvoDFV z`rv(o)Ff#?jX<7~k85$+lw0%u-24Hl@Xu!-H?tT?RqI7q^@{ZUWj!ttzmel}rEg9M z0l>?*vbnx#^xc~Ik6Kzt;k@^{bz|ZFgl`MwQVvC8!AxQFO62RMFN;q-5)v~pEsRA$ zcL4pu4Tmu+O!`CpFfYLP@p5suMPKi?(oA&uy~OUallfyaKLlT=pCC~^QurRmDLfFE1k2OsT4M!8_EAB87I z!{Ue-jLV7NO5Fc;MA9up;1p|P?D6+z)tT7U_0>!|YpyB@)+wV4BID`JOmIND7=8DH z8xcX#86&0W)lH;BO?ekf^TAp@fDo7D;-A#03wsc3TCPvyF@{RDJ9@e38SCWfp-=g@;U;InTue?V+WWr% zr9fK0e4KmJ7q($Jm{Dl4d)f@yQPwtmTCC)t)>WAv^4yrq7iRSl^E_~lPN)0AHirOJ zOP*=*EZ_o=mf-IleckLX0u+H^codPS3tjX@q;vWyTwi9VKhG2rTyk=~@54FffaRn~ zM0G8RK&qu~73S}wgD#4?0&MD10~Kp&n$A?aCTL)4a9}|BWlSrI;cP=l>nN{6-#QFe zp`!gU#+#<>+uDcnpGb|YUJv=-Qp#q^EX@2%o5c!PxggS$zsY?49M#2C7yD_ri>ge>4;XL&SldEM zm7a1y^dK?H5a=;q{rvi<7ijejB&zSP4*x}gVh3fCK5BwUCX?9+>BreUlckaT5SJ9+ zS^`uTeUbnaktn3D0<$pjCFaw$OhdBJA|w*E$$nSm*$zOF_nqwYRpsd}|3siL0Ix1R zSb7KortT%vEvO(%$EZYgSK%5RW=9kxiU8G(&#e$LLS4O304jlIl0~30dAbyV${}LB zo*cfb#dX@{%5k#YJy#>M(miViXwjm9mJ|=cf8zY#(Llc7Or}i~JVP z1h*WnO^x8RNu+O}66J^Hxk#VFXG}d$fWpQ(a2@6(<(%7rN}RdL4__NiwS3PSC`?aU zW|1iB2M!#=)4hBL7ci3o^%mdbSpmg4(|}mk_83*K6sRnk|GAdAi|I1*GSkI+N0%RBN2BNWNrag8)WinO=vgQg;x%-+Rjz-c;*v@*}B)mMRi6y|81BAS^( zc|b0JzPwHD1(msW`g=@dWwG-CRDEK-&ULPOk&nLA-Xc-8k_CVJ)b;=uA`A-D%3KO* z`(EO4aZfn20bgIKsGtdfn)1QrEuS*qrXWzZmx5+jmXDkXMbezQ74Eu0b1KzAagge* zHfD zXKN*y>gj|1b;JDC8>LlT;H*kkdXgJC`bvpw7G{(r61CI)c;#m4kIxsVBAcB1z+#&4 zZK4evu!(e(5q+m@P&`YzRW@h=>$VQqzyy|9VQfHFE%QCFZV5Cw#h@c#;=nNIh?PVo z(=r*`=9>N;Vb@Gvzk;`N|H2OdToc-R>?P7dzaFK?1npQo`3n`3`zvdpVQTA7Q!!a; zArw!ZcG-;pWf7_s)3Eu>0fRDlYE!O~*5jV6I9WWOpfkCDY}4wg`J{QU6K~f|S19Ha z<2ZlR`^qY)oBokvr5-e+6hFeA(B4yPU^D4Eb2mWATyi73fZM20kQF7Np_$t0E3YXg znpPYIZjAyDT5+6S5vPAI#PPwwiuro@LJ|6H#pE1zX>b^^#CIy@aMP>6FhdcV!*QPx zow+58+Z@_^^mF?N7OcL3v*?nVbO_X@z8|Q9MJlKj-$k`@4V!oBhjg5AieD*?@=Nxo z$yJ8Y2T0+^p(I8A3ofK5jh7`7l&%LYX`qX~@AUPdM6nXfcw?M;NT-;{YDv;6&W3wppn&BdnTR|sDD0TD;xM;ECzmm(@ArP`Eh;U z(~t9vf(t_Lm)btAuZ$npS1Kd~>6*e<62SB=(s=A7mhfgAbrC(YM6qk1_@!a|CcB{1 zb>3$6u@chVp9{x?LdhcxWG8xr%n2(T;Fq8JHWb+N*YjyaWyDiXZb4f6jUqEM8~P#)Nw|C zT5o^U&FLO;qU)aMJ7a%ED2Gn}#P#IDI{hmE)ES#hVmX(%Er1<1!~|s*IoyVdD+I3u zwDZgXnK(nA3NiQC9ywreTX$Ae1?F*)ZS^^pL_F{vm4Y8E*T&+2t0xpQ{Od1bc>JT+3$+9SH$38Qep}VY`})2l-%+lP#2Dqj zqdvF-w4_X#>)Y}OJ(Re<<4V4<&*BGED}GM7jxlkIq`h6;i5W44m&WK>4*->nJ=-$o zFgglOG?N{Ubp*;fts=4~Mu{TaVELX=&tZ=lX8Ae!MOXD=+HSr0o*CH`mkW;rH8~6=}ji-ja*uD^@i@F)!9UI=k$Cf~;zS-!go zVj{JY8(Sn}k2f-5^H=cs%e0JQ!W@2o8;-~u9--pq`HS^jPuqv z$fjinMF<|=xobRU!Q#HFR=e<3Y!drTTovR;N6wdaH5J*pdy%=BLlt|d_$I5PUZtIB7!xBA>k{q6A zK-EWnPKl(Q)6j%k(T_WbjiTw6iA)ECEZF3PK~6kSq(N($n<;%wL_;3Q#g7BGoKwWi zVY{6`FD~1C0~RH!yMjfcQt>RzO?2iOr1X=pd^f-jCsQC%VORMPhKW8VDD7fG89HNU zLg#pH4g!U{l-f6;hpWi0X$Zl&NUTRQE7gYwic%ajD&nOX6E6g)Qx5tm@h~i_R&?8d zKw%$+k!-VgiTXR1pR!04Ln#hoyd>F&hljgGV$cm2u#R^*g)4%YDs;ng&POLWlI<>Y zcF-89V-)nEac89?R#sD5lKReVs{%d9UJ`mZyEGg|G5DLj22WV%92dGSE)u-~n#WvXH*P)8>C$Z|Fi2Cf2(xX;DQHjz!9~FQy*sj{Y z|M-3lI?c6`Dnv*lxj{(|Zwl0bS|*2_^|g zQ6~Tv4!DOEzud5oLS?7zmbn8%PwS278PQ6p>O(blmic}e$_jHd8C73>E1$FP1f@aT zvMR_ixjt0&QQvvh1hhme=o`iO;-s#vXcH}rv;vAWm`!%~u|Qk?dgMBg(KXi_vCd>^ zm!=^zai(hn$`r7U(pD`mC+_}*j_XTB-h*|sDWnqRHmA}`qQcbqwg*^em3oFOfv7%> z%j~`3E}5*`Z1omdVTEKt$z&-7D%IiZE#b}yC6dgN@scAN=Qwq)^dQ!afT4Gp#8oqn;aqTocT%QqpB`6c>V?)Q1!_J0>f4heIrpzls z=Qiz`ekVUX{P>D1P%%Ap>P5IVpKMul6UrxtPP+}d6`^6|8?bm4l&m66Ben)g$a>y% z&?rZ(G_IaYP8%)^)x(;AnrS9>Y3Q^{BHdd)4JYRN#@)c}`80HX6Wret9=@s-hAdbS zI;{yX%}M!uSaA~na@nK8R<***QGKt<*mJ|YyI^oW_R2WdhGxR6G`%{}99*=!(sRJ8 zlNVx0Cs2=>_<9bn%v4hSiqRaM(HyVE^unyZr)79Mr&qx0>zrPM)n{yOD{CR`;7@}&`1Y|ClNKks4&
l%tD^bQ@*!~@fijQZKeAWmwUNCR z5K!pg*eQ|l)+&2U(uh=$gTcna_vZHY9DNBIM&}2=z0!mdHQEH_BYTamhHGP6Yom%j z!gFkX_x;_US<=<9p*7^cQ8h&b^35Oh4C7N-7^e5?HBAp+tW56J|65o_Bnpq~-D@tn z$1TAgs3&rJ_ZnLRb>n-!vy!Y#AxpO*B`48itZsU*Pg;Om{l{LaS24Q+Z}oAK!@@F6 zD22-DL(GLli$xW6{VN^U=R^l1o${u+LHSWgCDOv}$TuVoU<2dp^JSMh0>wH`IYM6$IedBR6ywymexsKaI(x39`ZuZ}6C-r>gs?f&g`HxKeJ0hakzYoa4xS*!17 zj4;t5eQ<%{^Kqq8Aa)>0CXDMlW0#8vbr{!I#Mmq#$ZmjZE`G36+RMedk7At<0_%K$ z4s-|zOG`@|NrcJm1P+WQs!uDa;@bgWq{!Wy` zcA^#ZNMi=Bx!5fe{^}y_|Ji_Z(kf^Uino@iLYhtyGxY_05F6|H0eSwnPQWSqCZhUM z?b6a$GkoL|w@B(W?KWT6GKpwdl&FP#2ZIuY!_(Yya12d{!7YuF8(PUt%q^w~k@xP& zM^$J-MEzH_(x43(m_UG97RkBs?BiQvnM@}B4`=iUJ0CdLQ#vAt0Cx=0JBGvy`t)OF z8oEhkG8b{xt7=Se0lX5LGKcHI$EggZT*L+JmA3kniD`+tQad^XoytLqUo$d1C|xEK zM8~C~mn z%ls@rl_EnGkVA>XZtbIxhQ)9CkjC4@__y*H({F@5gJuGahYQG}K*2!XXBUup|NecB zdutt@g@{f4M(0e<`4EyKg*bX*iVA~z8f{M)@0+++*XoPr-x#^up;SS$d>K)VO$}nw zfVv=QKrO``K)Ikq5ukb;p~eK)J%I-*)jKARm0;)? z?cfAkkNL3{hb<*W@)9M4N}X{q(e~lC0Y$8_UG>3|sL!KlqEgI5Tq3R?^-;S;USq_I+3rV4?InT0^H&PQHts}E9a-VayUMiC^Ih!o*H9mos8 zK?*zV!-GBU!Vc-!AfG1KDjhqxpB^?#m4kit=5eyI!P1iu?XGlH0UOjecD#L+bstqo z)gDR|(x}9gjH5t73Zt69k5?Z`?ZmTEW$fSqL@YkWbMSo>H_T(2>l`XkI1<+_$KclQ z(@(k|X%i~Wg_m>KB$_sIrR`Ykq&}C^#LY?Wq00yRnFvaxkE(DDQ%a9QgKOA4&oNLd z8yo8ykJ+J>vZHWLIyKfcfpX3$Q86>2OiH)E!oEITe)cY&WY+A>{u;a5t5`drZp&`8 z5bCmb8|myTT)LjUoBEftvDPQ|H$FXi$=bcm)}D!C^6vIyOn(!U&=2Uk<4}Tw0J;6u zLP~-<-e0cE!%%<=qPv*Syk$QaXvTqTvXT6vInYaVU@W=FIUnO*!Nd+~fkH)da<_nvpVZRvV7|E~h;Eaz>x(&_7a z@>Ki8@jbO(Rj`97-*LYj!t29YxS|WEM0la|Ls5l>Y5)l<0EbApV0X~BNcB*(`(b( z*us@h?v1XmdOi>TCHY$1lh*W?M@0#5e%8bT-0IuEh1FNwlaVt0@PnwxQ)DX&69U|k zBaCc?YpybBR4bI@%migJnRqsN6kA70gz*%ubM4R9xjtbfQGvM1UUeS^I-r*m)4;(d zCi8Koxn`;b_lBuY9^_a)*J?52>6^oPtHs<6P%4_=wC2G;n!0ZRl8-*iYb?0}=IJlA zYJp%(l-ew~4~9g$+fc-08bLGOo;r{*l-CfLzy&M-LqI0ymVhy#X17exy5=-6g`nj< zgT|m7gXHEzst=tv_sg6UV4w^!qEYh$l|GM@mf9y~F?iynb$IGs&pcFEPe{pPJ*BFi z^&Td?@MuJRFhUPy3c2DE)Q-^CMtu3M zT!n=qys}~}jhj_ek^h3L&PI|A@8Z#9YV67MuR5hl^t(?^NDlt%+|{1$>q%Radqt5O z-PlteRt0sVPW!}z#WQlt`JCa;xJg#Iz_Xo=( znjp8A{QaZPPxYB7&0+CHS`vaR{tz~<7ZQTl@d-hkwscGgg1?PL2mlyds)*`JQ-pu} zutWhDG7|I3(fNZoapOiWtUMX!>y$ z(YNdjNn3NpL@}qFTFJ%BM1{r_p3d6Z^%iWhpL@B;?uzkqZ&Ru`lil3q?u4jj-S7n1 z?s&zR;$$4AYN;QWY5d%;9#Xxl*=0Va7{~S1(JEuAx6U*?9+rGieVr(ZL_eJ_WR@{H zN(VuiFu`Bf673Ix9v7RVd0$6B->+{Ek8C0PK*;Rox*l0DbY^q0RuJCG$>?=fxKDRv%3WqS?E5*X4HN5dVLWIHa@``ljLZA53tX5z(wh zm|Ew&Z0`QmHV3Wys1IUeV?T1Nfq;YTpafKXTInSy7egA* zSloJEtiK@o0h4*5KVECwHV6ijF%FNTN!g5MU0H|hV(7RvHtUMSdQ4uXk=%@qpq|U2 z@g@`Nd}3H+v&CgGFcXXhNmY!0$LwO5X|Aq{o?@{j4IFEG6d(TXkhr#rmjmOVk*PA8 zi|kBXOS5j=tOgtMy3{)0)4-j>kqf!rtnCpj33*O*{JC3wlsGKwudr27$jG#evJBS5 z;bseQh!8rVM3vK|RoyK%M9ctdiRz!07SxZxGVlnLNq-;`l`EPzFIFN9fm!V=8+(P% zWBwgIv@MoP*8f>djoHapm#Yfg@;I0R{E8gv5Ndu=DCwhCO z5dx4elpU-aY4gr16D|JQU5aat#?0=JSkWNl>)R>srI1?^D{3%CNW2KAKpOmNvtDeKflmoQayH6 z0&z%7Q>OUo&=-x(w-nO}Quj_rK1xUfS0_Eh=j)4!SVVN-=(M!7Xy3MrCwA5U%xA!? z75%feEni=IVnrmOxbE#e^%T`sUmB{J=!X%#RzTrUhf+RYA9BCI<`0^M^25`BEqgrU z_B5tr+oLL86w{@RcbEpoZnm zu|y9piv-N&Hzkso0Lx8C6t)3H3GJ9UC|HKT4+WrLAW`h8?xv3U`quFUR*TmorCi}W z3&(`8K^wS1>rkS!n3!=&B+WUL7*(VuiDwM>Yv{HR= zPWG`vUIo$apT3_VUYRVOitwD3jh-w!%qLb9R9_ChlF{R38`wd8C;KJajyTLqNT^fU`EwuhZ_FsK~2Sk*jZA<(WxcB|rPy-pe%KXvwZ- zFsn`EFZq_mb*vi9m<^Dez<9Nq>v4ozVi_h@hjwxc*?4_#H5kMYZ{F1yJ!{ z`0%^QK^0AHw|un;ENj_)UmJluPNNrNLf0!~3)7i7ts;xy)mCr%U$LVt6~Jr!Xd-`_vi8_L>0IDN)Z` z^>s45uf^1E_0?b22{u3Z)wbPSNsVu#Wkz$28n4nNmfw%9>^SRSo(pG)z5UxfN|_a% zSiJVlwEA{>O63v{{5;y`DwRtGw?34~y=2HfxO%um7-6T2yNj<5wz+soKWKtnX)mb? z;7gg8lzj4jL6&AcN}^cX2Z!AMrRH&Wv+>!&DAKGAMBk1}MOkm8)mLPbWd!3QyBhNG zj>W}d9H9Qb^Wkfqt@9A8O*C7<;$CCZ45;iQ=ucmpvri;!Pk7)i5zB}Q2RRX5VheVPe@ zsvy7Sn&8?;@?N_khVja5?7PPGyOP0PUUNYE_MSgt-dfDv!gy_{eQ&j_W^+%u*LpbT zx4D-*3R)(6%KKk}GZD#N@;LxodU|=}Kv86(qbKt=FRZy<@)5VmeXj77$0G+Q?^g)9 zvtW~Ik(WH{jRK05SeVETl?1-X5%Qip@OjT^)@*|-4i|MLU0R|a`aofm4-yD8 z2V1*&ZVrqyYJ%cf+wa*y@y7bV1hz+}@k>#Sw%ZY-mKl3RM$sHTjGZ@$*;SgNnixF!ltlcjRWky3F1oRys1A&sv--GwhJSY&^> zImRDy#q0H_M0ZcQR~wUjOi2-tB;8=#ByM_BRG+D>l0bHL_C;&r(7KWUY4wH>Dm1#_ z*(QT?d~>nOhgdrcwmU6DDr!@ojuLfVRHf6U_!w-zFB4bmbjiN74pya}>sAPjOd;$* z|aO+XJCR*28RiqMp!09QD1%ZtW$qL&Y8c|u(&p3qLElGMdVl>C=4c*{P2dTKHlmZ zGMjIkDoY;~NJp&*)oz4J0#G5RW4$U|+Z2Cv9Mz7CAMT?<_m}cohxAcJe1%>5s###E zMEwAp@Q|bre|`Wck)E^?J$b`KqD+(mB62^;ha64hYWOS+JcMB?yxti*UZRH2qE-U} z)za;|VNsa7SC6W107}#kZ;I;Utv;mhpxiAEwuyF=r~cf&1|9WSLckmp&jn=BN&k+gAb?h%?FrEJu(J9LNFr^?A$^n5>y{idl!h|f{c7BbE1qV4|8{8l3x93qAgjsb=w{EM8O@woU#_65LaUI2@*9V z4!B8TJ<-L<1KuQw5?n|-W%Ax~SsZ!tT=Gliafv4m%Vh8K71`eR^w*a$GPztHahA>^ zVX-t+M&9oZnZlJc;%zuHSy_F5k%cMbm(c3lBnu06zXYlFp{}z{T%gA)lqg7c4FBkZ zCR#v>mnhE7BL^kwnr;8!_>i}^*infpl8p$LFM!kbqr%_yHFD8jpL#~oF&i2QKVXa< z=dO?)5+v&T&C-v1uXl-96v<1JP0btT>ocqOU*?B4vFiPNp#bzW=t?fr-z68(_fTJ1 zS$~VItgfs>H$=tP)Im|d{|Y~=e9(oYD^{cVK##{?pxIw(LT2(dSC95VeF>H#Kxc<# zsC2Q;Oc#r*iA|u#pY?iZE;+8lQ8h+2B?>F?_KbMxy5syEb5}7TGtJ6d*9sM6Z(V)! zZMuT1H@zvU&-9vj&x@RX&*4$8Q8dRH-`}-UwliPf>t*%50M*wC)Qd4DIwh(TsLttm zT7BlL$Av;)#;eEMZQ2&~VPiLO9%dKKj*4+68bI;*HpyoYpSM$7QdU%a>^rLn4yp0!MDWC+a z@05tNCS$Uw2DXY0VKGWOp#*s*7(?P{?eU;^t?eN&2C1}?BVZ1UYhX@-uKQuO+YvCh zAxjbMHQ+&sLfVcmJje-y$DvK?a5YUE%(I2frna>mrsg)Fn%h@2+O@WwKsc9hSgn)g zBxZfbEv(g2+qUg(85HRT0u}WW~an?M_)F4t7zV!5x&o$M0tdM#hAXg9KorYhKwV9Z=3dpYRnK&F%{`Mty5aV_7RKz3) zSS`oc!tIfZddcYhYg`$RnoUt5zHE%#%c}rVXUBNS7Qnf8z2qaB;PYvtykt2*wt0FK z!os&?EwbxC9QGj~TuQN0efwGG0oA&Ig!_h|xO3tfC|BqkC6O(L zz*$=6hejq!XYkx$tdJCHC55dT$swqB&8lTox+Q*KiFK=$7Q%IxqeP<4Nej7iwkJ#N zFPW3QO+{UFutT&;cUoKpWj5b!waK|(%F}4uos5tw&S~E1t22@vlf*}jJGwN5#2Jl= zIgltWWVed$e(uu*x%T=P$AacX5xnRm`nTu;<6*e_731eVuqevNj+=?G0Yg3hpE1Vo zRRZc~V#E6*;sn^Q)|{ z42i>NDWi^@)C5QzVxBq(Ou&O#TS`nL`9bfzxl)~LN2~E^Y-%R>(dwoP{b*)JA!8o~ z-7Vp7nCpI!);>kL1e+tVm16uUP;r*zxvz@VN0a|vQz~6m8VeOqS#>H!XWAv|nkQ9^ z<#G%OEg$JMb71L8fLPr7{ocLfiA2Rn$ys_QOyK#hQUVgv9JFrUFcrowv9^V6Kz)cd zkU}}q4#`6-(Px3s?5!fl3hC>MLXQ zaYNfmkn^#J9ZQg>`qqkRj3Hcer9&Ie$#z)|kB-B5KUg?sxYW_rM&x1Y2$ahSi~tmt z4Y{J4Mr;MCJ{pv$A7Fb|J!#BDqQ2)7X)Yc>(~F(~cPGu%*g}CS za?m*+#)PTuK)o6gC0KoBm|enL?6v@Qiq@N;CDGw7CRVhRARm-K(@hNG8ACpuuEFyp zoU^Gy1*hq8xVgDmmo%Wox{oRZgA0LnO-|7q8eFE8kXJEmCV6)jhIg}M9V0X7m+^BJiY3a-EG+6)Jjz!Y3N&>nxH{aNF}P9AW=L} zLx}wr-Gxe&mid2^t0*RkU7Mg(RFg>v40WHqyr#X`i?Y+02O4(ZbeI%Yz$EX*@P zUu%Q0Qp-e^xYs0EsOJbhn&*pTq4EeL7bEK}+W=ZykE7Voxk>J!vN-4(Q5E#z0bf&5JYdj56$Fx>@c_EF-nZXcf) zgkNI6Id0^ao>HRNaQdOt`0-PvNV_)n!4H|T*}qHG$6I~5Qt}xnMT0BZmi%%O(ySIq zL*MP&1Up?u^z27w(y*TI=^;rPE{`z5X3Vr>f@?CxVE4O_Y9DS@m--1nY5DQsZ2D6H z^*}kw=_a_o{&xtJVD)ViQF2#w6H+ma9+$+IP%^u%18$s(bIrlrRcw!gU>>rdf%y(v z+;VWVxp`0~3|Rm$(bw|_#D zA7mURgbHaga%kM<>@m3!n!vXaK8tQ1{f@rEr9I@YCKdOvR14kLdg^_gRYSMt8 z`8o~MCAK)yN}}=w|C6VOe6+q%w!-E}k-V2YLa$}gykvdvYRQp1Wys}G?~lWuL^rpQ z?Q>0rk#aA`Ls06y$V(d0dd9o;jL#&yrbV(|vP{;Ekr$rw!TJxqWD8)s-*g&4{JXLG zIA@D27=&tvQwCs=Kq;o?JMBa<+3EBp&bE8+qzL)bWTm;j=ey9BO(UIC{H=f*ZeNhd z+=Rp~SC%o~H`)vqA02L2y^J}jWjq%wWR75TK!|<53qJz(o@kJL)e!gF(OvXq%z|=f za&ddv`e^26k%Q@sQ+J1YTmP$WKHLmZS`BFwTsObwz^<^}L-ut@7ya)-qHNj%*{;uv zo%ihpA)ZJe4xO;?7O&|;iC(_Op+k#XlzNMcFRfH^%4sLFz*y(D;1Lmr=GEKqI2tOtFtV1RKvC^DWoAc-D#ej8feVDRtBp2Q ze9$0L@l`@h=(az!Sschkwd2;3{{=5$3*>JoW7c@u9#1SKM7Lh0o(TC@3Zd!nC;0kG21{f%?(2zI%_ zHet7U;t)$dM3HYLxm-FMOFlSCRpbLo;w4>24w1<*b4!J%qcp+@XI4P zUbAz>IYq7>o_%XD44N2uyr+{z9z2S5cxmr$?AR;b_oJGS~ZiSYA&o2VL6>@XxURYZwH7OBADvyd@_5TvXoyyF9$GYz3C z6Ws;~j6+8eHz?tZU6X~&>Hw7RHH)9ZjgqQHrX8q%w0|#Ks6!pDq6g?KgkxJeVJwDm z3pqzi(1Ed@-$keUeOY}%)u1twUT=fy5w(m6y`xxOR!Z!t)!w2~V?qbLoJLy1bU?d`ifm`P>J6SJclZ)<2$f1_8?i#nzq{Aq_?JHs?MOPg=^j>P ziP-K3pux7#;Bo-C5LKh(hCyo)nCpiBj& zOeWE^nFOdaOcq@0|6fFg?+VWI9rphP8p(<6%rU5Vieb`kj@3s~m0nXSmAkDoVA2G? zZ8Z*Cr^EpPN)x`peBF(RN?C6i7Mv>WEmINL&i*gC%GePoAvWrac=tE^7x@Shg&8!5 z$D>4Hc;h$c%=bfq5Jqu)u~;B8nX{r=xjZ z#QW+_iNeFjhO4wxqJC!X2ohx&bYdwte-mo)gUh$2vAsG@tWi$(oyE$i9}g^edWOtdr3e1LMa|><02m01hleoU7(DTgFR)^ zIaHCICMt1_RF0M7b6sT85lv*tRUFm?$x>Hogx<+0#nnSLR$nn#?&(OZKIx2JveEi8?)oxE95NyI zIutFx;wC$AifG>?Suc4ewi@zP_dDsM+I)RRoy8Pr?l344n)#RC+>xH+_+3r97JiA} zMW^Q;bRh|+?3g5}rG4n-BkDBrr=s6aq-QdA{7B+&%ChRd?tZ7Q@6~Y1mfGu~b9&g< z_sRiPF|m_3d@X?LoE~NMJ^!hb;e9byU#CR9HdbFJP_Kv8SGOg7Jzq<_B0GIon+<(E zV?F*Z&sg6=XL&d)&Y+|Ci`T42FYGt`tR!QX-r77b-b*HoR4k@pao5qKVc7ddB40%@;&A0)sSt*<$zD0iv4+mvYarEr>NxM)Frjan zQg)Jyc8U$QuZCgorA?OIgvE}rLB7@>yn*hap`orGH84XG+REBYt9 z&jOF(t4^RE15_=8aj`?}OmGf)2eX?Kzj>$%xE||pd^v_t4U7lY`2Z_90^qhl%Nz!_ zTNd@=cF*LxXMrV!oCT;MNOGNHGGQQtq~k*L+zt)>@G(GjelnGgdr}qHgnO?pd}8Md{`^`@q$P%1W1*M_2-e~7`P5IDsnVu zWvA-ni9^z8>oT%~R2adD(?Xhkl13aBIqcwxLz=qol=oS?CJXgs9zNzY>chlH8gZEN zp>-dnx?1@sAEF@x4r8|9MYCX`$kW}E5$MHorCgQ;_mJmE@vXJ_@q$?YIZtR2iK3%5 z0<$pZCFi!G6DNx?F`R!x6Xw7W8hdDPrDI&QHk3H5kp6%H@E0(Ia7hFW@J#h7S&4$@ zL*sUneQ5>H3A3!sb7Fe{i}ChEq9E6O`Yh4`R#sMSY)?2}#Qb=VN|b*sqbJ%AsY6a} z#6C()%jRJby~b{xs;>>G3g@WGmijd=Sx_#STitv$gjm}7yNOLPyZO571}bTz8Gck@z zWnzRW1aqaIlg)|dZObK;?Kecrz1-K6J}T{9d4#@Jj(^Fi42 z?JvpK_q5*gpG8j^hOTi@?VIf0`7QhkFudA{PlVz64CTB#oiKG0hn+xm#z(yvtFKd{ zUK^{g6R6k2>MLKfeAN}+wUfSd?QP5Uk~BJEzc_6bPxzIPuVBbeORok^HcrRu_!*e< zR%G0M5GX@7rs^-DyJYWzJ>>tq>R-5{+D93AXWn~ShH6u!m8l}{5L*XHs@LA?<6@+v z=Z(S|C+sBY*jR;>Cp#cjwj5bOGW*mKi|J{ceF3J(=Z+U&x;Bwao)L8BI>sE-FKv{4 z%>(9nk`!Ot=J1K0_Tk|wlUrZq#8AnCC*02X8a^iL!Kp?4v=5YGRhUa-^FJMy5+BUL zcy8w7PE!>BOs_HJh5L;KV(&Bf@1_c&2Oe&~PEGDHrV(D%$|;IQNP2D4HeE zAgN028yxOBz(gd94e9r(JRT}s`-g|~t->(){cw3Emip2R?*Az{-%p);qUsj!dnyjj}#w- zowBfzj+e|ml=A)(_XWR+)z?lO-V@?%lYOAB+Cm&sKB~x}^(T4F4xSqTWf>)N-<|foKIhb^~ z)c!Vx5Tk&Uufn~N@hanC-|DT0t-g@!qzA3-Q3Q%5K#8hA)9n~JAo;^qsI{p|B!{Ll zRP`;4Fk!sn!kIK+=Zsj7HNq0(XcF8B?oEL4T|4ab!+rDu5eE}U6CCQRht=zeE}02| z{w7%Fhw*pZires31Qvm0yRSn!$lQI5iF@%RG;j4$;;>8+8k%K^I81p2ai|}b2|Q56 zvfcD)cxEY@W)3b3fBO@w&`@X~uifB6n*gni2XDO{9&YLW8l+MCThNt$3=&m5D;1J} zq~Zk>g22oq_l&g}K{JbOrWF{eY!-><76@SlQ~17S0v&`Ahd?zFppYU7Odt|9G%O=K z!#M{difeh*7ce>_Bct0fB2jK*$uG%?w|GA=&h_Gf;;lZe+XhT2k%vWgkMaF3?UT>'Z4 zd&+5Z-^-P$eJV|`Sw@SD8f+=3S_xmjlJsC!88BfPBa_LPG3^o+5S5p=@0PGb#nPVA z1^BKwx9@n5-_Qh`srLT6N5{Q!R zyEboRBn(_f`D@)8g*4I#ZxPesJo7ia(NdAl^$2Mo>wY7vZ^DQ4_NL5%5IR7GrmX~? zHc#@WfrrZ?lHcjoTQ2IS-{#1VtDuTe$fR97A0CW2WZklKI^AjHgM~iott{({mk~K? z5EuCfX%#~jXc@uk3(TafJnxp@}7LXfBqCBJk1b;h$OMBUgQI3#h2i;xaPE7b@L*o zDp#}tibPeUkJ@2((Ol%!wCvw*=_c_Z!kZla^Zu6}dID6cd$n;#U(+(5Te_e)((N?E zBm&9851Nb%eN7!CYRVWr1Gem+z4(`06bWT=FYLu@20OmwFvYlnF9zQN7GRA)9D+SAKxt_j|nufW>ZbtAnzXY08TqBm1y zQNM}RM<2%6_VM2_bWmUujodGu%J_^fBolvtRYg0l<4IT=RA@3=mRn5^?Z@9KT_By4 z`GL(HPS#%jUD(!Y=D$ZC+Wx@PJg|ZCnr;V$&BptWe)u=g*H^w&cJujMu;ZY@7d*Z7 z62`B+Y=(Dd?DHx;S+eRkduc1Kyfj~5r}zAo_nvnG^*aZuli__)R$r$?z0y-B!~43Z zKHlo%qV1=yo-CO~K3>MzPh0(|jo`IUaZI0Ke+819$PE2P6}H3(j`m2OE-I{;F>S`Q zL6O&Dm9f(Xjp4eDB|oYk2h>#)#5|Y^$C9t=;feR0nJX>JMNYyO6c->vU(KJCO6L!h z%H0>3smj=3=@WA7Xhr}eMLc3d{ZsQt)^5Dij=UswN?1*c4?pfS6TW*UTs~@fwAHuF z0lm!SUR99jjgL@da}?@tfdT8+#6%fvPXbJtP3|lt+!q?;H!Z}WhW`j^kkx1b+`{#s3CS>SQ5ssn6~Lg*rxvA<^t3S7PxXP`B!CwS2R`mCf~5o0diDz9APN zXWoq!LF)E?g-qaWyo;|bj-Qrq=+BmK@D}RG8)&J7il(}~mvI0*U61at>$`4QN@VH2 z`I?*sfzsvEL+kSk$bW$gZjs0STN8OuvX;9H>U_TOR=BRe&0S{q>EY_$f>zv8vK#ZS z?%zvHefBbWYDDHLJ}rC2u&-EpyycO`1fQT3IADb$dc($Gs!~cEo^qn0hTFYOkULGoj-Lh7FtjpN&!QOug4|dWwN^T@G@8`fWM;a1LX0A~LC}nu4 zh%^l+&M^jpqoZYXYP?D#PtB!4wrFlbhig zYPco~SIDcNOct(m$%3E+d|C($Q-n(sU|ED`S^G;@?^iz+*WEpwTsz!-2e3XdB%YM!%HfWjf-c=Lam4o}~@o9s_H-B;s zQ@X}MnK*pnM-I2SN$$#z-qW9P3VvU~gq?g8Q0>HF2R=%t;S3>s|6)uW>tMAe{qw?@lk zVNmILbj=TqL%xs;$SSgHf(l92d1eEVBfTcJ2{e)$f}<3)(kd7p_kcuk!}#GW(Q^Qb zzojHq;!H@fy94J$HR$n9a%h4wQB%wqa>Js#NLYM%5i=8F?7<%1c^DE0Tw*3*V#pm1 z`XQtdZ0`d@{7kUj&NOfxhtA|wA6f`<=!d+{BgZcDBN9aiD=Z$MwLJlb;6l#rAZh9< z_z9cKgvdq-xyumRq_G^CmdONmdJWm**ga+)HnvT^w0tdwS8{=I=*8v&5=xo>09sn@ z5mp~14oiFY?wwgHFuWGxkftil6^O%-9N11BH9L7iN{G%FPC7JAdNpV}=IaaHkAwSB zi*r4W8EmV_|F9i{sB*ox@?8$isXZ)?=F(i|$5V$3aBu||uL03bb?1lFY?98!bnRshde*Iw?y6;K@J(R(#e1T=Zei(ZX_8}$9p_&( z(G-%2jw^*BGpsYuuOTg^WiBC5TYYE%lNW$JW$7=2vyKlCoC6;SE4|D2Q)2fU3zS+8SEA9KKgGd?CBD9PWcL`6^n@vYJ6WU7L{ zO?Gv!qOUKX{Gzu`i9;NCLF7Q&?K=vTH?kb$9&Zj@M_^e+4lSp#k@OMIGxPCe#_q>T zMfht~kzEI%z9V93!i2nrjzAUCmf0YgyDQ)M;LntQOMto+ABh(LjoMq{zYyPfVkCyP zU+B{GXsd6EFYN`0<{m~#CM`e4g<`PG|7V;nj##5mC_F_Y^qai-p*=hJ&Vkl>y^eY0 z7Y?xQqX2zFc|3YT6y-{X&nmSyJtCWfVD)KT z`ya0_nIYW(6)q9#%6zOQz6Hm1L{y)3IZS5t#nJ+SIMhg1srRcd^KSs*iKN8g`dj(7 z2Og3rRDUQ@H@NOu&8%BoYlUkT>l)X*S$tQJD1&pRsoeP>&+#Ulv)Ry`Vv|)yC8{;W z`_}dGl7pvtiHeTm)y@yrR-Z5piEnPk%(GgV><$lHtN&dR)fqfvz{fcplAL*lDir;NRVk8$B z)m-ArD~(|hI^6{147rdRS(ITaP}j)*EGK2ax=W-@#GWXPhRq|ccCI!9+n>ofpO#HBdQ?g5U~I} zW%aDtzO&uoX)iI zH%tGlN&97O_Tm`cPN(d1ra3yj=f7{_uoI|Gpnj*SPq6y(XH1-SoUYn4eeAr8mhD@V z(=PKf{Knd>oQ5P(iBgGQzvgs$fO$2}T2@b<+hk31SWSYziH;R+n|@~g`7fD5r<@+M z!HO<|Wsz?VP=eLRhBz$Gm|;7He98qm&dX3r;)F+aU%Ntj2^Qk43KHGd|JkkzPRUlS zksgI>J#BF;>@`m*1}Y93v3`=b{s|IwtMvh(hLO+qTTifA?VbRX_v3(S^EPVUBaP<` zs;ehheT$utr@GerCdBxlT$D+U!1XIY8NpJ5no&lpB=|x+Ym#8 zATS#o7qHG6sOx#VbhOSW6gQcRTY>u~?-m|YlD*3a>h77h*!`^~c)6?90Oi?2)ls&9 z-J7RFe_4JWdK!weF~zJVFOP_}PTjI6uZ2hyyBG5hbKhhWY1Uk+$fL4d+=8B?mOX3L zz@|9uZ>>X8Zf`cZfx2o<-mccyTlG=zd3Q^k1>24H14T#Dh(r5!;&6v|5wa9peQLWj zsnztMqj~8V7AJ%{#6(${=gG3z$7-9$!oI!7 z{D@RB#wW$N&l|^wS(k}Jm80yc&WppRjuhWvL;5Wb@zIw_r^d<_z$r(?v|y*EQ%;K5 zU3#T218xdwAIF7$_7-#S?# z>7#C(7u^K5hl*WMgUlN;G^CH(NiK2P$wd9lv@j{0XAWba(|K}FoLkNg2R)br60p0e z*bS$c?}2+OYbUu&wp$@GB&_qnP2{|ZV`zvjk*M;ODBmV*Ipm-zc$`hu5+^;Bz1I1K zD{a~$4$pddc_v(7{%!#Z1R|qUywRJ(oU*w-G_0+NIYK3_O`;GeF2o~kWG^eAD5T!&y+7wEjW*ysQZfPSD627L zOqtDSOu2pvg?jibYD_pEiRMENx00oE;wCflg`|(#6RRB8MUUBtmqk$CitC=UgmO|p zzSgSG)J7bZ6pT|Dy7A*^rqFkeMe9g=r!>PUCv5z%-5aZ-@v3e@J5XTWl72D9D&p`o z);PqzYccZ9M4~9O8?CCdom-%GTZaq{avL$TFmf^3iBDHyG541E3pp?`St*9B)vs2F zGWjy5(KC6Vj?xh}A#wCxg0f2g&4gB8ibI}yqgcO{mna%G?6wXg)*3{2Uw^AFk?$VJ zn~$bRlr=oHL^EeEi_l;U=)y=Ec$hc_nK3>nw}a|4t4-E%ccJ?);O?nDQ0BPL@&6%E zlm-n{p#ZSm)(NT)N}Vv$emk}We&Ee{6zU04=fx%jiW0yfaTxt_%AxfXQr<)3Phoaj z=c7nJK|m%=<-N%-F@airn0Irln3t#lz;}ViP;=J4))FOHeTG5(cB#LaEd3AC`}*xu zZ*h$>K`zl6F@Bf#NDE++-{mi)L`8*N{)_Y^EbMo&*m)iI&AyKw1jwN({$DX19l8fWOXPKSYpoEyf-u|4MK%H0m~ zK+V>b*dC!Hpa!n{NxHt}3u)Da$a>upA2?+*r@6@H4s`;G*OzmkVx-qp-HeI#BYWN4Mucn2 zV2`oYu!%g2Hth8`CSEBQ(vw^gryu8%0M_kTr?2l{nL=L(P^X+8!`!SH9Qj7$^eQsE zhEUFXDo_`@MuZ%^SyuQC<)yZcX^ug0>mEIy{_wN3koyCt`7kFX3_FQ- z4&7AhEgfV31oK>HdJ3TKF~9gJ%6Yc!Vtyt%aM`a1D)3bR%Hr#z-k*xln=pY^lsqRn z2;~<+OF)8!k<{gvI7ahP4Lad8AKgI@Hs^L2Kz$2lTtr_VjXN0{XXQfLr^~L~+tOlt zGB1OYhZ)(o!MxYFC%phz6yB0*fc*5`CSIbxS%Za1x%_l8Gwe2GXH;kez;< z9NYwOT@d=Zj12ts&6>5d1os%PwCU25jZAp#44V`8aIi$k0*LOH78n7wM53bmrB8Oh!;O0{eUej6nK*R$ zc@4PWXy2a>!#P8-~>l>k-YIyHUJETpCkJ@}_PD~(+t%Y;Oav>7tg7irUFRd7}| zZG}7&hAEdQpA#8He12-_?8j;vdKCMXi@AQUKq8dzuh}TK-GePle zSc36T&PQ?ydMV^oslJe8htY~BkUWe6%*JW(JY=Dui#Jfez8f7=fI&?-v;Z?^p0U>t zBl>^n0Lo$_5qheteqas;r(xXFOE)I82vm_wCX2TK^@tjW4y0A(I#NVa9WTLYWQA!Y z3<{ZH(EQ6^$d7jHqv+Gwe$U#H{kA)8>q>*zkdY^ClSV^@Bv8&6TZcZyPN`J(96&?i z7W-2&HZcNm6o^9%n2K>E`?#uzXj5j44-@2riFvIX6pxv!(3!r~haiZdZ&^g50zM$e z5t%NPSyHOAYsQDa>kUcv$_+#(EU{Pa)&tvZgi<-4slunhriaz(5|D1JA;!ewNI2~S zFCQq*Ig8wVWo5L=Ak?XwAP|SV>T{rDCQRI74;q}D*tbULmH5~z95aCo(PHaBHs?Yj zQQtKpeYL}BGrrrcPBc7nf=Y-F5{gd}*iziF40Zv&T?=WrZ~!tLJaLFXaZ~(opNj-2 zfjFe9cuqS|L*jD@&=?N7wGYrbrU98q9?m9*?YafmY<&cvCcIZri5zzMiorznLHW`@ zI$kn#i^tP94U6ZAwh1Z$sGG!?sFnUWAroG%>Z4ZQLU%eQFIokYXzXEyEhT!jwpF|_ zaTARRNTDN?AjubJY`2p_5=;b&%En^rRHZJ3M53x1k%LU}DML1BnI8?pn=p&Uum&tR zO_1PLV-em{*d%mDo&=s*hH#P@=^|5+{~sEMnPyXbsToNnstqV44}VHGVcJrz`+-ye zsBJ`|`j~Lk%;%AmJmhr14$cxfSa3c>9?RSGe}U$wt*3%X!w&E3pbaP@QL|8=G@*Gu zbd~Jxt6=pR2D`7_pEu6F05k!W)zADWP{ZSSpxnQ$8|P2W^BvNc?47sx`pg?cdxx#WFO=rhijTsH z%?ulftecY+A0Nd}Tt(P%s13&{{v1Ceq7bau0Ni9;S_$Qodw={u#NqUtU{>B{C#u6g znr{NljE_Qh0XvyA%-kF(4pwC49)h~b!4s=!v9Ee1Zib4DQo!nN_e!wO90)1aIVDCBcQ6pwlzhv<^o)M_{z&*vd7Ay(gjHNjzp@Wm?f z4KS+r*lNRMqOW((rN>+w)qf>BW6rh7A1PLu$Q62jjCyUOB6yk(R_`V^xPkureE0O; zQ9Ag%5OX-cWV-9sjOHj4|9UbuDdKrP&UPOYyaL9=s|M7QhBH4kPy?Rd!&E4xN1+p_ zhbKecuW!HQ&(V>f&8vJxe0?u~=IG?3UWC>6ib+)G^jNE}6R1~w>WtxiT_nop5j76y zt!)c1D@jYIF-m-mLt5OhZFYTi8qFF=bE%p0R;=ns6!BC%>siHm-uR`P_*woeMqZKM zvpitRqpIUA<~1!c$HtCquW>jRYaFIHE}v{)12OXDlaTU~s*x=anp;+Va=0g&t)>B{Klc$EKV0aa66t7PGED!idhBt<1EGlk2 z!->={H+)gB`h*&Xa;$NPci&dy@F=Zuh#5+9UumTGZ)|;@jA(`*Lh2Hajl3!|?Wwaiv2%2wk zYPFHfShWf2_E(~(2oJ8KH4SfpQD+un>F^Qg+2JalsYS=CuV8UQ{^w&XEv zJTy~g=}L(DAWw+J4t4bAZkcaETdhO78JCc7tJ{Cs#2?O=IDDB_pHSn_XjS7d(o*B_ ztQ}2NO3RN#)BI^LT-6}b>+p3Oc`gw@d-r-y}(%AS5LWp?Akdb-~!br|V!JH|b{r@tYX>3@n7C@qV_#fZX zW6`xK?(`mCqSe-VRDb1-^CapTtb<*4N_t1~dXAiB*7!~$F zs?yn}M)aP~Le_-FA4W$tO5%|jq~Y+x;%k{2sFmL#uw4_?02i29Dy|`Kb3qxC1MDC& z+W@ES?f~nyuC@!(m`z~laRh;4PVyWYK(3DwHu*zJpH@r|nkv2x%evHHipL}}t7T3S z)rVRC%EWhmlATNv-1}3=nMy@JOi;nFD1cLTO+j(M4RbJI$m4b=(=dWYiqHL^csxDL zj+k6SfNEs^PD>oVM5~XlaTuxy&AK4uludn9jYBK|OC7JpGV%uTWg-zE096+LZlul{ zs3W}hoFKHxX(ykiv=LJhTKK30Ar~f*s8omSjEs;-TDdJTf^s4;k!9k$JasZ5>YTU* z68mPX%@{NXz2|>uBMv*3(F;tl5Qp1+XgW^LEr$R#kXAT60^7VCg||#ek#0vPsJQNj zG4o|Xx1$)M#oA8G$XH=>GbA1#-5{Bpk@08I?Vu0Vqrwcxv6MJ`iN=Jb#$oWB#z)mS zq=f1zcPws5{W6d6`lCVdV%4M7l=b5QOWjL zmvB8ztGdjeI%O9RC~YGSBQba96c60z+wI;a8q{G$9AfxdN8-?j_w@y25}@81fyZ3} zO*cQmGlj_xIp>2DRK{+{kXhS}w0@C;K{6Kiyp2r9X{QQiDp^?G)UsxzG=i$WmNmiB z$kvw$R9lThm356nZO0mi17Ig#+>ozvsKvlQnhO_!dZ@->sKD@k-)MV;0QzrdF(fy| zx6#7z{tpVk4ivL*utqY5A(DQMrWu|PMN1QsnZ2IRQ#(v`jzC9GZv<=Na0=$e_zG)( zBJrNuf#LO`RO086Jo{?`Zup!)p%aaXpv5Pn=TNp#BPr~DkldU@b9bKJ79`5~1nqh` zVqK8k2vFpg#x3WiT75tDu+%s_FU1;%f$cR8%VdXuuW_h#$-G)wS*^9rs;so}`X1On zRrId zRmKbbh@Sa^tRcN&i2MNTeAkm~Eb@o5D9C|)=F(g*`3NHLYdpQ)DS&NJSc{OHCW0t} z7%%r6NLBF_4v!i>BI+%fABOb#{PA91-@=jvV5fU|j;IFB_+C-l98BzVPj|&7h#~6a z%m|ZVGC6fMIkUSLd9q3tKdHu{^_Xm<>2WS3p_(DvQN0Tn z=}^?L!g$xKS6lT7Kozf;n#KnY70*+qSG9Mt%d7almV9hrg_rd87@kNo zm2Om~5v!KVo<1M>!;;u}R~`b2?eRV9QuRwWaZmazM&7eU943wV#a$*mia!i_YFmVJ zdqjft#^+VA`vGIZ++O1_1Zx~hgc^s*j_EUGmtdJ3YaIR*tBh3+_J_J)bcl09BKEG3 zp5#LMX2gi9V7n|WR$BFtd0uIJKB1x9M{QWL&op%FDIyM|;~ufHt_60)J>@%mu$e79 zLL{K|g#h)~8i$3n#vukCPM{uFt^5)sZkRL+J*jsAhRv#Vyo-bQSyys%d#+eXl-l^W zTk2NU_Pg?3=zgx-yI&8S8nCb-hb%4D61K(He=C0_KM*v6O?1& zzq6u(7IK5Qck>l!sWkuXE6eLC*^OuC)L4*ESKqu(4J}x2PHm6Th*6TW0^xkB~~=VnuJ$d zuVabAt9njNCgc<=c9CbS83ldta^+%vIJx3^A7jV%tk=UX)m%^7fq^Uc*nxYl` zl~NVn4ia!7qeCZ3<6uZ;k&8PYdsQTxIN5$T1cZC#BukZwQ6ECCy)x9kigOzqHr{3f z>s+V}4GncAAL+{+l_MSRq)7U$Z^Rsg9iRC5SbajoA#|v5*yo`dhZq=B%Lkv(nn-`~ z3jZj=$U8>wo^l%3-?d+p6;RHzcs^ z_QcP}>U+4xVQR-3hZ`|U?TlS(+o%xA=ZqV@YmFRV);3uoY-dgY7xX}l!((8ut)i6! zkvP=Th(nY^fjAr%FA#^dNF1i6r3Ve5#NomLG|6USWP8M6)VVHt47p89^HdSh-uVag zo>S&bAPz&Ui9@70&~fXQMf#|LVQFbAx*dj7az`P?X`$o%ivmA$#?FMN(ApMasXX$) zII!Tf69tNYyEOK$migzvO!EIfXc5Ymjj^$AvjACyXzzv+Le9f(6d;*h95 zw+M1rS{0Ev3vo!x8@8*yIke0nRej#TvxcUjZ4%YM)X+L`f$QJ`cBUzQTtL{aeIa~a zfMkCTC2HBfkvlfHeX@7opaonH1nS0i;fZ--=Q$Y@Q+zDMAz$NAwMQ1$7qReX?&OO6&v`tq~d+PjmV1(KU#E-0pNA zebY3;w4FG#6T%FKsgU8N9O6U7A-OHxUK1q_-PUzvczNQGNYv1H>P6>5;)4>}o#4?? z6p8Ib^^HOD@CIU?>jdNCACM?Imf%bm{lIm+a82-|Lvx1Ag0~J^B&vuSyqJrX3!oB3 zRNooP6SoyQd=5ZqUH$fVtZ_JqyzU>?06| z8}4rw-zDv9tNlge7Ds)mZ)+|80m1gjG1iB~!Qy_m>q3a?voGY9c$;GUbk~E3>T3gP zN+h4mCptpcJT8(Za0!g8+v576mO0d%>@|SJaC$0H8kad0m6dRgDb)Q*KAUw*XeQ5T z^~9>@WAzcK{ZlWQ$5ea_&1YV+cQ9q%3UbHnWO=Xkw8mjC1R)m(C~)K6?)}GiW}D6i z%RT0s&i2NVhbr8~Bh!lJU`JH}tEgcWdq0wo)nnPeUMo$FA7L@uOxWh>K0kRqlq=-# z7lQT!J(Q1>dyuP^1{nL_YN72Y_7hog6qDiGRs$@CMMfUh>g* z$n0ILV7QZX??qAcUy}bKFOS`T6%KQI$rXhLtUZ{^mng(Shtu?+87Uv}%?Q)yt0v3e zzX(6^r49c?9<(gNlz0$|dZV&(=fCe;}*+emrTdYvf*;<-wWJq=(+7GLQSd ztatDCd-uN$e@>z|F8p{(a_$PimfLVx2_pZ+NpW z2dGEZIGjSiz!ygfp;0Lx7CGtB-HBR;8^Uw-G(3Vwhzp6gR(-6?sQv{hj89T|I*Yv~sljCMVNLa7TBI(pvX%-a8l%pJO zliAc6(xY6+d-KMTS1_diym8+8-(K~Z9v}|eYaBLPfNHQIPcp$9y`6yhW$R*tKOuKo z5gUXvOMKLW62&^JK!YTHVkDl`;7owRw7~?Z|6y1BKwkDCPVzmbXr^&%A*x#D5E2u3 zG)?3exWJMg^bAu4r1zir}+QJUbVd86JYda+{O zsD4%LK!q%L5U68NB$^f*JJNdx%3?GxQ3NQ-fAe(?b65mQ^kXWXc$r_V&5xAa2cG9b z^3;}ZK$wZMtcwZGcWJ%H;MA`WYP*;?w=7hBiIGMlq`Xi zFR{vyKbVl)BC^;$2jdNoP>JH4kF?z~MlEV3Cx^`;|9^+Qp_-?=wTv=0cCx4`#66AZ zPcFzK?c&R_`e>?BomxFkWsr2Nafm=s1(=_HJk^gD7!>lME#za?Xz@Bhl&mF+4`e$n zUYnhry^Dq$PMD>YAW-oHuLeoHTHQT|m#7~pubccK9gM__24%JuMzl$kLo1ZowZgeB zCfY}Z5UYSl6cpLr>R!m&+K`Dk!2{*j7Rfd+63Zr5BT$Rocd1u9nXt4dIB%d9it`~N zP7_qDb9>q_d;o*wBx!J3%v7vp_DgQ?T4q6Z_S)=L*rRmuZ2|M%$+Gueg6iY*p7YsO zquXj6Iv?mDQJmU{VR%2GO%W4y76%@r`V^t4CHZ!cs0US_%L$-$4vofAF{WCcMR~U& zMD_hQa`1+37Kx(#;gm5{qIjTaxyMpwtk&aBKvWiT*DJ zOBNTfIGDiPilrvZL>V??I{uuOWc6tW_1&e;#~Oz}^`JEl2?|)_uy|ke|K4|;3!GiK zTJ{6hIQ&9-@+aFlSMy!tev-_;oZllJ^7jRf-mT`o$qyW}@1nKpD#-|MwdB6qKdi{To>vbHZcEebY0L~YT1e$yrhfq zHBpIz6!(j2AwR}2hl1u9Ul>MI_(I?6`f-tv*za<&%OQyAS6v?yal!suU75?VbN0t| zB`zmkmamUp9qiSAIc5dXVU0s-6;n;uNA(K3L~9)O{}vN{di7pug7R?B z_g9&?QK5>^&^cTvnJKJ7L(Suf{?L8q`A)nM$|r~CknfhFKYFZOv%c|TJ@=pbV&^8)&+Z~3M#aLvFM_?oh@l<)cFnbs9@E(AQMs%B)Jt&^xZFSXQr?C&>tXeJ z;8yp1dnMn$4VydJGpq_$kcT&~=-F$o9@wS5dapMDyW(AssZH<~h1dJ*$t4wD{nx)a zzCJ7OIhTDKATZ$-|E3%k{|evSZ{zFZoHOBP$+1qLo`bLN#X4oVZ!*?5z2Z1Qe&H*8 zbDjD6UN2wY3+|&jr&kxKPKkO=tiC4!)oe9;TxrP} z&aDZb*k0q1d{Ce>+pr>BiQhM0eoAW`l22pwz5j(TeE1YVQI{XU&yNaUd$_Fi<6q%3 zzFh0wW2{n`M#sPEKnYgg)73aE?z8i!9} zczNRRQ7P3fJP1^W;)V}QoZ~Y+=>@+h0M+u!OO(ae_ivA=aj52N94?O3*wPw@@aF=2 zJUWbZSUlI`2$F1Ayl(OUz|ajS(OFAWaXQT+T!O_7xxKoK+hh&-sby|%$+!gU-d3T; zAwPYSp4UVriX*?sCCq!%zXsSQT6y=9yG^k^+Uudw@Y4AUBUIWpvz9* z4NzC0$;P^e>NQxYP^fT-+rBoDrQ+-v?z{LaY3KHw+CwqK*hMHO}4LsW$tOy zW#2d2j0(R*>l|LvGNG~4ZI1rT{3z5or0+etU;3x+cZfuphV@S$@7`n%>7V8~+c<-n zcIAv?@K{}-U-~$A{b|SW<)iFr{i;c#*qZGgf1F+6GIsT#NXYdFUp~^ib(3S-JlO_F zat~WExSzh(MVa0+5*GLGtqgWpPJucnMHUdI^b4QYGXjdFbC=4puny61#ppD*s8<}Q z$JaQ74mA#2d7x@BiDihdrN&{Ahdy@zoU&Ia2RqhuG|#z>RY(ChNNKS!47{T!kBQVW zSr{%ufD&pP;{K)fR8EOR(PlAp!6_#_TpO*g6*a*bTI7pCR~pV4|k3) zV#X?!!QKYRcR)kCa=o>9jnqC`=EqImZTqK+l}hEH0q48ulkCYa&&VY_BZfegVu3^S z!A8$4LPn(fVGB^(oiLe#GCWxHBhrP2Zr|^aj$W$+OS~a68l2m@Wdkt&jK7eOJQ1Jd zyhzWk4*#^L4+RR7&^f%aK=D?erN-fKl|}XO#9^s}p!!U-#v!s%xVkvIa#>_4U*mAG zZ(d%EPhJtSL&;VVhZ>i;S1W_!PuuOu*-`|m4_3z9U0K8f#diB1>e7Ry2Oyb`H$*O- zj}N6xRR^G^%%ng?`xR6!^QAz=2@#gBwAHuJ-9j8%*EqzS%xwje1zXAd4cRv^i?4Aw zAeS`%!Ln%@BtsJ;I|7CAcdTnX&jUT!s2eWx5~kwXI1 zR_p_H_bIoS-eduaMjjH_ovbCQ53R!rJ4APpg<>Tqbw(O*mqdy(f$Gv^dz3sBl_(*g_Z7GLXpO@yqaIb`a0{(*Sg?^8fP3Obs{fnI1}#I@^vEJsI_ow| z{bwgW4FN53c$D-}23J)j`K57*S10l1zS6ew>sMPZZu?h?;T+T@5t4V-;>^~kRO z`5H)+g*e0-hw1-?pA@SV!J~Hr&+wX82ZtTU4_%yb)A{0t*T=uFBz7>Dq8Pz5(q|W7 zHN@bL4_RA%n}frTmn(PcmIf;_fmM>PT+NK$A8&xhiRw}PSDLW0VcqoJV}&r5I$GrL zCyY&uc|VNYz_szcr;^M3NpYxls);U+z695%kzEsM$Tv4xQCNoKQ6?*9H?L9dolkCJ za*gIQMgMtvqWW?b9}~gd6Z-zN+pu#L*=>}9kBQ%+z`}+Y`1;dCQ~5~6O2dr!ltWl} z5$J_FeSN>>^g_bees{jUPN4pEU*DSs)b-a;qBz3UWnEA#!1v0H+2$+oj^T$ zeZ8sU?CB=6RS1>wNfl?z^&Jx$w){rLX&(7B_0QGRw^)7bno;kEXBz2uROm+&1x5ha zrHW8G0#On6EnUK|Dlp8z?R%xGTI{ENWtnJ1JRHRRQ$HJS64W{?wW($lK*t2KFK^`7b?r&iG6;ap0WjN5g) z$gUYn$;s+=*RM_!^4OB?>-CL)W>)czj{0;=Wt=?VI#xX`FUVgHb?Nhno+!CkvXng9 z3Zf?9diuQGSnhNw-X2_Cz5Hu(L)H0YW&ToB4&`ZSmaya!`g2eHnnLrIdB?Alt@%sS zE&=4}_K>r3q@iYKXJoG>XWKI`ts07Z%q}ozw*a?yX?hi~dCmNb`1Mxb!^Gi~0c{bl z(X*)c{FFB(J!r<#wyb7>2|qJe_U_`_I2W+4qj}zFtC+h2#nEH!3h7a;Y+CjxUz1ky z_id7?$FStr#s%!x_*)o+G8DFm~%TwW?I*%jB&ok z8O*$z9o|5evd4Stw>yPrjHfIj{M2K1_BdbNbkSUz*S5lS+6q|~B)NxYg!C~j>8)5< zCY_rd7zv4QPffQCC;u|xtaN_%peUH&m%UV02s`c5GCWlCYfox#pTHyi>mY^9hh3Yjs9Ba1od{i!q9R{+snY7!v{OkW}NKvK#ju%7?)E^#nB(DtC@>UTIL6?TOqmNj~H)Cpf9y+0wINAEpwQh z9wjp#(=b*@)?w#FfI8!3(&d>j!y!hqo$@weK$W?B&UR4~X<1a?F7_jh%=yp-5q}Fv z#}uuEBqEBnqPt7*4bCKJGF6Gb7-M9@aKs^TG|I+p1CA)*0vFJTkl~R)Yn=^?<1n=5 zGrI7p0WWDc|? zfc%v}QHJ-lR4R>oDB>{H@e&9?ZKR>02ox_-+~@8$f&ID_xDe8%nG^fgSXq6n?J;C8 zzQ7!%JDi$>+@~GKh`zt`K>Y*9TnvwcR539|JpFl~euO0Pr{UqQkr>EE-c-9paeoO{ z1T#0z5unK3L?eGWOhsu!XG-@{tvh6aWo(QPVvK#1hWQ`l4c|g(cRsLi3?K596iFlQ z*>1;D#NlgoJZo%_oW%Eue)I_{t)zc=xPoR{Xg~t(0&{m@7M}w%$q%kiS14R&(GrPC z12Bao7(8(#Q~Bgjh3x{a`!P(dh)Hm1de$mSTl}?FAI;Ki*6E^EmMqQD0=2ZLZ#8!2 zG+FcMwqR=t6gSDwV*RH2fH~T~$=W=}_$WASw}Y~d4klyqQdhs$c8P)|V^BM!x_`ZY zKVRM!VFU@%ypoZe1{UXi~>c$Y+$OejZ9FP zF(~nz=nb8lXo>WBO_xyEbO~`wd@ik z_S=xL_RPt$FFFpTa&k7BH-_(t1Mvg&)-ME>uhZ&j2VzKmW;);Y9NiTbsD)C-K}ums@#E0bn< z6VdmtV!YCt;}`}0M)~?INh1E0$vnpm^^+~_TXnp(cGuKv&Qz%as&C9 zvf(vReWu^MylaP4rGZbbf5<-cDaFcubzZL`|F)l}BH?wJUZB;-j^8)=c&3SID z>D=ruKkBuT4Pg{j#j2F|il@R^)wbTfvVfh@tJl;f$e)YJk36OcIIbD&HM$zMtX$Ev zKlwu4IM{z89Cdg>~t_TQ_93 z?y6gsp+~$fRoWp{Dce0>S7cLlO|rYGR`jF6WkGX^?crJ`s=kB|BhlDqHs{+GUbEdm z9rQ&`twkbLeZI~2m0br=Q`^=KO*$yOgD71o(tC$X2Ps~Dp#_Cd z^wLB`iYU^n^eRY=B2{{S(HY-=@%P>P-p)ERXPS=vckNqjva$RUOL+Uei(HBUt zM@9C=Jz_rnOn7WC(*9In5STV{p#92q>}mP24T{v6HRs)u+pE__3=ryxJREAmI)?1q zv9uRj)+-{(2T7z)%w57VT;lVbje^xF(4tE;RtE^MwZ(i|332US7^@HW$9h`sV@bTM ztGuwa@f|eIxZ6m6?J&>Leg8g0XISM2{ab}$(ma(W%-m|DcT78V$uWE_Uj>>i?Q#A0 zhaWb@H|<_PHeEs=OATzX9Z*N8s8M=Q8m1DX7YsCwkj82sh0P+&!m%?<3R-rNmrZj#+F zeDawn;qyWHB5OlnL*U8G$@)Rl+=;@#p&~ixO~mMF77-WDDsNE5VaAvOtpQraF^?>3 z*lNDzSZRBr(k3)1SPB|bB)KUUJIuG;besAW<){d7=po-LiWPMFKJh?qwPj^hO zO)h0CQO+}_5~YfU_uPjl!iwp3ziL~<_te6&t`w6D{gxt4JLlW z!AN4IXUiI3qG;F*nA%OCy;f4@P%N?MVg~O{vGf zSSCu-qX!RlF3w_KkLQIrZW}FlzLSUKuO%o35n@zYi9U6h zNQSzQaI_KaZS_U7a)@^}xm(_tsLb?y%&hNr);$!HHgx~3IQh#~XoC-M>LZ4iwX&zE zWwi3Cx{Iq-_RMQiV$BFj$p`w8`26SLcZxP;4Rt?qzV$zd<}{`D3v?YYc>NiVlGwYq zCKV$#T#7I4CqR5C3%cvImDJqy)>;wMC>!o*lP`(q&`amU9CE+2**f_idadkeYYU03 zlTVA|sg;!ZFp@2vw1i?+yLm=`=h(>|))a+~8g(sy;eE=mr?w!A*|9TT_a(hPy2G>{ zSHOOk&R?C4#F#w*1>y=De4?58V3kXG1D|9FZ%lFLaKgQM3BeoxhrK4E5$0Y;79J*- zJ>b}(f7HIi*v2_a`Ffm3C+Xh3;ys-tgB^VBsit#J^EBC_S2sfy{7d(x>N<+WSXV;A zt9#E+Y;0Ggkm)al>8U`(-oAHa(u1TlYthTTC}F?rjMbmOf_`Q4AvhRjGlO7C=snv! z833=W-ozKn2N-F8V6N%!zP9W0z7?~siO&x}oXy~Eh0#2A>*c^&TnUMb#K2(d`q)4r ziAK~UrJizZw9so-34;j9-w2;n$;g-053=P>zczvrP~8>W7##88?NKZ%KYxZ0=%5)l zD{nlL2lx4pcJIq86WCzu*BwPX-D5}GuMg^griOI(Ic~C&&8?xdaTVPJZ8E0ac+g%1 zakXOVN%`Xu?TML?3M84(s~1%LArd2c`KeczC=Ip}Z?|k%VipEZ(?~!P0knmfhu7L; z2o@rxgE*bn-O!c9>~Bhm7Sks9;(Oa4f$RmvTE9|jy^H<&F|YY#GVnSu53kkkqCrLZ zx$vel?i@L+Ca@ygFO&R^qA@Uyw!0COCHesNICng;pfV^%-sLI}Md^}yJ^{hv{2}$R zdJ#c*l}v^~Rrq8~%h%Q?_1xwSkD1UrrJRl8{6Whu$Jny0Guw3`kBBxkwi4Gf7wS4( z5|1_+`h+&cEDE69Xn*$7fSmlhfl%(x0VGwn-ICksm0R5uH$L~n7@hMSPQGTgs3?X~ zJ))?rB3NqlS{sbo>0$X~)Itgj>K2!REWOK&FR^6bV8K+(BKt3Dg9UBMDy4KU8fm9i zwhWr7hzD51`(FW%t*UexD`{jz4ZUrU4YF=?s^lhB1K!B5@SQ=2=`Gw7AH9A(aCh?* zq9+pN{q~t$0HPrPaZ(#^xwRKLpUzq~9!W*(F55Sg!uEV+k76|BBpV6ojT2hypy|2A zQ+K0YwK8EKl39VB&t)C_nzQI>N<*<}S-L!=tpENRD?CP6s$gQocp2)fXA*VoQGil4 zs4MaPonW15<0B#yuchU@nxhn8QIq?zGGG17EGTI*XF+A4CV}O`JaCJ?XeY;mh7T6s{>3sH%C42 zoV-l)KiCbLrl2>Y7LLighwC1@JR=I1+fdMhzQ7FY1kx(xbX-oJC1$8y}&l z5oTSPvrx{tX&-)Sb?aSy;wQaMD{<94bAC3>o-1P!9%sC)9U;%9n&gBp_PEnj3ia~O zGKxSfYM6yXgE*U2wkvk(%2tBp6ABgr+75FPCg&ESj4<(~slZ#GbvV#0i&2I2YY=u3 znm<2sVD^Z4^0r^8ks5mD-N;1uIIjF=KBc9xOgFR}oX7^JEfwOUwj;y-UH{ssxG|(? zyZzBjvRRw>5o6KQ()ct#(z#sI_l!Nv#n1~n4Yq3MrBl*X4biXeNYOdxWggqA-U*&) z%l&y8)6c?FmT>-LszeteHg_^+LPvWVUR(RTa$y-!kl~}>1nED0JPof2nWFxk$5cbU zOk1|S#5{b*A+2hw@Ug5PZ}=vnv~Ms<9spEJ&^t1a8Mv0OI=n0jT@7k}t3`o(ZLj1D z5lz3A*4N-RBpt7=;Hdql6DNUfZfQ8w;~;bkL@&Wz`DNsa|ut%4{OlBC$w#+PeEDv~vBzU{C@5-TM*U-q`8A+fG^Y(0~< zM4cz`@p`e}az{|023e#`FUQIrykyHV|L*9liNvCuW~$7%IbY4~tI~B%@@41Au1oVb z18ICiXLe~_(RS-xOJvH*RN{kGgd#vr5+U<#N1|pk>Vl@U+VL3k<{sD_Pc#TC-4N_Ide`jX58bZs3Z( zf1E3i^pla8U_HM!6H_8nP3d7%rL{bFSBW`^#2!!5vZSQQZNek%F4k2O9`4(I zf-p&6T6W`V&AlRm-aMXxciFUBXla~6`ed=d()oJ{tF6tC+ppuAwy@r8UZkJ5ZhKzE ztif#o920g-Y`6v6-?_5jnDVw%o45@`&Pah2PfZa!x=(>jD$KACW>t=bp7nne<=1hI zn|RipKq-EvAE>5HD$eDcO(+)ZX>|gN@)1Zoz7>>LIg(yQzmyzzDo7k(Ytn!m(2?e?Xc`#*~hp z7>-=gEq}9Y1aFPU=bGfp%f2!lRIx{`m8N$_7+utN=LtW7%anx0ifMGZ34ojh!*nHg zsZM)pcXDKgJ0_n;4azdMvs$U-qBN`-K*|ygjT5a~%3a)I>SZ~IMOk{K+;Cs9_(K+d z=&E?IYRfoJYudE+GTN8%EQ+;~Jrh%_e=_U1VFN)pDD^(^Eq?Hlxg_8I8N{<5!!{XnmEU+OM>oZ{BXLEpP_V=}58a0cJ|M&vuEv3)ADU(fne1`AsMvS>wu* zItR-4uj`$vJm0Jp2w$PWi(|x#!)bf?-9qi!znhYX{dYrUiF`8#!`|;k#_K@Fdxb{y zyL|`#1NIW|KVl~y0P=T-*17o*p#W^tQrA~2SHZrIPX`a520%na1i0#+WA^RNk4B3< z(Ni~3zOALNA>7URb4VdT}X&>@J!kY zy&sb@O>gP7P!>m{Gr29=xG56Tw=vSNN+e>QNFKQCYKBv5W4Xq(-*i!?IN{MSwM+76 zn3^|}$ubN2OAS!^@h<=5O{2Y}n=gh4mDZJ)u@xlppbmcubZ#JQo&LSDBKX{lvVcy?uzU5)J2BS zDU0Ooqz?_1=19;QPQGn!@m1x|FaQU4MoCbBSZ$A2VX@>kN~OC~htRLKF_$_c(!f>D zWk<=gG=Q&wR5Wx16%cK(eAa5`^!Pbq7v|>7MP6|Pv*zG$UO#F%QQdf8Xr76$r^;5@ zKy4Q|8pg1%)2(rOvOR5Us6$8;6MJ?cf&&2D!Uq5hb#QQL05kvq5#YP(k#5p)f>^b` z9oS1hHFsxsFwEZ*{4?sWk1_nU12Dn%R3RP?&W>}y6E~j5Gebd+z=mB>7+qf=|2=xmdPj85$Hy8^2r`RqlJ@pGFC=3XL|056k zC5@@ttcX)#wek`0H zNMHD{ClZU)#v(5-{Xei*unQmfE#v%*vVTqzC3FP2N^jElP zB%9_a){QZChmc;vwPCyV5DysG<9mwx+2J621Di9JT9WhU0Ee;L7z&2LoIM;bx%{!W z_bN>MlU@P<-;T>G+6Oy*CQfj7I}f0<8&nAP<5bYo!|`YTf6X4>^78*RxuO4%r44lm TunGYH*RUTjHtAFjf9w4VmZI8d literal 0 HcmV?d00001 diff --git a/results/tables/TAG.xlsx b/results/tables/TAG.xlsx new file mode 100644 index 0000000000000000000000000000000000000000..edc87b7bd9cd94ecb40c72dc35394a4bf4d281ba GIT binary patch literal 46822 zcmaHSbx<7N)-4Xf9fA`G5}e>J!QI`0>kynEgS!L>62jmfT!!Ep+#M#k4DN38_}zP} z-dFF{cl(d7?&;HAz1P}j_nf`=QddGmB7{RjLxVHU$kc`V9~;K&v6-8-lRF3dKl{q$ zG1Xp9%%D>dneE2|7kRY2qE?#172FRv=J>aA&Ra}xCfh|fg7k}=mn{bRZlDusO|8CU zb0m?Au`@O7it0yki>r-ftB2`xbfp=C24sI~BM{{lbs+py%sa`8*J9|~rZDhdDtss=&=t?g_{M4_zFL_<WY);Vi& zN>YbLRdzql0Us0Z*evdF-@X{TenFbUQCC7mGe3ef9=rmega8Mp{=Y&*@H)as8sOq# z?c!mk?dxjoZo=;4>{R)E#HEK5R|fe00<4H>qOBvdm!D`Ii}VafpcWNwX_UQjeG3YU z{G@}1#`gt(;;(!4vDH~im2+KKRDY}SReiR67m+DB|Hz+-?T-P(Z<5^%4NhrD$R*B& zD3tl&IX6rrn@gj5V!!KatFw&y!wq~aN^E==829n5HkaPVZ;9=zDXeXDuHQ8aXd^WAR({s|KJWd!wR-xR5$}S*jXQPVf6|mO!cFIm(_QP~~d9$KhmBtnP z`vqI5PRjxcnKYRPnLhrzw*o$5BkcZRhZ~Q)4lNw?Rh4~;GLx1uV}UDKcXvD#_TKlo z@!_rHb~3_)EYwh~Q>Zu2grzRame5__8n;vR^H0$RZW1Jyl{}}&7f=fIm9YO_sqWa& z;@aO6OU4H1@Xeaw6Y@V)!81r%I>5uheMSCnRN=l-Wd*QQcLTV(b6B{#{=*Y!f(zr7 zr-+SC{5r?-(5ONp$rU72Pn;ng#AA~|(DaKRU5Jn{6^F=Q+Xd;hGE}RCu*Pf^mP$C$ z@TdjD9JR+GO%~$FZqG3FLp=Rza=+2+s`JzX?G@ICYa63@hXIQJx2+h(xy9iHM%Uau5QlJ=CkTER~_(Pc!9 z{ZCUZ0dCg+^2wy`*XfJ<>D4Diza&e+ zk0`vC5Y>1S{SLP&wcVKwA5v#BeQ_xt-CYJ?_lKD?mgWm!s95WN&Vm@{@v4Lb~JG{vu zjDqz0l<%2?ho?!pXMHyb0nwGO=PhTLTIvZ7^S4=JbOs73&MMt?iLdoQR8^qAyM+Ow zSjA@|^6-lXfiEw*_qKlt;H~kcYh4>^>p6Dpz1&+(lUqhd3^H?ycKl6@Yul`#BplBd zL;hp?4ciZh{~)UkU?(SkMV0lx&Udm`WPO}C{v8#)0d9_;0RYE;(EU$@lypSk!VQNh zX87^9g1>9VnJRWWIszr+ZTMqb6$X{(o^MfPOeFhyvwQq3Rv*o6I{w~*7C-0n`5^0P zgh&8FoC6Bh0ng7D@FDtszgpKdx`U8L{yd=ykNJiflPhdvs-aW3KYdS*>owKFd-w39 z6*=oT&dtm1P(Ot=Y+%qa!ZRKOQLe2+pB~nwnV0Uft&=usLg@^-Kb^V+p*LgLOJgUw zm#Sjbg~ZBS+-b|GBKuO?@V&=`8nlH_>%w{=50=cBp7Ga(RS1uTcE{uV69$8!T5h``7sBre*EnVeew=&hh`8bFqK6 zcRAK`cIl*@aC-Z7D67BB~eTgH0;3O?F6%rCFql3ep zGb06LLwH5rD4Q>=#IvoMS4zg=gi~_+S-FXWUm+l#nKsV7*;6w=q6zmoO*B+9WCwZNGD-Wcw=p}CA>fLvWw~6`e0aU0mZ0| zDH0~xEXu*DJ@T7Gth`tt%gJ~`4u8U?BFSMo6PI{ikN(#tF1df^5ir0cWvBnkk(tF=z}SmR7wyoL zoj=7HoPY{ky`POKp`(KWbI9MFl_HAy&d#~|uj>KLNxn|ubWRiIT=6Fd<)al9;?E1P zmxmF4*yYA$I?(^&4hpyimI6BO&&~(bfR6(MIk2bW8Nm+wj_2Kx(^K)6<7bW>vB0~_ zCfLK-4g~fvlGEXT|4e>AmT30!bi4+HJvYIgPFgv{U!HrbPdlFmO4h{uzr!Zfa>QT{ zFW&cN;;^Tc^ffV{53Gp;2s_)jH3Qy{GZA$>UO$VA1wM`?=DggW---hreuH5y>MQ+pCLZluj@()8OFN5xX2;)ySE$? zOX8@8F!&s$YI^T`D$Asd(80p`R~AHvUn&B^spzy>h{JK=-7C7vUb3G1LaNwx8iyNOE91F)P?QDbVj-HTodySYs`!n7KHsxak)ACuvrV^3jzb6s7Y-mNC3Lq{)JL>+jUmwBHpt zHEiI{YEif-4SOBrcI;V;bMzDyxFlMeo|+nmYcze?;WYE{(bEW#eVjgguD_#QySqPB z<8pkrZut+&6UcY=C=Z=Mz=`9^D3gs6XE`ch{tFq_%@ri$+(9=m!{2)0Yizq4`+)qa zdcQped((F;K6)P+D#dW5A8+(?+ngSCllK=7i&t$HhkTY~e=U|C=jSTIX0d!%m^_oyX_es=&NzKa6=2>)eljWE*KFy|QGJ zaGF+mM{Dz|$>U|`wv-8S%6!7xpOd|WU{2B=eapssCV;r!iK8y|ggN#GyC=S*Dolp2 zN1sg6m2wOuG<`8nezsF&2DE(l!uri~`PD=y@UQ`owPK+GIx-k&l*immhtS2h{^{_T|lseBHXJk>Smg{EDe{W(fZjCe-Fl|#)QA@!s?55IP zIL%dgUM;Q}v;PS2+d>%CpvV-danoVuq^THjtJ{z@;%TOc&|oy-dF1%bhjQd@lE6JE z-X+_BiS`y5naGWv3aZ3Zg7|flt(^}4;>RB#<4m&-=m(nX6?aW9G#3Yi3v)UD&ry z+nd8-Bv>**+mZy`c09T<+X}0kG81^0S#T4Vxqqd)Y6^xnPH@(}snEe|D=@8VpG2$R zLMe>JA=|5~f{#vZP#Yn5R0wS}x2Z1@W=V1+L%cw{2Um$=9Lt_|3HTO**!x5K5S((@ z9<%KWd(Z;k?5>y<8Sot9P6F3i)ca62OA+KHivq?xOr}XCJ8RqPC$2Wph!Khd)Wo+z zW7tx-N929KiCfHx^NCb`1H8fJ9~EoR)qS+BD?RA>!0@Mfk{yh?XH0J$mEKU%wTel; zgo3U$ceU+0%FDHCuEiHD<`S$Eq#^la5pI)`T8knzvlYw5X=$o5I5Da9E=c=zJT2_r zF(F$a#fep%-HQ>B?1vQgKOlgFL0T?N+q-tj%LmJC>)dh6Lv~F6D4rnuWfY?fms9eG z0!34t=W%U)FEfmO5)61LGJ?f`uKs%#CkG`?)v>KY%&YuRLln3bGKo zL(jcBrx=;@%VwHOH0{uJASi@cS@qj1S742fMkX6$><8>xv0T@p!ao=R`6BZDSrDeA zIMujHcQWfWoMVD^UbZM->gOWHyb^N__@ZsKOtlxDDC(>9R%;d%#!_O|oLQ&MTSK+r z=q0i0goy(P3UXwcMQeLOH!Z4SSaI@FgMvZc=Ndy-VdQH%@1jU*j;RbrAi4IOk;{k+ zgV&n8Y6NAONay51+nz+N^4L#9aD49&B?iJ3Gk|~+CnV9_5Ny1}xi6aGupl(-L*`$% z8cN9?t&68XM8rcj;vr|b7w@8e{`c$ZVxf+2WVvfq8)=&tG^nv>)iZnyRM-NjO+9V8 z5?#?|yryQ#ZZ%H(grVYrNLAXblwH|Tsb0G{lYV_8Q9#AC=RXIUVy-zyh6Aq@fD%%1NBJ5O!z8#xcP&}3I2vv!j%j+rYd~sQ!JA4r=+X) zPh=%_lO>&Grj1UV>QnsdHW_k{5+NuI{l4;om00A7@2PU#ZY#ZIW_l{YSOOJ?ivx1j z-K|e$TR-Iu&+r8!j|)wJVa{^yr(Bm=74eH5f)Vv4m*V6arJvViqp92MD2}NJ$N8t+ zq=+n$bQ-pJPOf<89Mr2hi1Ms`Rr18T$e(n$<*JmU@Y+5@8>o+3{NVAr)M0g(zkkWj zATpON_eo8=r3A@LeBJ%IV_C$97d8uRRQ5NumwaQOYSOVozOqE0iU=0F_eyNT<`&Zb zB72Ai5~1*#%xj#I;txvI>`?I-0MWFr_f9w;?w!y93<)N~7d*O|n^^B2AYOHT#gaM} zMv6)Y`;D&)BHFyGHu8#J^rUUfY%9X=9dTS9?kO0>&Trs}o2J=1+!Awd&{*05%42{o zhYvp#$d?=F>^P@Oj$3XUt`>CQ*}Mp-JRaS{x>L(7?De0NA;cAY3)y0tx?My(y%8s#~D zr4_y~TPdnhyHWgJ;dH`Cfxp);T2k0%lQP1`W6mA`X)Ja}I%Xra;DC;o|2km9b}MO~ z7_T9(uM!&sV9!XolaleR;+rSkP7;2_J>vcTIqeun6Q8t8H(4=c3Du*D1~qM_WBMqm zkM~=Ee|}MZss*COIIp!(Ci0N@`p-$9mP4~9bLtbmai?gGb%I6grpm|ENJc|kfGEn> zkv(D^65Ex)ho_W0E%Bioi8W1&$|b4!!7U<7g?{fV=D(N93&_*{oG4}v!b+=4(vaL+ zpQXrfy%%4B08t+$4qC*Txr#pwl@@84=uQ9*%g)-uinOm-9-eyy0V)QPcwPM+B`%vo z%!tVwS_jkFgU(uvxxx1XOKJtXJ85{~Y=BllU(XiFw_hw!5HaZVsns_+tUq=RQwPJB zx4fGi&6O5jm~WW;m=Jrg`bCP8^ik19RqIT6zsqUWO zKSZ)Rt6RVd=zxYdP0EtksDbh#aRju(vrRlHEm`y;!C58yvXC?%48FnL`&_@sA|Hg~ z<`Q=vkM9**e6CzP`=b_4u6Dh8tE#i?w}4JUm+7TLj&Ic`Ak>|pM)FwjfRj_uh|4Na z2rVRPCEylBHEq{+R=o%>UgEp0@(m&z91~YLT4c#Q{qSNwFl!C+A+RmjFo@xJtoFcphR(&^Dea{*3owCT9(N(bw?xq1FLcYmS4oZZbb<0B;Esing>2??ee8FQ=c8h3-EjcP*JZQ0-sulah_cXp%A~e}px7pQO=lM#?T#2#qXdO(U zL^oYAMVn*lI|PD0pDbpq{|u_TUC16!RI!^nAK`#7DT}XQ>HRUBJpJocS>+^BIA z#JK{Y%))yhws&7n^uvf`7Z24^PXFG)JrE?=I}@!uarC`m>b^ga?>;Da-xriM-InpY z-h#oQLBYS%$qCx&03lYMMhY+DA{jcPT;Bd9TttecR*fq=x+~%SF_j(3Z~NwcoV^`C z1CKY5tSUXaU2@rOs=JIi$LYnEtU;|=$sI%~HNv-@5Mo02xwln7@h12<+uQF$LzCT> zx{NIq-!jJ^WYkqn`)r>=jnLev!W*F}$`fadRlMZIHM{qfjuLmr`D>G2G;?AE4Uh>4 zPJ{Tj#$5Av$LY*dWDR@{9$ydo{7lhE!-u2!48>{qiN30wiuP3nL>`lu9 z7giCjLca`x9Okm^0RQroD!5(8nLkb*%KNEv>5CpN)&6GBM>DD9+{bZzBg|oV<7A<;*lO@L&(ScAP&DdF`m4DmTV@sdkoBdMS$i42R?G9JgzwL00^>YVep{vQ z*)^3UymS=9Pt8l7;I}0Gj$X$c)!aMr+92+7V7%?08p^p{|8(QnIlVg-;uadvx6=G} znNvB&YL>IYhz$$t?dC@-3xE6ZMeEy zwA@*FGDUDs*A&vXy2G>-jy`gnh|b}AzN3!nlLhmguItW|5|?4RdJ)M@RvZ~ruoFhl$6WNGcoPci zsm+Z;Xb~RZjR?&qXzj!)@>ftle4GQcW@_95K_}N>HfsqUAdB7`6sWgstXZzvVE@)ddq2;1te+t7zzCsApCA1t-u;OQwc`iArSc$I$MO9>e{;%C6`!zw7E z*q{h|dXhKgn|M?s^vfN1zriR~+7&IRo!R9Ik{buQ5J+8$$A*1;|7okv4S zrmSQ>*SUUFWvFw_ukwWGl1M9kRG}YZ1OB<<@Q7BPb2$Mu_s?!WLjy+Bv%MbBQ9KsQ>u{G#iV_s1r;yZ6A5qw-it8M~ z8wJbUL4Ty*rv0e0CmNP1?l{^m({ZLejeQ=MoS<|fR16CkBamo3{Nn~hG3Bble9L~A zZ;AdzI0G`jAl}`%DqjKmPdWE1Yp@ z3d}bBj-m{g9qB>kvA`&D*=&R(sCI`BpSuJ{g$SV^Z27a zF$L@i(AKIHn9;t-DkQS`cOeDTT3+ab`lZ3y(j;tW1uF`3`!ANqJtSW@tcb9wel(`5 zYwzwHLkUA6GirSE7x-;Uo<_W()aE{JWu*)Gj;o4a?y>PZhb~`{9E_g}q~YklUh{m7 zOX(e%WH=~8=Uz}|%j&KrLS7Dc5AiUo05%6vuRJ_aYMxRn`2fR-&_F+cWU$IGwC~YS zpt-Aiyw*jnjrN;o?u{dP6;GY^673|BT5@r+J%wo%pvK1M&j!)Yz`=_G^z)<~8U_#k zs9x%lvwSOcY%HOAh8@d1Im)-;Vgbj#YF0Bmr8@Ql6YJ&6UPtle%1ix)`%)_Mma}z| zF*}jPr3E$93Q&yr*9`mzX*gTrF#;PrkN2#$OMt6>58{B^re4)11q0+_A=_n!OoeX` zRJ_cB{QNUI73tp)V}6#W3O+w1(^+=T;0TK&c6gePHnWqEt;V>ens?Gwl!7yf`0sVU z1v>3NvWQ|q%HX^ZDWwIWDl=T&1~rLCMV-cVd9l`an5gbIBbx8YToj2Jk|8TTOsRorjdP!u`kx=cY=VnA4Lw`#ukc2orJo9 zdL?%uTf6Ddx|(*c;J%qv zrXIaVFdLigw~UDV^?-TSMY}lML+llyj;pH!;lxbA3VU+jQbLcRQF~fvvR}Q7b{Qt4 zfhAbUpd(+Wodx%8quuvYeK#tU4UeKGCgH@hw`>!^Sp0d;-PzTa4Hc+`F#^izCGjt% z#M`!!zW%ubcv+IE|Ew&LR179{^KU%u)FKfuQWoTv3CJ-*K*@?n=Eh4|ve zQng);yX3!uu12aN3MU|V@^@P4_KZEbhFQ?I$r1KD>ct{Hwabo~KXs^F*Zbfs)|S#x z7s*qtW;u#VNj(*bl_0};GG$}~-=kK=A_a0kFuL;awAZoUm;*J^JhIxMV=KlA2B8yN z@6&l3k(Zv~mW1`7cDu`>K7pa@;B*7gR|lUN2iKijw>(Hjc>|X5tuqH@fS=NGWV`=T zwWu&lA6g}j!v|t#@8w^N4Jdu$RlZ6dzSJTIhMM!q`|5AiQ_4j>D~N|b*{XNTa$rn| zbtDah-e}v;l5JoADnFxLX|6}vu2MSTV6GpaALK%U{rzxOBNB5E4?hI96!2Yg)wWyt z8A;zqd}`z@Ne>|92MezFK)Xhu;K;eUs0i1o+~T@~?+)5|z1oiIJwAn^K2D*lpgE@B zDh*2!7d7NS#pOx1#d(x))7)5HnVE4+GD;u6VqUgOS>PI)CZU#~U2c8MM6Cneb*@W| zxV@YeRFa1$-Pv6H+b2LnkQaQ^UVJE7n5XT+3}LjR5s!;)wpmo^hN6(&h!D}_6Dy-aJTGLh zYWtY?Yc3Dl7=bC)DCtD7H+3vLXdiOT(@221Om@pXovg8=4c9A2v^%w~9vkCY9AI6L z5oV4^hh|m8%mdgW4WB^7MPT|Xw2OMQT{!!x^w4l@6jlTwkVsfUMB*iry=76L+hgATw%}jNQ=4K5 z{`#%I)Kf){HLZ5Uq@lXU3;jUCQI&9hl5}b0i&<#P6p!DmIU4ijRl-VY2(<-{nWmtg zT)G_|h~ztmW1h~b)Vt6#%a)ZPPaG=e+|0BR)5|5-P;C7{X|BpO;s;1i9qH0F51%7B zVm^nN${E#J5dxsRnt_G2URRi5a;g>z!VzQwc;jt{jsdhWY*wJo!g~P)YyzKhS(`0A z|I87>XZ3yK_sUFmIP3@ugf?R~tk^?%XuLRAPu6BaNe#8HgsCx%K1Zxm1g9F@G$^tn z3bu-{HY8Uv1e&u7+|Q0WA`5l9%v_AdrZ$H7hJ5qMod{_h%+R$Y#JaZkIC)*nPEFSq zBh$`r?N>V6>m<5Ne*L7%inXzv+pXv3pqIeizN=!c zBfrpb3uPN|owl80;mq^Dt(puArx33Rs-&w~3diFn0bHd0uL_Yi40%{6n1${0s)IL++3s?<`AGaKc!7RW1 z$h1e!FV=?UfyP}0muTtFh?a5i7hX9{{^8#CekNc z%|!2x7=*&n(w;{&=~izzD-X>z;Bn+#^lw~~BlDT}yuktk6yJCZgloFmHy{6?`sP#) z5CC7;TaIK25#rM)0Pb^#G>9Y!pB597sFq1t1sFFyv30HL6%4$zu@;0ICx;nGx?BY* zS?`!XA&_F-)YSxq)h>s!om;kCG0c1quLPu(q=|DYM(rVA?)90S zo3wPG`8Kbld!xJP_F^(+CK)i55%t|Yc3Ydc*N#EqT08ZTp5sV7|mY@3xijFAXfGIGC@`ISv(S za&-ETEqf!v`f!BECTBk-e66!3V}zmjg28~)t2>xEf%XOqJHjBb0VI0*Z6ySJ`A-)A zYOiUpF#;I{XY$kfw4P^}_2F^pWH1_0L7sEo_wNxVZ z%2-+L8pLg=X0c8Yc+ULvQEAoQabS{<##uxeL)5JAkDYp#e=1AL^|nJJ*!3~zjfg)f zrNfmFz{6!ew^IF(=`s0a@Xb^RS+YA5>gkY%8e5F;<#%tkj@pvT%ZzeC&Ku#a9zI1q zf1EJ-gzI2Ii%R+{J30C0W7KCK#PRS7{TT`9U+lRg3cqGC^I62qvCftx#^wBKdx@W| z?=L^{_%}ZFXm)x`O9>NA+PV6wVyvY&bf=1sjCxNFbx1nzGMe5MAxHJ99yya=5IkFi zHsLv6o-7H^YyZY%ooB~5p3HB9Z;j6G1a49qiuh!M9VcQtcuG~vx+SKnOiaO8KJ6Vh z25<4H(+siVub#QzyDq?v)46v$FHnLswF)}w>#~we$JT%Dt(!Rc9RHS~+yj?n^GmC{ zQniRqy|}9us82V%U&ic4BE&I^IMT=RBA>iZC@UeKH%8(BS!|SS$Rf|T3Yy)|zNHxW z@>($8qaw20IK0R*ppnM^gzI$xSUQtYLJD0KiKmPeMbAilSjrBUwf^<9G7^BKRvlm1 zR72>ww)di0QndUhX2se1@i^bUn=1KB4yLnek)irx+W2R?Z=ZVWB_1sxc8*_YZ;;v% z;mdozlD^&1xK*RQVHGwoEH{aLIB@ylLX3&s4!(@{iY)_Om}e=o09=^*sE%5O!N1B# zC;Oi4>1s_Sm8OFIXTFGi?!#29Ex0Sua@&W4(J zp6S|X?LhiA8|r&**vCgE<<2C2`tL(g!%GG2`F?#tp`^>W8JV464fwq6h5RT!u_>nl zJ|nHB`2D3^FwAAoxHUePZE@KdC*xy&n!V;;$1!#8dkwb=GR)erdL-pHBTdQSly^p4uJhL*Z%r?*kQj#2H-BUbYqoi~Qcx-EE)!V_cr6NSRU>&wCp0~d zJ1)@M$Pp5?)TVhgO2W5IcBqN6;k%V1({>-fni_|Ajd`i-<9)U$RAb99!5U@p?r&wQ z*=2Y@ikm4^CWktk_dXlo#zwX9-}_G@qkh3#b) z?4#_;(?}}y(g{MTOx8s734^P8#nqjn!e? z8&(#-d?n;&`0lS<&s{eP7}!)2W#;1n^EBu4Ici7L`|4QkCv22FtTEr($0M&ce3ra@Qy1iEinIc?q8M!7Ejr`s4)!?qp;{B4{1CfL$M&%u z`d+-R=gC@3HGnHxhU>fZF&n$wzW#H9CmEp$`jL|zyf5YNpn#=o->C>MS4#tK&}VBSZKf|(=eb57u#Oh}r`5}532SnXM$^Qquqg?XxB(VMDxs2w z4QhwJlY27X^ATo0qwUHk5|*0HcPHj73e#u6z5Ka8$54rnfV=503O-3qSF|eAUTVR-&_1bOQfGr!vU-S2PFF0mCPnAp%Ksiw& zJgYzlSgVKf=4O345p89sWtvR~it2q0`))5mDcy0*|L~e|rfiusyKtdsw{44f57EmO zm293>e4gxK4F|7xjC7g{{L6{$;uafo z?)LkBILRk8C-qhLd{kz#Xue!hGdn{=FeMh#$|6*%TG>^yKox^^5Ne3H+v6u_hidez zE9{iibnil0Q)kgO`1r>;x{HGWH1*m}hs*F=y9gN6@jFx!3ZjC7s-Bf4=2&}GEqPb- zTxOu*Ueigeq@QZX=M==GA;m-ONC+y>*Neo;XysoPa6CHj5bqAuRst*&%d2MI=B@cQ zfwE8V97WIu^u)oa2hI&S@)F$3mCg23Q!Mt)3@x?!2(C0En)=XTG->7JPB|eUi49&w z^g{3nd8x6`V)@U=hAApAeo!~d;L zO^?Dv>{);^WIQnwi*2wB@Uik8I$wxz$u=a}zBvpBo07=qE!N5~1qj7GF~HE*9WD{< zYaHRS(aBPdBkaYe4^HLjPnZ?Et!QnJsg!k=PG=0PVLW2!NNt{ci8k!`@S71JiuJJ( z&zZl9DmcQcimL^AE~~l7Ld*2_k!RDV>q8Coc*FydT{3to`nv}{wr_S{ig}7Bz zNEs=%^jUtuPn2X=6&o*6wQ!hg6_n zIQE|Wm@NiZX&0ITrIU=!WNho{er^yvF!A)9mpv^@DBMLLx}+#>>>R|KGb2u#~N2vAtU@j zYl(+#=NvorLVHPMBv46#$XqFztrOeYn!f}fVbKq!CeH!pBG37LCnv`z{D4&|EI#c( zrC=zjvSZLtjM|Lui0Z|%MxB9*JL&5xI3E)>-u&JfS-2UXly@q%r7j<^Xa683u!zt^ zy%a>Sp$f7j!+Q3hMV`WI+A7{hQo)yCB^wDou+OGN;q)F`7Exy)SHSCf@(ef`4%fk% zPcy(Z6V!bvP9?y=1_)PG{7I%4U>a~gK?E5qIz+2RiKOq~VST{$#$0KGl~uua$QB)ks1s ztY0ykNd{GvV_}s<)WQ1Loj6;dGp}t8@8vxK4pzmA#SYAI#8XUSq10RBZ)N^rG0Lur zb)}~l`fOdO)te~Iqbxg-}%KXh`JnL`Yh$*z#(j*G;CW0G<7eVpC zXh7H6JY+?uxn)CNZ?04xjKx9m?Ln*$@2#EL+Ri1+_sCixL?h`|1C^sLYt2)Xd-NY% z8h_Lqzqcs!zpf`EPx_QL!zx`aMebgepKoC2cx3&3-Rn2a;gd5}Z7ep2Nk3~K?3^lS z!ur~ks0K5m>2h-Gedj7LZFyOqhzstjM$PhyPN|>td=b*J;D46zGfYILf}juGe$??R zdgm;bpC&!^lTyxu#Po@p7ONe|M%k49g_o_qGwyv#%TCUeQa<^E!TYi`tmmX`P&19Z z_auYEZDL5$lG?$+?)$?X>ZzB1xdJ6L0c-NLJ=+%PzqM!oqa%9N6?oWLJ6r#I&-G7t z_OXGP`?3Houv0DX{1J3-sWr{~;|nNw0rG?9JeRM2BCrIpb-cSqcghB*-ijI zVp)8qs{&O}B88Pv%z)r?C1sDKy)mgE=xOUWH0Q5WDK2#R-6}3KZwRpwQ5jmVjVxZN}6~K3tz%quV{-wD(aQa+0JDQ*Q!S9{z z*7>6N$4?JN=l~q?Bh0qg?BH8Wbl_U-`5!B8&QDKlf6Q^jA6@y*l%H}7qXd*rZjtI# zs&308Dv)5)=+y80^{r*%htdAZZW4XK51_%a{7v8%k>M~PSs%8iqNs;U^A+J-id&-i zGf2v^HXBPD;v}o0O=D0lHy$1qJ|i(^piFeHN<9=GMQcy;AVqSqBz1|FL5qYJ0;$!a ze7kr`zD~TC!C*n~ptb2+Z!TVairEUFYo4#5eB_P6I!eX$XDu9St$u4i)9Q(DSo!Uc z;R{#=;q0&_8DJyZ6lS3rJ4H*@qx1h?P8N-v*Bqi%^X3e`Us4ROf! zcR5LB)`z>KKlXh7TZg6Z-W@eRr^ZeESISL+TA9<_u33g_N7hNa*HGH2p6c@|5)hHn z0JCFduxk;mh>J*S82JZ#nI>^9wVP$e3sDWt;>BhR;4=X$Z);OfXE3hHS<&yDPq-y~ zj|TX>8^B+FqqZ~)QjiL~-R9x`-!k7Qh9h(04s1yxfcm73j2hs&v^1?x;l647{>Tma zuD42dqsfelA8hrt%sLBA&GU8#h^7%IVZQfmVV-U(TyNHXLH(}%tFz^FCJ^V=D;KB(we>*hg5-i|}Z+}I79M(o4Vt()5Z5V_@r`O6nh!ni3{ zWWT*LYsyETOQX}KCqi%a98gSVGjCt`lVv8_MoV^;s!u%gyen-|$v_?M5cw--Um&d- zwqe!b5-gfrbJ#@ipoZ6CV|CtzCsJ1GI?00BWrd)czN9*9uXQ{JaR$YhD~z-sf?MW~ zsi{XcX7ZeHv#-?{L~JfI7M`d$;xqJ1JuKWP%}O4cqZ@g;=ZbQe`Oth4f6 zQs>0hEx6qf*gyps-7bX7?!O`S@ly6rE^ifzrqgrtrTEM$SCi69}HF_`)CxV@Av^wutR5X*4PH`(aWOwWr%P!;F?=mj>+j6OR;p)5<$7Kx4p(d?rjJ``iPmbrNt7+Hs zxu<%;+n8+YNI0XLm%6W}z3egwL)?MeXk~Q4JM8iLoGFXT+FxXp&YvsBNv)>7 z$ZOA4TzHfe$&d86q!qNH*^WuUrVTHO12PwUEy(M4F0yC%e60_XK*Cc?LpCDyh0GYPD{@0x#iXVG|mROZxyQKX?ZWgF-2^hTurD0eTg7sx;; zIf0#Bi9P=aJ~cvs(QhdP-x_V6oJIsRnT(*cMlL#w*0~ys5TZu$r|5A3wW#Axdyh;TN$p2eJ#`$+d{+}AJqLi^$RVQYU+56!D`hD3( zTJ&^#vL*$~Eeg$aSssN{Bqo4(Q^ogajL(|DBY_tu#v6~-jF_Wt)MF>vKT%o;y3NKA z71_=-0M5ksFeYbq7F*f^IW!NkpHx|ERUinyM-y#laKa8SayXRY|~b#+0_JF-rr^dHq9J0V-UA zr)_Xbe`Bvlii3;a6mJJ&;tFpUm5dSxf$bwHK{*%q^*cKcmK1$q&0+E=4Nej?&3lNR zDB0dP{N6O^Mi*XDVJJ8H=Iw@Jo94}d%mMN;+9*VbqV6qv<-e)qjI5O9dF?H!*cQ0G zKN#FP2y4d{H|yMsBkn5KUZY&hJL0wm^e8RXI*0bEcmU||sqORp!Ka>8F%8Yqd^9@~ z5J0K*pAaFJ`rpMW!@;DN1l+(kqZQb7y@n&{5+(E{2SAyz7)TZbVpg?t)h@)_nlSe- zxv00C{@L0q8dm>Rr$_q#;q`x!Dr$F5wAOPey4OPr0I&?UH=D(kJ9wlW{Xnq^>h>`e zD=Dfd4^vX4P4)78Tu>`_Vv(;(i48;DLt#yMd&@eo63a5a<9h;lIfUJ9Oqe~7v?hvo z!p^n;ooSuE_Yc3k#RG3Q9&g28&YR3&Yp{hiSo-C)o;dL9 z?s$Y!uRh=HuLTYccmo3;_b=yQPbIhF&rj6i$3XwJ2j4ZI|6}@uB5dpH-}ix!fK)SJ zw(_0tKeum1=7>LS%&hs}ZbSk*d9-~yn!kxkUF{T$!}M-K2zE$7ek*5fM> zSK_d*@n*p5UT@&z8tiT>G7$hfpU44H=WrYydz(EcCg#9$0$*UgCTEb-7ohP4q96jh5mJuw0oAFd6)qvi7{Y71`;3eV(rOv;ydO+yUMJI@@ku-|znQg+@+I124xq z{R8JtU)pc_7wG2$PaVk|*B+Lm8apo=-#P+M9d8_ue@-ks9fluPlT=mt7Gc~rg4q8q zsJ6J8weI%>s7%9(Uc?A@?xzQ;)5ZL~AH-LGsw=}59-nDQ#0UT2c%2t~Ilo+p&FK(+ zMp+BXFN)3C-ehdP8)6USV_ywy_qklTHzA0*cedQ#j5ltpjcw}xQ*Fi(cz@!71(4!0 z={qH9zLQ}Otc^8`k6r6DeYy!uif16KpK)?K|7rYWL()l30t{@w+p6ZEUQ{1Nz4;a^ zzP*XldN=d??(y)C88G0!E8??QO}g>ZdlKN%pSAu!Kq{lo@e&eX`2AqNgIIlDCUV$k zUECNNTHVgV?y*Hq*2|&zIe!mnA|A9E8tqUIp0)&|b2=9ZO*EZBbf;Z(@)oI*Dv$oE zI6bVu>3IJHOI~U#ivqpHBO)RHqK^SPo=-8_24|NJaM%=ax^)oMS^$`>@WS+XAX@6r0ieCgrX zHv7spzLaDChrRcXYBG!BMQNb~h(PEBq$gAnA_Ry^hk*1VA}U}ZSTLa|QO60Pw@Bz9 zAWa2C1Vx3BQ6N<5U|~i^6B0nhQHtZB<2dgm0o%-d>)rS6UGM$z);jpdKD+()-shbC zedk+oCWXl(+s7V~KDw>%$HTiE!tDkZQsuYHA`z)xNrJ>WQS-~J?GWiQ+|_HjL4W&| zzIW(8yiK~f#1W0gx|ez2znoI}H$mUKOeGW>GY)7Bw8;L2ZhictMWFZKD3BR`ZqdWo#=JeKa2 zq#~D_9>TKvt5u$MLKad zLG{Y}kPTMNBIl=*5}=7WoaA%(UT3#0zz%q z*3i!aKV8|n*Kw8Ey3$E~c&16DY%1aDlS}Z^F}m;K%BJWW`pPz(XqZdjs5lx1%s7XK zoqL?N^&??=-OmK~SGLG^&v(390<)_IO0W~PU7bL~H+Fy2rFX*oF;g*N8_b)5k!rK% zzJ+czrm;CU3hu~vA>domw5?X~)9oIwq+cK6u~$MjwkPS=R-B|ehaVVyOxsEi8BPJY zsucD2lD@L2g!oxwo3+{LyCbiZbdPM4YcBD0Y?!m~tF3}swSflX!`98 zsPs$nk&8JzI`W{L<=+!B545z2`ulCJg<9PTU$Bq(vo1!l(fW$$!(9Iz^pA29N zm__@5f+gHPugl9cBCpv`&zKC)V+&TA{{8`#0IS|V{rtkyM@p=BR=q~Bp)(`CmKUO{ z6Q-Z5TUhm9HS7O9HhVXs_LyzOo|MR z)Gu8LOpf-LZyP5?#+2_4FMqOty=`J4H$pO`TVCd{T3C%
gswtRQdc_{FlSvtvK zRVkZ)R6PIAYSajPH4?2hNEms+Va*zeUKm>W!)kPA(RotRg1h1TZ*|W$S&b@`&1a0P zJS?7Hh%LWnVzHw9_`Ki9{F!mm-RIbSG3D1ru=}p9oJndc-r4rF27m?3j`Q!UR?fuE zy;r_wHDesdMa!Y^WXec)_s+kEMw?xW`58BRW`t(|$h=%PFE~O%d1B^c%6aCm+;n~| zKR}-@C5-G>8nNX1^EEqs4f1#Tqq{869sEj*+34d1?7q-Q56pbC1c>JsH_w*MTMrGl zH@wp=Sjm}sV^KDLeq_ac{{8ErmA|bZ+lGnMyt^cW%HNKMn@O0+X04Sx40N8 zS3ZuB&OXO(FC(1=nG=gP+tk9%9AHivS+Spg|6*vxY;SC0Tk*+Xxi!F}0=byE_oT9U zBna-Kce?p2mfss$5{tylSDs;j%H$Y`DZem+-F|K5V>j|==9<4eBa_ARJbyQ=mHm63 zS3#aX-s!tXpT@4&#%G6CtVTVH&Wo%C?+XHu1<7c$ds6_lThzUKG3EQLMmLqs-!>b4 zvw*z^Q2+2V7xl%Jj}xS`FR=FjYM#vTS6tM9xo~8~ZT|i5Lo3!C)M6?>a8ms*0r)K@ zr#1j5Z_0Y*XKJh-`@I5v5c3%y)qt5W)t2sM z+bQv~m(3p!T2lX9mdQ45QY>76MkNkP8#}j_%D}1X-99zm=C!X zy`%(4y-W`X38oS)duLlvn>WGWD>BJAgC=u5();&zW$tXD1Uef` z1&_={nHNrm^|fQ-hTOF8RC1Y_QLsX~hUq4w^q~xTe|uuuH9Vx58bD|(9h@bU4!Ie~ z#l78KbEk9fo_c!No`z}!v(6??A8*INLX3C(5O{4cwn>0Xk}8Lu!eTZgioe~GWOOH3 z!~hTyFN3*?l;oA8t$bm=fw#V4&cmEb6W?K;RQ3(CNajj+D>-~J9w3BYC36%2d(WF$ zSgdjOuQ6PN{GO05-}ptpF?v6V8ce?R!oeUlwnbpwo^#%cOB?z4WLkjK0v>{u6ZM2Z zf*Sh@RtT19LV?_1FgQw4>d{8`OEE*GLN({RPVB9xpV|xX&DN1wb2UBZ;UcBEd?$Sa zCpb>e*4dEs84Sw^+PuS7UGp73Og;QU7PX4l{Jh)txi;T3*?@OZstthGs~n2S^aw&* z5iwR`&n=RMe+Cf&#JtM_)Qh?Dg&v3^4*?+$$*bxQ6oLSr`@Z}l4{#Y?NSHU0U*xj* zRrN>X&^WG|dXJz6D`JzCSO{hhH#Z%=@ymW4m9Z05kJ9Lma5mj9?AGvev|r1WzvqGI z@DMQcPzbVZsFqvwtH8<;vddarPRw|nFx5n=HK;!d9oY29dxTL(*807srv)x@GnX&h zH}DStiqh%Z3F!3SYaDOGQ*P&yb9|>(ztH!;uIXumi~N+!m+u?+@e5t>O^staJf%IC zTfKN00Ead9)` zI2lItsWE7n>KeNU3zw0Jgk>T5?Z07nC~r|D&8U-P;$qg>1*rEkW<@No`Z4e%nT{Cf zc}gAZ3ZL+1?h);!U$noDwA5Ehlu8w}_sekvc6Cc!C94L(C}J$}HU) z5&y26_D);<_g?X}jCDku?joL^nE5?T@HI~TNtVJ|)spT1O!WP;Ch0eL-*35mttvn{ zSgaks{NZoJQr_S)?jm9LknzzLgeNACh)=TNtBG2xiDs)c5GLH2nM=N-(t51uCGfQy zS=x<6^dODoFJKfe1b#HOY@+yy7%;Hgm^Ry(4%;F$-gj?)uif!RI8x;j0NuANHoq(; zvVzMPLc)fT@$noB4?CflGEYpoC+31@5P93?f81k2U$Sn6Hn47Kq`Vco{8p^*EiPjc z344HyPvr`5N}AEMjoGp-g889)>4P?TiEDtf0!n{DB7Q|09ln4$dO>L0(~e_wKW76_ zh}C~3-uSBq@&@kwCYL2$pN5+FeoLI`CfQ-P7K5SrrzD6sFCy@#MIRZwgQ56LJ3W8xpODlP%gDfL@28760wSjztKZ(wtG|7K4Nkq0!B#&=qy(Xkl zrP3&b49dv00<)vy)#|agArMaJaPeK<@m;&(Cn%8gYKUvcG6-E}?6f(%!-m;y!|b<- z*euv%E2uN}{_Z*zB6ZxW`*qhw*VOl_HW*q$Jc?(luiX3TBRq zf5}Y&DC*;07=jmu=oQp&OB}KlBisWXHB+A?Bdk%S)+huPWwcy@d0QdW%eBC*QkF>4 zipWKXx~#K$9{IzUDuq@OBr01li8D5dGO0guQ@}aYU|O;sT6ywRFT^=7fmLqGxB)6o z?5a$hsFF#i%eXTBSr7C9J0{+adDJeVQ>Y9u>ilqcWn zg=q5<&?JB&5|Wq!>sSGLSpnLo;F_@y1q(sZv{KirH$@S8Sv zqU4%!2n7pA(eyu)ot2^C%C6#vQPjgIY2(jiqzcqo#WmwtE%jI}%~+JPR-Yu_|7C6b z8m3aeU*&L(c-O7aMuUD%8--v-)#x~vm6{ZWJ~4TW?DsZyZbQsQwdjOnEJKayfNxW_ zS!-$MEa;?K*gKHOp@UQALw^W@?#ZmJbYOO<01+M46)fLE@!HuUz>3No+-%$z6jhK5 zpS%7|_w+F52FHpVccV5hywO%VJo~Dkl*LYLYv6TAt)=u?gz06ai z+;M9v`Q^HPaPs_1J;TO8^p7;|vB0tLSv_W)cc2Q4nEQ>GKahXorTWB6YY$<)sp2VG zcapK*RbifZSw8XFebheosC`yU=XzVkbLVSc{sXJ-PwKp5_FLaeo>O?6%Xd(##3^z$ z|Bg(Wv1mXxIJdq-3X})g)^6f%A>aC#wAT84=i_=?#W-p|d({3|v*g2O$t@F*^*)Ig z_|H{myng83kj%d!d9%mduh0B}i$WsURZ@;|6!6ApHJpkBy9d{kuL5QZ3J{z$+?anI zcBxyE(VYF5qx?JlpjYI%__dc70PDv8z?$&iSl64X@33xI?=ZNL|BO}b|65o$1;t-` zBF=3KxNC=3lfq{zey-p=wQ$;n|2=djuYLJ$W%6&t^BSk`3J^F11URSdx8<$87@y4R zJHD&$4iRPE*8N`w6c<{L_5ZiPe<0=<=AIc}Cvr{y{}g+#Rip}UUjhHFE$9DR{&PCZ z|EU0R&eZ=F_+J9-(tj1o|DRy)+427;`16+Xzj6h?6bH{B-yQ&xs~t(}J=52xJ^#j5 zPPfK=B>MU|VhAd5wupZ(VMf>bBhmVKfuJ742y7#Cf}MbVi^(`j@BAe>;fADh#xV@y z2|?%#gK~@>yfa%Xm`bqhnssrbT3IR^pCp$CUQp+DO?iXk1*J@OCZSC@D(r`NUe`ph ztkwy)vNQ{REo|9*)`t7y3A9eXE-hk*KJy2fX)7fx#o(7f(S^w{qc^ z?(&)`&KoDtI{lUtU0Q1L2d|le6-IMfr_zGb1$JWHSFf9bjW6dzKRXW2*fl&N;VM-5 zCj`tbrs!%1=gWCO2#d%=)E}kWyAGcLtBjyOBTTH@Hy7XfFkuMz- z2J?i_GL=kkmUQkAY5dYFands$rUL6TM}W-hemRA|PuTy9xDVnXm3PND&*yHI;x1p|fglBi$zJ4-s1*(HXJI9zc)A z2)GhD>-RP$=yiWcPzQ=K$23)8&Q=J1-PVv@n;v({hW%|jh7wxJ8w*o~^#MAvHDu4G zM-~kW7k~Um9WPIb^T3b8QmR#{{VLt(6!xob-&-0WdfiUS6KeF7Noc1_XH))y>@j{c zKAT=+l2Ox<20X$dsBstpKf=9=!5*uhf@!jcXtJ0ULQ7E!ee(wA4(Mxzn6^OYLW7(x z!yJLjYE=0@2$+{l(U8u+DaHy5&!ZfDiX43y)AaEfHCW$P1iw)$5x)5m5k8(?69OjK z^l{CNFz0Oue&bf6!sdsavJEcK0By*~HiXeTCgBxWT@;nu(!Q!YI(Y(b>El&EU^{}} zq?NewD}n6@qfbo2N4m6Bf{KOA7XhK}aZPoYvkijZw3Ubirjcu=CA!DM)M0%#2%24L zg!RKEqn+9i1AsxDDi0xIpfjQsomoc;>Zry%`aGbE5HYYB(b~?ej4yPg231~+h>@8Q zZR*Ur0_exvH1z^Oki>~CfvNOnDd!H!$lzN$VhL^j+DZP}5D$BVk@5@y-7QT{Q29qK zJ@(^iyc{l64i~>7<(!d%L2Muju^GKdgMK2ufsQ_4FdP5|O_;L-g5Ro@IBN=`6hPw) z44l|fluF+$?c4#24E||HtO+o{wc&^`(w`ytbxU_7s600IRdug)fnITemS$jrg1ecm zsah2x7RGyft&I0JYU(v;>Jdz5@HFWZEiEeF#_85m#V_$tp6R0?N?Nc!Cj|fYR^ofp zhvTy8HBIR?9WPR=9i0(WDn@`zV0}1PU#%z0!yxUPaSnsnNE8xc_CkgLhABrMFc^sd zgEq|B1;KCEN`#m_B0{1SaG?sgcrzL23>pTZMHG@?_Ue2kk=H$51tf3?euq|~q!~bc zg2ovbB(VjPMkmTR+ek+ScXLqh(FOzJ;fgTwnIY74ONS(??A**leFvb<#{@NWGXvAK z7@`)&`vL0xuQl~v0n|Y=_;Hz(Y8@({_H-+ihnnMTd-wQ^4y?}&!H;VtYMAj*b5=xJ zwc`#1wFo1SM_{=g;-ThXfIDXtV-RLUAwy>GMGgjxqYoI22LOXE%-J2mzoV6C1W+5T z$l{o?xcF!waUO%PAPS+Gy**z^utA)VFlP@0zeg)^3kS6ajWaOT#FnWvdNbU)10ESX z!a?n;4F<%+6Jc~}hVZsqnlDM^u^A8bWq|quCg@`~b2Uv%9cp2W2dMGontG)GHDv}b zEt{f+qVnlYw^s2`bDWjv84p9j`n(YQzO5Td>>4;Z<@o9=>zq-AK{yhHyqLXZlYY*= zsGKgn9D#WhRoJ#*)H93P&K7(J9O=0O#$%fObdU0PSssISN z6fJ!!pV4${bP2a$TLFk20E9lQ&kw=ByOlVPwv#5#zm>-^JcJjRyE@5CWOC{7x9S&Fa%I*4)!E~^$Qi?wg2hJ$_kkOn@=_J&S> zX~m+H)=~5&EAR)700SW}2hA>l5O4;$&}3^|pk29k8EqKVXrdEJ(~xh@s)!b|51AyNM6`mkGK(Ch@H=9`A2@{_eY}8C zMDGhsrWr+slh@AK78hucHe?o8=@?c@?Z#;7OPec4tBz#L<7_i(DnP&jGbfuB!xMG7 zoc1?@J6)PAkhl*5){9ZiB02?ERqAzfYjBO+hfzI8bP56F#1D2H-+>|$@LlP$mgz|9 zj$m$*ytE-kIh5s^u`pAQz5}JwC9Pwe%!A#1&6k6v)cY7MbK-Z(2QjLJL??pgQ8Y+W z7g)YvFo5faz;A$Kw5)*ZzN+BwZ(A>#tS|_>IVD>V0!*VA)eA%?^1t-sOQ~ZREjwcM8dfKsdM8#)X0MWZYIrpOYs=YA zc>eSN{&9?;&=O)Tf&WkG9h}(f4QX=54v@mk-WQ5lW;RkAJ};w+uO_0MhD?j>z#j9R zK(y1?|A7ABe?XryT`SB`d0Z$bU1*O!e5u)4F~JhMRalAwI_Y07y%GN}5q?VCzV#H} zaDnE698?pnoLCZ4-G5OofeUW1REod=^`@9Lxmh`!tiE>|)U65VWhipEPEh@ul`ro{ zkMP;H^Ofz0C42OK$OV`cL6XC*moaMDj@?YaU>9Jq+q{mKf5B1%IuWE24w;TJvs_AoYmGM<-GQep_z2wE|#gcl! z@)*acRuhFqXL`ye1N+J*xlP)aiN@96&aJKPZv+}wfB#SV>(#%{g+Re^+munm8DN*- zc1y=K?2>|@Yg|-8|Jkb-#g@<^SQCY{Hq*!-B1$! zTSb9=a>Lv<>HCTQX-(^0PZ#sM7_D_l%*C%O&k?kGj=Way`w4Dk6Vhu4UoXw|l>^$a z|A4kzI|+=zZ=nGMpx@z)Z)1@e8$90rUlW{`@jFdUPMT*K`7c)s!1EjE(7<8#Wo>f0 zu)*KBU0Cqf_42y(68Aw6v`)tB1;$DLNe^GuXW)77JCBr~Hh9LK8IBdqk}7}!8C^E%PY&fOxWef=j6Ff6x1-ad*USrTgC`B6DaL0y9q{)liNg0 z&P;!D?61>&f3*ZKl&^MdQSRFkB>or=dyE$=MBz8o@&Dcl#Ra&S8V>~J6y&n!qxQZ# zoqJ!9-C#GO&o(p;zsWv|M8b~Q-gc9Ge&SAci#YDQ+pk8rK3w|#-DAJ|2>$e&o_3kt z1T)9OZ6Y>jW?DYx&I5AfNpalm?3lKifGEP4liQfX6nsRo33U{5YaDvCns~JOW>eN& zQ&vG!T9clHB;y36bsS2lCK9S|c4Wcm=gI>J;LW~vx5;c~xgm`k*z zXj;nhIkWhjkMJXg`4L9^vLe6QAGSG-ny`;2ps9ow`L1z9*SL%wv0`hDFks&*E9K0R zaz0{<7`8fBUC}#sN zYOgo-k)36Uy=9P{Ue|RaGQWw>r%zy`A(w<)Bpw|i-owF z6pc=aZb|e_Oxn$%lc@oGs#$`nS0OQIk(d@Czr=hlJ)0V!u9~H#dNnBqof6ZM=vRv0 z(A+tumj2euMm5VG@W-M>Vq0w7{n`zRU&iI6zxswQk&D9|oBk$4rd}g*ZotIJ<>7+TR0ZaMJMvYK+=D4q#cA*joqL8FZO% zMw6e(5x^G#)LtflWnGeB9Yitc+D42dCxsa-0$i$DEa2x!bjrz=#GQ#*VH{k1=K}cD zvINzxLgLUOaV49fKwxrD1Ro$&eyw!%i)sA($3roo&t%KTXG?-!bTZY9nDQ&sKUMHe4SHKDE>Tt$7i#Mq&!C;pv^WG09eH}ZA~Zp_ z4lVaS6#DqV{SB}Wcv^j`MQWJpn+-a6Rzj8LwjHzSK}((98;yLFmQKnpja7vEol1XY zBJz0hJ`AwO*JDhqYOExF6*_jt%g-UjvaKp0hVa1I?Lm)Zw4OyraEX5$s^eVqr;0i` zHN@(;Ox#jO@O?>>!bABRq3`xLY{ws-73n+M!nd;E$m4N2GP8a@;v^Us42pFqD*1xk;|R zQ^~LOPMg_ys3ny)mr5(h&J-9aROxu{Lr%q8gy0{12Hvi>E3{v`};+!31gFiqR2Qduq&xbFQ*pEC$0 zH8=4&bNHMBLKf7CrqY2rkT(kqut=|b!-7gs;d&iYCO7$a*>T4|PYjlpX z_`aqaMi^bMvAkZR6Z0+IIKt?s8q1$*AZJ)~qe8!w-NtwB!@(%s6k&9?#`12B4w+^1 z2JA9F_?J)lmoqYPM>gvYZ`L)kMTnf*ci865mF4cnWuf^UK^bNdRI>;%HfHQEAHh@m z@{uRJ%T7!9wzD2d`^JKp|=5kj}n$gkbw0!^j`qKXUTrgAj-G&_kiECgyk6| zfSuWT?~5L#yhmYPCHuXCC|G4>$HO+&wK6?*GLU(%pbYy6s(pmmTRdL2jz6o)RrWFn zrelPW{6$Ooi#k))mEJYN=yZMWQjin1i#Ox)=Hl`S$mf!sXv$-#dIw^?LuWBi?o+bg zCy27mn3r*#bYC6l$i)`Fd*}OK^eXgRNn|Op|m6OZTy)t0cl`R zZs=d_sYmzKw+JP4|GY8{3Xo^^N{jrp3B2*9Wx@lE#Ny9Ndxm)FV@6oW10R%oYRh z+>8<UDa;t%7T^_b*e)gW^)IPa!|5nx=%;N~Vk=dgd3yu!_(s#`$kACA>70NWjz zn+D$JGk!Jl?n_H&eW>Cl*Eh{7zn1P;R#3a(kVL$?iCYOX0acMYFQdG#Ixw3G41BcY zZiQF!XWG>}Xn^2^3_cXtZ7gytn5H5|D7F~ma{|zXa((L9wOmX_S8zWjQsQZiq`d=!@s89@F>6gYtPD zb(2sy$TZ$rfiotz%zxm=`InFBdlIH+4>OGm>3bSoa{Z<*BndBWySkhhK%xk4+9@8_ zhFFYpEU)SMWQZpJ8Ig}{xerH>+JgEAXR`|pWOU@-fmpYDUcpv^jb{uX+iNWHb1+T6 zPVnbVTPptaC)t6mq_gk}ZoIxjLJE6sO8t?Dye8vtrbH!A2ivqgDsyUgSUrFM(WcuE&DW$zOB@(h&?Jw`uP4 z3H?P@xdY{tj|2lF5PegsXi&psr}hqg!}E4vL4w_+7Q`r|QC=w8Qgkjob1g=S{#9Tw z6o(#mg&3!F2GdN}f?Dk=3kD*wEl7Q6)~3jSqWh40vVb+|l#dejlr@r{i!vON3(Y;e zzApj(1Z2AWhGD_Apiu|iM1MA&VQ8Z|~d1s=> z8sY|-9x&KxRXshy)QmPw(prcP<)gsR1pqK}QG_8mX6{-{uQ+T5gH(lI+FZ!m-{^AT zLDpK?txpwXq`dwyHf!UVwoFS@sBVKv~d{GLA^=s(z)TDi6^ zugE0%r**|u;b}ns!A5dr`=Yyk+g%%r{XBw$YU<5bVzP#?E!|9W&z`0d@#`t_nMedf{?x%$E8 zJ)4%E*M`xHzWEJ5IFda5YKD4n#aA5f2UGLfG?RUZKbmv)X;PKuL1T~m!A3rFQ8hzy z-aLmgtEvt*rWdqfjG}MiiwDO|cRF~(rY{VG6)tBK?cXxg69H5W22%^#G}EIP9L&|V z_~I*7K-XZfQP5me3rCkA2ZW*{U<6Xcpt-~2Alx9VRfyK@=RudEA2e5wFV2`W-I-C) zhA@hDl%4GWapE3A|7D$X+yFEGD+FlDu+(~)o~nJb%|R_gv-o0zDwOlyb3f#&EE~Uk z!$gv6(+iYTy!<{pM!pstFAVYaNdr>y#`XCqp1=JI&EUa-g1YM9pB84I@X%G37ZcR< zj{A}X3%xB^jv2LJKLc+}&|Es|er1!*d6kd^bKXSx`h>~-O1x}yXoYv6PQ9z_lh)dR zDndJ0(s}zUxW|q^$L?M(_ujd5llz-_y=5cE>~XF;o1z^RXBBzJkzZB4L-Pi%H-&AQ znNbq!>p#6vNkz@!rc4s+V54X?VlgYfjsNa-Q;UjP&J2KC*oNRLDhdIIa^{R*TGh7X)Kzo@MIb6!+rM*DKl3DV`N*41 zVo?#A6qLy819QTwzT40h6*$O}HT?a}d#HY$G|@^#>$zeT#^~x8nUV>eIjJ*ox?9h&C*@otK+Y)hT`Sqsgd-xWgI z-b!`m3Z68H7X0`^P1$R#lCoNs`u5j-^6VV@L=V{Xy&*|Fv=I7}pVU9WT0g&2fN=J# zj)C|)g>C#hG|=Pu1}VW|sZ9g%r+E_<>Oj-H(uOB%I4R*=Y&m?+;Y1v;^N^ZD_j&%X%kDrV^a&VUT}%5u{*T% zEYE;XDghWMXybQ}*99U1$bEBbqPk0+`bA2f_{60OCWr5I-dKn_-pe)tsvJCqhn9GFA$pqZ#UxdP-1YH3 zwz=XZ?zVG)@ywX4k6;PK+tvvJZvEWBtzUZeYLy=7j*}cgPC2)Jdf?WNsJIWE^niS+ zsjk8u0&e{*AmG*y#>%*qtvn_RlZ&b4-1=Ptw|+gLXT~`iyDn0U<-o1qAs>R!pz2b# z;0c{d{vEb>AE^>q%pKEvoN}m<8qbEm)BZxgZJM9PiLiWB7gZZg))RGy+T{v_2V63h zMweDdUsKqj0rJG7&iex@JIAiu)?+FwQP>1hi38dh4fp+YDZxIesQ&j9u5&z#m)A54 zM?p*M4s&wHVa{A*7VX!=L+d!123q1*^n8m&qi`BC8!uOI0s$$JP1J>qT-tF^6Qnuy zZ0XmE3r+Ju_Gx-2ySI6Sq}mA&j`Uu)$U-z6Xq*h?LX?>l6>L8aef_?yHeLx4Qc-JzFPw?hboPUD;} zH_!rH#YnF;#n_SfHP~Jt&_Arfo+g6(Pmn$vu8M(No{COt^g6&iU5G~+51?plsi3>Y zmI}QwE|8f6`e3o|_joNDQ_4310-a==+f{*!pVZ|=sT09p#qlmd7fc8s-PioE91*dt zZiq+0nsKd!T8%{IUqK=4ZVi@}6lX;_4mU9fIo8*ek%nb%1W1rj>G*72F*H0Y2Gf}Me?~shCx+vs4-wxLRdyQ8-m{(;4sIBC*#cM z?BY;!vjn=+>;40!DrF#VW{X265r>MfWmWD!xhZuO8b(bR2_~@K4L6}wCi9cjguG9dm8b&$Gu)4E` zr};)gux5(G61`>#Tg(!)9ABq~mbP98yRA}YxNvoGXWXGCV6~`URVfpG(mYxa!%>Xp z*myJ~L6vUPA`@pO4n^98GrrQU9wqWY^VCU0)|-@hNHq!kxKY!gy@Uh(s?8bjlU~t+ z9}uJBPAin9_K@LrMpL%6sRGit5;Rwq2%~ZZ`C;*l`J{(K;#A=_t;56_wZoBo7j|Pe8I~x>kBVO@ zRzN_boJVH59UlOsO>uhz(VGm*6#~pQVPI@(wj=p|TP!%~Yr-E2#F{mL zKr;GN>(Y}KYTLNkb~K~U6o-PiS8scr>W7|o24E$yW`-q7n8nRMuNKN#vRPEDBRz@h z4e8Jn+Klk){!_%N{)5S)zUXO}VM&I>`S4_SGePIAmlTlc!G}_{9qIXBv5#=r@fgR= zG7Jw8oA4>D*-@aLz4>R1H`~@A$~`FZpg~{ULZ>qB)bYs!xw}5*9f*O)JH>hM!j%dud+S(x!d) zUF-Sc&PvsjY+dEZUqNDjqU(VFetFZj*N5 z6gi~%^oPuYag#l!{b>iYqgQ8G5kPs&G_3&NiY-;?Xt$>)fcu=)m#m0G!YR?yw0wN) zHbDQGL!ZrAU1mij3yVZgBY)Q?Z($2JC5wU=a0zZR3+LQRStl@ks%dG-*5hsbqZ8~L z-NJ4K_477;zmuufrf|vIRndZ<3NqbHjnl5#nA50FG*nO4=qfi#&kLI@(sSv|fp~k> zlkk_Vst<_HkyT7hVx&zUYk;}P?r5goNsFC^EwpM`juZ01D;U-in-CYp2}y>H(Yk|0l>j;aN}!t+si}6`9{bwG z8$GSZ5s;n{{jqXixtj647h{RoNDPCOc{KGK}(-|qM>%O2BrMk zWnMVuPLB?N@xD*iy`Oa=yH6FDp6oW!#{XMnG!APS{K?W0{;2; zSjH1p_@mdj!`8@@Q`59d_*UIAm9gKA3%hgavlsl(q38NK)jSz`Gr!&OOSyBh8Ab_H z66!G(wQ`?g5u5tpq;%noXJbvaIRspnj##0#JMN`+PaxlqRrYiU?!Jy*VNGz3xsD`K zuU8=O?_^s1B>#3C^h^;^xLmiA;EAKIrbxY~eq@Lp-X!}#a1IgI ztFy~@A}S{gJ;lAm3nk(*+=7B94!i#9;gcz>@;lgPw;nZ)h~`|^xpS`T#u>c3El%aW zAmA?Ry|BVJRrX#wABpi>@lt@Rz-YTa_Fk+6vlvSDpAi3U6TomZ^wje)I`Ww zS~Gs}w#?Ub2OG5%K);S}+9C;(!ev&+ZbfTk_t~m@hGD~c2PIc`&%CgWJ0(@FR-)L? zGRa2f$V-}cR`Me}xx~cFDY~M|7%6sIgJXg}0ngV5FIP*vEW&(InMT3FASCVAR-&l% zScomwT67fFb;BMGAt9j4+KO5q-y>h_M%hYv!n$%37TIGCwrVL9EbSIvA>8M1M{zfY zsE)Nnhi3P6s(Z4Hes$#DVPY*sITH485fTEn>@ZW+d3PJSV~0;UA`dAtJ5VW>h=qxg zT5O!{1r=MD*%eqzlqbwxn@x1-hu3A0od0ld+$7ZvimeNJZp>_Q=WMr z?sz6WDtVtXHI`_nCX$4u-DzdiLGfgbD_9E@XUZNfPD02pJ1oyo`t&RK4TDLMUgauz z^U1o3%NP@O+N&POsK1S1;1|PaHWA+sf03~OF~V-CNLqPSfwe}B!rU=zBB3AtKErKH z%}4N8!BN=#8wty=#=7m*Qc|$Aj#eRV1uU+!+pvk`ez;Pmc==Vba8pX>4LakO(8X6{ z4i0K5saRT9D}xCIH*$(tYl(7IVW8iIP0a3xTLOVbuD~Rn@gfw|LN^dd!_vB28B08Y ztrF#G!k!!4z1YNxe)ujRaP1ob2S>G(bS$m6RhH+`Ta&m`il9hBX?>lVqp72QFfZ8! zxX{uoleiPWJdf_#z1i52d)LTy2xGL2j-d68YkIQ3r5i7!iL^eZrl*i;WBgh0zW)tZ z31KfgVp;PX%dy<$K=7iA0JxlVFIUwag&`D4B^~`NG7YJzBsT;;7(wWI!g7%!BNkEKdJ4c=A4P8 z4YV@ih46g$&SNcilp`>v%V-*{PeaQy(bPCj9o$O4Su>G|bw9)=4uLAlJW}=SqVQX5 zo=eK4lCgeP1q~Ud^w{Avcw4*yYrUgf6|-d-T}SKl*79VVHm1D;k1=X-CyKDvgrn?; zFs*ZRr*hFl!SJ;#n~+X0ru!$^PHKHwSlSTJqthnks+r*;Fe=uaz$P;K;p3U&YAzr- zBCHpkaiztr-dFr9y#Y6}Qp3*3+_l6+S zxm?$B856}$JK78J473qkE#nEqup_Fp&e=Pci-xa7n;4e3D^)Fm~?PaOUcGcPqZ#7WlZx4-;Ik3 z1jk!4JHk}^+txa39vv5G2}R8Lg4iXRGbmjW#~ht7%cOb&;z{c3`r` zMa`LprA=}*k>7RX(q{(Z_iKB?wMYo3Wd|=-SGZvmShb$83{ZPCtUHxWL=3=jS>hL( z`?&>R2nxVu8Eu=>7q9KboY=sVQ)<=7BtDpR>o6 ziyq;*dKyrVmaAdhmeIR%`kJ*pYj~Q-9ICnJ281rD#AJXKl7pO4R@j!Et^cbsPWh@m%^mpnEQ3%GqiC zpXnkVd6}~!xZ$^q)EuOyibCU^dEpij;EuOx!A9*ZlL=a`<>aG?)#m7W`VT3?Hw5Q# zy~_y|hfWZ%1Mv7Pm6LSPS%ZoxMJf$$$SL`yb4lBiY)&n`{*3)$fCBS`m7sKvT z#<&BAgtqu5RO8B1k4&#(>>|n1r{fMY&;x;Ivmfk`r0SA18;LBIXdA!ND`s8%r1t*z zwmxQCFeU7?*50ghT5Ms(=9J6A9vsWK;Rg&nC!!YHsM#tZn(GF%*9~+ZA4%e@eig1= z?Jdz9yW}H&^kUfsOfE2M2+T@x%<7Od8;C3|tv3F%&V>L#PUgY92M2I!eK}a^N3BaV z+BBd1S+Ec0BguLKM~F0(s!ZOd>Gm}dXI&e8Dx!Rt&+9U*S*};$1dpR#k&_f#p8@Eiz zVMpX>pVPvX3#E4(J(?!N)8>UearWm&A5mdd z+%JhZZPkk?&Kd~hq7u>sr!2_Vzd-e!s^EVG60<2Bw|69`9RxJia6ly_Yw>T|@u)qv zQeYWqlPqz|=D3{4H0|RKTO#8;#K7SK!Wosrp4A?BqK(_@oYOA-5Cic9{ZDQ;*syVX zJ%FklcC7Y*ig%WZ+Rqf>rp4(B_4^hbB@drn+_)%EU$WHMsePQi<@HCxLlt~c#bN*Y zfXc%}|6w6!YL11S%E_~c7m{d0ubT$`cf4-4)gMYF1P-XQWvN82*wgv_FZ;wo{Zpt9kxjmAed3kF!qAkWcG?VP^SfDL#eileE?>Sr@5!rcTAoi+PfUwQY_%X)p40Tq z1QYMr$F2j@o=-(jPK&f}vLOGN#hds5upzHi1Bve@KCzE21KU6%6%kis_rpvY^pAGZ z`(yRqt_~SazCX-8HF<65LTMdj5>m7N~bZ#^FO^&eiSGf3|K?10@xHSib6z#^EUMVMAtI zo`t~1KOt{2B9d>D?|M+}d+h?zHO}n(B<)VVz!s==L>)nReyV<*{a5e2z z7n0WUQhUXppewtp={BV4wxe99WXJu5qC5+`jich+4^Ipxx(z3~!4ZqQ*iLmNX}$X_ z;69}3zN1{XB>4V9Yn}xK2q5aF`NHp~V?!M|S8*i=?l1J`SyXLgmONz(uO9koYEiqs zpL5xl>rPTVzwGpp6@P65cykFgSWc89b;XtAm-Vi(e4mPv&#Ye20w3oD(vS^20WXqj z<+77dP1U79XPje6lcu|(C*0j`Ha79T%KMyjW9bFFjAKEQrkmoZ%oKbe*u$kQKf#4k(e%-4zKT*2{<6e+Eq1B-%j->X-OSm?gLkeY9?tSd+L zYuJGCzTzSSMg}rXw|UtrY&OfKKOx!z)Ob&FVf)FYV@KnBdbZEu?F_CZ1Uz*~!fv=% zH?_EU<+`gs4T-tEY~Ggtm}qcZ$i6)OHFzZWJK$oys4QX+>HPEi3uE~f*EL3M{&JJV z|9Hp8{{YnETD$wH+1R)DRhF{DEB*lmaL>0+-wq-Y_*A!J*@`^te#VvWhK(TBR7$1X zPp*z)W_Ua|l%z^uc5-3U-NCm$YKkgqe!pu55He?vg&AI>2R`jjJF^;y-olu#0$Z0q z*jNU@wq5X;W_TPt3^6Qh1>-^h1b-oM*o}7gqS;uJL6r!a$Xz>Wx7*!YXJZM2Dlcg1N8YvZKYF#FzInj56f0>XS0qDB%G6G3&&-uZ^8Coca{GKRg-qF9rhzh zYu|)gDcI5BjjoUC4=io4FA*JDkSek;)g86lRmXp@CzJLk=3bI;UXQ&KJb|Ptyy7&% z-i2SRzx$oN<&z zlRNiaJ>ajGK;L{EP9>=#R-8VtO13hNP**@h7Ts`%9#4CB7F$|nvSs}t;=z0mO> zZRdRWd$QyYcucLk>oK3hxpwDcZq_}P*MgkcDStw=e$uC`;AM-~yZ?Mki5=o)C^RGs`-I49Gklf8fT5;{LS5R4%UDQ|TD2zPOrDDF9eJp`i z)9~T=7&^MADnTnryp0{E`AI$kF5iojd5RxKSdtAPZO23c%Z+4A)y9I^ zY{{kc2_D?*PY-Pj5L5PLK&%E7E)X%i4Y)SiT7OxG$fjf^;Zz?5t9A8Is2+B ziqZJ~?YOIiGSMy6TtjJcsAt_>^Otmm-6dDllGd1az0qkF+DD@+@gDjJ7mZU-R*PeC zw5mof>~>|FOj>D~$2Vn1@C>Ww?|hYlRf)EN$DGhg7r>{+9DOsOU;Q+9_t%S0H=!6k zYDqn}@2EGRa;K((Q?qBz_Kjte5R#5tyvAVWg0U)TgjSRx$9U_U6)z2}b0<^`{e)@l z?|E=`)-vr9K_X2oay_=~y;`%O)f|zBEJ!}B$DQX-)6QE;!%yx!I(L&?FH>{7MPJ7q z^U@<)y{Spkk5oNsw)q=FFn@aTU7R0PD7(Kk{I|Pll`9~S2h&y3AGJv}?v#rDo!zK* zgqNP*D@7b@E=OCE(x)YG zK^(>|e1IB8-QtB!^5DyJqW=mWRDavxwT~%BAhY8ksuk2=QMHDz9{DG}$fQ((64A&$ z=5Q&Nb$Yk0N1fIXs+97;oZRCc#_o0WG3PkzK*%j`SNw^USi5KBYMP@C+T$|1S*AyD zG|iov6F2{m)ZF%cWg>it^;v@7XMWXL2anwGcEyT)5^KRl0=*RL!*Jhcp6{IPj`Vo@ z?1bNyMAh3qdF2qz*k3eqKXo_&JCLyZa8do!V(k%PT3?i2p@UIrChm%>5o6<_CxGTU zQS~M!uiTwxY$F;uojPob9XR*=UC#w}|DCnrMiN3F{j6!_a$)Q?$1Zo_#xzT5Lx+=I z;j!E+r&SL=K4&=iGj<^9`Kd6l5Z3O%9>md%;dC-!Za4|w%!=MJHHfPfgcmv+67)2` zC}LRAIiTBfVIe^_#i$%lh8r)_t-&DGLBD!sw`ufc?_C*gJggx>SMzUu%`r9MLQ}OU zOx4=@lm3uRF*3)~JSW}NkO3VsPdwg5&8-oAE#Gx$d^RZ)4LYPIq@VQfKIw0jV|Qq{ z8x~#<=K76q6m*~nTW;BS!ux`nkaN=C-ljOr#tT^dIlN`)LWOcSk*O90sRbd_g2)=8 zQ8hi>jyJ#A)@l82$aOa4VhyFFMAuW?vo|4HnfYa zhnwAqsw+e&4G{+}Lcv91{nVEl*n5|rpE#XtfnFi%ql|Y+Sp`p>yt5?%MH0T*8wuD}g+Wyd>{#D8utLpJPF1Xqgmv~rjge#$VOC?_x_?`lvb9LOR+)+%4 zNbwEfw$!1bf<4SHnPj^l=fAVUOk`MUHw@sPaUx3S4?Eg_FsP4DSzrr1ImO1`s=`p} z3d*34KtyIKH*?30CVj@$N$H*a2PhLhuV@h_E?cLG1`NiOD6o)J~EZmebA zK&6fN2S-Im*8NkVTeEZP?H3Vq!8WGkZ5#@jbO`T{NbV=U4sf()9lb@os8peBP@@fO zm?QpvQPJ*o|FCtB;kNp{7aTSP`?diWUjmSTFR5e)e!#;c*xA=s8CXkd)QY~*)Bw%Y z9sPiK%tRm)8wJ3?Mwv4YWMk)Ay&Ge0rGOGhlR-BCNajcws>6z@az^~hI8K_}ChO6I zP#pmFsE%%Y$q`h?hR6pe(pZVA>)5!uLR=jhS0}lW-0$vK!v;~mP41%ZCUSh_p!*Q{ z6$2AK@N^Ccty-6Cc&Ls|l*5QvH$0f!A6Z9Z+dgt4s{Vh-`+Iw9{dJz0bn?}n5V7Ec5-pnn(Wal4)~q|<_aH>r}1q_{k@xycggccZw9bOZ|?RX#-i0m z+Q+0Z*83@LguG;T09JDA4!tM&$tyS33dWXHDEp2Q*aHAd*#lATb??{%_ZwtVlAXjl ztqMX_0NA4{y79y#sEQ4dn63e=7A(3VjER+lfekZf`eb9n8dkxY)Cbf_b>4Z&a|7*}-4Q`S9dcNc8 z-uGNl)(!Mhsk0TSfY258=!%Cv$SgzSbsNY%*e#@EY4;LUL)mk#*DY$&V>g!3o-B1& z4QsQl{Vfz1l7h|De8%GLsJ@YI5s_mR-D7iPgwl3}X|}d3#G_OC%wJq{Xf8MOP$=+gv4!N^W@a1;sCE~HmU16f0sF_Z^R5`12|eRA@AD0<|097Nuw{1s zLLuJF8_@6GzM-9;q$5vZyGx8iD_d?X3a#Y6rU17is_PuJV7rN^(EOIDg`xS}*YeIj zON~QswnQxo?e^(=UyPK;U`D!}=D>7fiS*`eF>B8-%XZSeqTY4?wE9~(n@Gb~u=dnm zv1lEPq}^+y)<3OKPAd+m%>|2GbKogH_}OWB9VGs?s)s;RJB|-7BEbDp$XJCP$l3c^ zGj%r-LNh?)HhJS%G;P!4pJC6yHU%7jP8aSwz}XmTmFD2A_3Dm+d+iBVg2KsJE-ryN#EnyQ# zXhS?msDMZ#fP{pz3Egj_S`LB`;T8n#pI_Jr>_VqPE_&vJFdu<&tX*Z%>||4$YgSMe zl2efBgfW=)2Q>!_n zqdj`yhUvs>*~c_9E+a?M4DQjdRIY*Dz6tI)hvmZ=;(h8y7+MzVsn!KC(^RvawP02i zpN13+({K^|Dp$U_De9Aj?PQl-QuJ%aQyEljV0BN|z^r2a9oV`e_!(fas>xeYGq#jn zU>RpK9xA55&FOnu<_YMk0<2Qu(OaZVqAu#Tb*`z4or?%pEZLIm)kfk={B&aAVLMcjn_gWq8l!8)ACQq9iq; zBTr=}g$oUG%R^dD-KEC^lSj5Xi}lEupXkg!4#|{Wsqd@Lqv-Qg9)oV;)~B|~_84+C zJ%lMcyUd1>dxbym4Z0`Ifq|Q!_Tr$lK2EGD{e!+Ql1D-E&Zb+vz2gSvPR>P~55jHR z!G6}FlL**J=92z+tDmqVKfzAJ`-FBOy_tvHJQ*&06Hl3mXU2xZJyu|fXV@hgFI+^{ zB<$Ifmq0}%QJKplRnY;qsw*7r%B>b?pn2tfEqXO{gBsD<4CQfVj`9xOK5w0qM#~6Y zCc`a$!dAba`&HC>Q8RTu{80hy?tGvy8cy~TrT_(xnklMKHfILZrWDnkLfmxZw|U6g zJTf)}H>i$*Z%>1JPp$92OFyjZ+sCE!aU0S%44#Mqx0kU6Iu9=w3dx8$tVM?ru*1yd z{X#&C3udrZ=HJhJJQ!Q}7d>Pbfg`U5)xUwG#|O&`1!P2VZUP07L}4zs6~;y+KHUpz zJXnFwve+l{+L0zfWl2y=H_nsjg5Vw{(Cp|rbDj5BY1UzB2cV5B)MA88!B1I_Bj+I!4FV=DuvD^q-mN*tIvxMQld&~Q0sba}Y!iXTgJLKWBpHK=E>4)5#iO8NdT=pTw?HIt zUsj%>$5=EansKBF_*XXaVVOd;}K*O}yRwwKHX8XCb7;fS%kv#p&pQb5??JMAklLo!rY9eJ&KCFgW~8eG z*$3IrH9Es>(JQ1I6k-S1Vu8j6F!6QgLOVOw!X55-GtuD?CLBWUfONFu!H&LqNj_Mm zz+ouFFN0)d5X}UHw^Tp+@(H_iF(@`wlLrl#5QL=!y=45mUfc98sycip2PUGc;La2B zoOU5xcQGHVzg`7R&bL%yKD6;-{I;->L)y&k+suUAhCRE4g`!;e8HFCDmIeh_670No^bgd>a3vY1BVwmH84Xv*p8>MEU z*&f1naU$=!+FHo(Z5OstVe5aZwIk=^&9UTMH*>!DipR3Z-=^<<{2|H*Z|+1c#hWi8 zmvS4c_~};C_7k4Psb|Y zgaI5goZ@#w(ZGYt+BmGmhR|raG;j>V&fxpG_)le`Wb>=3GBemuhA>dQzAbK z6Q+3lLWB_6*c0j(7mVWADW+V_5$JV^M|-KqFK#=2*sA;RhlxxLqw7q^ygk?Ur&V*Z zsyPfEXQE4sbUFXb1+j>QYxcPAwLc(0v6Jc+5!w$7+d=yt(Ec_j>o$i`$eCEY zTT&A&^{*`jM?jh?gx7G-b`4L+U%fa!0F<`z5>xJJz2|lRqN8JD+0Uy#ynWs28Xh;E znf-iP);%-*PrnWz*c|f!Y?bj%Gb1md2&2 z5I6M%xcE5TUF$df_gLmjn2uHKWYWyU;ESV@tyLf10xr>at)1D=k4(jn&rC{g`o%?! z!gOBT{vd1ZbbYgRYNGR6+@w_2T6^=&)+5t9vu8l7-pJmj7t?R2Z~7(qO`rUb7Ok_j zdZuwE+-myuhc|H_-qp@bS5J?^KXIILQ(t_HlQZ6K-+T0*ShAAR`4MF$H>Wvsmnmy1 zEm*KX$tV3!!k&@N>tev&>IB$b7lHTBR~c3Qn;$XgK;$|F)9ts0bM$Qj_5&K-Lx2TY z&OHD5Dx>}kq~5mSVWglik{>=MA}G>V&O`sLgQ6{n_XWUe6=?qBXKV0YMr{PK1cnE= z5yK-Q*X@mn_?|UB9KCWSurvW}mwaVi0eF4CSO}zNa!bk-%7<}c&dcML>1Th2@g6JMZB87wnN3Q$k^9HnkNZ7ZP z>1=dY#u+Oq2`9uyk1PVuVXLH;)S|MDx#39vt3Wz>%r3J3o!>bJ)K zB^#DgFn_+vsO6Y1#{Vxu=5HPTckatMia%dv)S)fkI{cTh*v)Ak7(OMX#o$LD%qLE% H{L}vdN<8sH literal 0 HcmV?d00001 diff --git a/results/tables/gwas_intersection.csv b/results/tables/gwas_intersection.csv new file mode 100644 index 0000000..8359231 --- /dev/null +++ b/results/tables/gwas_intersection.csv @@ -0,0 +1,14 @@ +association_id,variant_id,risk_allele,risk_frequency,genome_wide,pvalue,pvalue_description,range,beta_number,beta_direction,chromosome_name,chromosome_position,functional_class,ensembl_gene_name,hgnc_symbol,group,type +41136253,rs58621819,T,0.2097,FALSE,2e-10,NA,[1.01-1.02],NA,NA,11,65547359,intron_variant,ENSG00000168056,LTBP3,OFC_female,DGE +41136409,rs12923444,C,0.4375,FALSE,2e-24,NA,[1.02-1.03],NA,NA,16,21628389,intron_variant,ENSG00000197006,METTL9,OFC_female,DGE +41135995,rs10789214,T,0.5661,FALSE,4e-10,NA,[1.009-1.018],NA,NA,1,66681134,intron_variant,ENSG00000118473,SGIP1,OFC_female,DTE +41136026,rs17641524,C,0.7909,FALSE,8e-20,NA,[1.02-1.03],NA,NA,1,197735587,splice_region_variant,ENSG00000213047,DENND1B,Cg25_male,DTE +41136085,rs45510091,A,0.9472,FALSE,8e-21,NA,[1.037-1.057],NA,NA,4,122265238,intron_variant,ENSG00000138688,BLTP1,Cg25_male,DGE +30547745,rs10127497,T,0.1382,FALSE,1e-08,NA,[0.0064-0.013],0.0097,increase,1,66584461,intron_variant,ENSG00000118473,SGIP1,OFC_female,DTE +30547749,rs6679379,T,0.2875,FALSE,3e-08,NA,[0.0047-0.0097],0.0072,increase,1,66733473,non_coding_transcript_exon_variant,ENSG00000118473,SGIP1,OFC_female,DTE +30547797,rs12118513,A,0.2148,FALSE,1e-07,NA,[0.0049-0.0103],0.0076,decrease,1,197547956,intron_variant,ENSG00000213047,DENND1B,Cg25_male,DTE +30547801,rs17641524,T,0.2086,FALSE,2e-07,NA,[0.0048-0.0102],0.0075,decrease,1,197735587,splice_region_variant,ENSG00000213047,DENND1B,Cg25_male,DTE +30547485,rs10929355,G,0.4558,FALSE,6e-09,NA,[0.005-0.01],0.0075,decrease,2,15258840,intron_variant,ENSG00000151779,NBAS,OFC_female,DGE +64732910,rs2894699,T,0.4305,FALSE,4e-09,NA,[0.017-0.033],0.024859993,decrease,7,114419101,intron_variant,ENSG00000128573,FOXP2,Sub_male,DGE +64733014,rs7146581,T,0.2246,FALSE,2e-08,NA,[0.018-0.037],0.027423386,increase,14,102834735,intron_variant,ENSG00000131323,TRAF3,Nac_female,DTE +64733043,rs2369818,T,0.4386,FALSE,3e-08,NA,[0.015-0.031],0.023054866,increase,16,21602688,intron_variant,ENSG00000197006,METTL9,OFC_female,DGE diff --git a/results/tables/intersect_by_type_and_gwas.csv b/results/tables/intersect_by_type_and_gwas.csv new file mode 100644 index 0000000..f59842b --- /dev/null +++ b/results/tables/intersect_by_type_and_gwas.csv @@ -0,0 +1,1215 @@ +intersect.x,genes.x,hgnc_symbol,gene,group,region,sex,type,intersect.y,genes.y,gwas +female:male,ENSG00000185149,NPY2R,ENSG00000185149,Nac_female,Nac,female,DGE,DGE,ENSG00000185149,not_gwas +female:male,ENSG00000185149,NPY2R,ENSG00000185149,Sub_male,Sub,male,DGE,DGE,ENSG00000185149,not_gwas +female:male,ENSG00000118972,FGF23,ENSG00000118972,OFC_male,OFC,male,DGE,DGE:DTE,ENSG00000118972,not_gwas +female:male,ENSG00000118972,FGF23,ENSG00000118972,OFC_female,OFC,female,DGE,DGE:DTE,ENSG00000118972,not_gwas +female:male,ENSG00000118972,FGF23,ENSG00000118972,Cg25_female,Cg25,female,DGE,DGE:DTE,ENSG00000118972,not_gwas +female:male,ENSG00000118972,FGF23,ENSG00000118972,OFC_male,OFC,male,DTE,DGE:DTE,ENSG00000118972,not_gwas +female:male,ENSG00000118972,FGF23,ENSG00000118972,OFC_female,OFC,female,DTE,DGE:DTE,ENSG00000118972,not_gwas +female:male,ENSG00000118972,FGF23,ENSG00000118972,Cg25_female,Cg25,female,DTE,DGE:DTE,ENSG00000118972,not_gwas +female:male,ENSG00000131469,RPL27,ENSG00000131469,OFC_female,OFC,female,DGE,DGE:DTE,ENSG00000131469,not_gwas +female:male,ENSG00000131469,RPL27,ENSG00000131469,Cg25_male,Cg25,male,DGE,DGE:DTE,ENSG00000131469,not_gwas +female:male,ENSG00000131469,RPL27,ENSG00000131469,OFC_female,OFC,female,DTE,DGE:DTE,ENSG00000131469,not_gwas +female:male,ENSG00000131469,RPL27,ENSG00000131469,Cg25_male,Cg25,male,DTE,DGE:DTE,ENSG00000131469,not_gwas +female:male,ENSG00000185710,SMG1P4,ENSG00000185710,OFC_female,OFC,female,DGE,DGE,ENSG00000185710,not_gwas +female:male,ENSG00000185710,SMG1P4,ENSG00000185710,Cg25_male,Cg25,male,DGE,DGE,ENSG00000185710,not_gwas +female:male,ENSG00000134884,ARGLU1,ENSG00000134884,OFC_female,OFC,female,DGE,DGE:DTE,ENSG00000134884,not_gwas +female:male,ENSG00000134884,ARGLU1,ENSG00000134884,OFC_male,OFC,male,DTE,DGE:DTE,ENSG00000134884,not_gwas +female:male,ENSG00000134884,ARGLU1,ENSG00000134884,OFC_female,OFC,female,DTE,DGE:DTE,ENSG00000134884,not_gwas +female:male,ENSG00000105223,PLD3,ENSG00000105223,OFC_female,OFC,female,DGE,DGE,ENSG00000105223,not_gwas +female:male,ENSG00000105223,PLD3,ENSG00000105223,Cg25_male,Cg25,male,DGE,DGE,ENSG00000105223,not_gwas +female:male,ENSG00000181804,SLC9A9,ENSG00000181804,OFC_female,OFC,female,DGE,DGE,ENSG00000181804,not_gwas +female:male,ENSG00000181804,SLC9A9,ENSG00000181804,Cg25_male,Cg25,male,DGE,DGE,ENSG00000181804,not_gwas +female:male,ENSG00000198563,DDX39B,ENSG00000198563,OFC_female,OFC,female,DGE,DGE,ENSG00000198563,not_gwas +female:male,ENSG00000198563,DDX39B,ENSG00000198563,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000198563,not_gwas +female:male,ENSG00000198563,DDX39B,ENSG00000198563,Cg25_female,Cg25,female,DGE,DGE,ENSG00000198563,not_gwas +female:male,ENSG00000198563,DDX39B,ENSG00000198563,aINS_female,aINS,female,DGE,DGE,ENSG00000198563,not_gwas +female:male,ENSG00000198563,DDX39B,ENSG00000198563,Sub_male,Sub,male,DGE,DGE,ENSG00000198563,not_gwas +female:male,ENSG00000135766,EGLN1,ENSG00000135766,OFC_female,OFC,female,DGE,DGE,ENSG00000135766,not_gwas +female:male,ENSG00000135766,EGLN1,ENSG00000135766,Cg25_male,Cg25,male,DGE,DGE,ENSG00000135766,not_gwas +female:male,ENSG00000227152,OR2T7,ENSG00000227152,OFC_female,OFC,female,DGE,DGE:DTU,ENSG00000227152,not_gwas +female:male,ENSG00000227152,OR2T7,ENSG00000227152,Sub_male,Sub,male,DTU,DGE:DTU,ENSG00000227152,not_gwas +female:male,ENSG00000213816,CNN2P4,ENSG00000213816,OFC_female,OFC,female,DGE,DGE,ENSG00000213816,not_gwas +female:male,ENSG00000213816,CNN2P4,ENSG00000213816,Sub_male,Sub,male,DGE,DGE,ENSG00000213816,not_gwas +female:male,ENSG00000237649,KIFC1,ENSG00000237649,Cg25_male,Cg25,male,DGE,DGE,ENSG00000237649,not_gwas +female:male,ENSG00000237649,KIFC1,ENSG00000237649,Cg25_female,Cg25,female,DGE,DGE,ENSG00000237649,not_gwas +female:male,ENSG00000178397,FAM220A,ENSG00000178397,Nac_female,Nac,female,DTE,DTE,ENSG00000178397,not_gwas +female:male,ENSG00000178397,FAM220A,ENSG00000178397,OFC_male,OFC,male,DTE,DTE,ENSG00000178397,not_gwas +female:male,ENSG00000178397,FAM220A,ENSG00000178397,aINS_male,aINS,male,DTE,DTE,ENSG00000178397,not_gwas +female:male,ENSG00000128564,VGF,ENSG00000128564,Nac_female,Nac,female,DTE,DTE:DTU,ENSG00000128564,not_gwas +female:male,ENSG00000128564,VGF,ENSG00000128564,OFC_male,OFC,male,DTU,DTE:DTU,ENSG00000128564,not_gwas +female:male,ENSG00000156097,GPR61,ENSG00000156097,Nac_male,Nac,male,DTE,DTE,ENSG00000156097,not_gwas +female:male,ENSG00000156097,GPR61,ENSG00000156097,OFC_female,OFC,female,DTE,DTE,ENSG00000156097,not_gwas +female:male,ENSG00000145757,SPATA9,ENSG00000145757,OFC_female,OFC,female,DTE,DTE:DTU,ENSG00000145757,not_gwas +female:male,ENSG00000145757,SPATA9,ENSG00000145757,Nac_male,Nac,male,DTU,DTE:DTU,ENSG00000145757,not_gwas +female:male,ENSG00000188089,PLA2G4E,ENSG00000188089,OFC_male,OFC,male,DTE,DTE,ENSG00000188089,not_gwas +female:male,ENSG00000188089,PLA2G4E,ENSG00000188089,OFC_female,OFC,female,DTE,DTE,ENSG00000188089,not_gwas +female:male,ENSG00000230601,TEX48,ENSG00000230601,Nac_male,Nac,male,DTE,DTE,ENSG00000230601,not_gwas +female:male,ENSG00000230601,TEX48,ENSG00000230601,OFC_female,OFC,female,DTE,DTE,ENSG00000230601,not_gwas +female:male,ENSG00000099960,SLC7A4,ENSG00000099960,dlPFC_male,dlPFC,male,DTE,DTE,ENSG00000099960,not_gwas +female:male,ENSG00000099960,SLC7A4,ENSG00000099960,aINS_female,aINS,female,DTE,DTE,ENSG00000099960,not_gwas +female:male,ENSG00000099331,MYO9B,ENSG00000099331,Sub_male,Sub,male,DTE,DTE,ENSG00000099331,not_gwas +female:male,ENSG00000099331,MYO9B,ENSG00000099331,Sub_female,Sub,female,DTE,DTE,ENSG00000099331,not_gwas +female:male,ENSG00000242114,MTFP1,ENSG00000242114,Sub_male,Sub,male,DGE,DGE:DTU,ENSG00000242114,not_gwas +female:male,ENSG00000242114,MTFP1,ENSG00000242114,aINS_female,aINS,female,DTU,DGE:DTU,ENSG00000242114,not_gwas +female:male,ENSG00000239887,C1orf226,ENSG00000239887,OFC_male,OFC,male,DTE,DTE:DTU,ENSG00000239887,not_gwas +female:male,ENSG00000239887,C1orf226,ENSG00000239887,Cg25_female,Cg25,female,DTU,DTE:DTU,ENSG00000239887,not_gwas +female:male,ENSG00000121039,RDH10,ENSG00000121039,Cg25_male,Cg25,male,DTU,DTU,ENSG00000121039,not_gwas +female:male,ENSG00000121039,RDH10,ENSG00000121039,dlPFC_female,dlPFC,female,DTU,DTU,ENSG00000121039,not_gwas +female:male,ENSG00000172889,EGFL7,ENSG00000172889,Cg25_male,Cg25,male,DGE,DGE:DTU,ENSG00000172889,not_gwas +female:male,ENSG00000172889,EGFL7,ENSG00000172889,OFC_female,OFC,female,DTU,DGE:DTU,ENSG00000172889,not_gwas +female:male,ENSG00000114204,SERPINI2,ENSG00000114204,Cg25_male,Cg25,male,DGE,DGE:DTU,ENSG00000114204,not_gwas +female:male,ENSG00000114204,SERPINI2,ENSG00000114204,OFC_female,OFC,female,DTU,DGE:DTU,ENSG00000114204,not_gwas +female:male,ENSG00000154096,THY1,ENSG00000154096,Cg25_male,Cg25,male,DTU,DTU,ENSG00000154096,not_gwas +female:male,ENSG00000154096,THY1,ENSG00000154096,OFC_female,OFC,female,DTU,DTU,ENSG00000154096,not_gwas +male,ENSG00000283453,PRIM2BP,ENSG00000283453,Nac_male,Nac,male,DGE,DGE,ENSG00000283453,not_gwas +male,ENSG00000177051,FBXO46,ENSG00000177051,Nac_male,Nac,male,DGE,DGE,ENSG00000177051,not_gwas +male,ENSG00000161939,RNASEK-C17orf49,ENSG00000161939,Nac_male,Nac,male,DGE,DGE,ENSG00000161939,not_gwas +male,ENSG00000172476,RAB40A,ENSG00000172476,Nac_male,Nac,male,DGE,DGE,ENSG00000172476,not_gwas +male,ENSG00000182601,HS3ST4,ENSG00000182601,Nac_male,Nac,male,DGE,DGE,ENSG00000182601,not_gwas +male,ENSG00000277075,H2AC8,ENSG00000277075,Nac_male,Nac,male,DGE,DGE,ENSG00000277075,not_gwas +male,ENSG00000100191,SLC5A4,ENSG00000100191,Nac_male,Nac,male,DGE,DGE,ENSG00000100191,not_gwas +male,ENSG00000100191,SLC5A4,ENSG00000100191,Cg25_male,Cg25,male,DGE,DGE,ENSG00000100191,not_gwas +male,ENSG00000198658,ABHD17AP1,ENSG00000198658,Nac_male,Nac,male,DGE,DGE,ENSG00000198658,not_gwas +male,ENSG00000219814,RPL23AP47,ENSG00000219814,Nac_male,Nac,male,DGE,DGE,ENSG00000219814,not_gwas +male,ENSG00000183807,FAM162B,ENSG00000183807,Nac_male,Nac,male,DGE,DGE,ENSG00000183807,not_gwas +male,ENSG00000204287,HLA-DRA,ENSG00000204287,Nac_male,Nac,male,DGE,DGE,ENSG00000204287,not_gwas +male,ENSG00000135114,OASL,ENSG00000135114,Nac_male,Nac,male,DGE,DGE,ENSG00000135114,not_gwas +male,ENSG00000184731,FAM110C,ENSG00000184731,Nac_male,Nac,male,DGE,DGE,ENSG00000184731,not_gwas +male,ENSG00000273802,H2BC8,ENSG00000273802,Nac_male,Nac,male,DGE,DGE,ENSG00000273802,not_gwas +male,ENSG00000124208,PEDS1-UBE2V1,ENSG00000124208,Nac_male,Nac,male,DGE,DGE,ENSG00000124208,not_gwas +male,ENSG00000181819,KCTD9P2,ENSG00000181819,Nac_male,Nac,male,DGE,DGE,ENSG00000181819,not_gwas +male,ENSG00000149532,CPSF7,ENSG00000149532,OFC_male,OFC,male,DGE,DGE,ENSG00000149532,not_gwas +male,ENSG00000241644,INMT,ENSG00000241644,Cg25_male,Cg25,male,DGE,DGE,ENSG00000241644,not_gwas +male,ENSG00000285607,FAM90A9,ENSG00000285607,Cg25_male,Cg25,male,DGE,DGE,ENSG00000285607,not_gwas +male,ENSG00000145779,TNFAIP8,ENSG00000145779,Cg25_male,Cg25,male,DGE,DGE:DTE,ENSG00000145779,not_gwas +male,ENSG00000145779,TNFAIP8,ENSG00000145779,Cg25_male,Cg25,male,DTE,DGE:DTE,ENSG00000145779,not_gwas +male,ENSG00000104998,IL27RA,ENSG00000104998,Cg25_male,Cg25,male,DGE,DGE,ENSG00000104998,not_gwas +male,ENSG00000171792,RHNO1,ENSG00000171792,Cg25_male,Cg25,male,DGE,DGE:DTE,ENSG00000171792,not_gwas +male,ENSG00000171792,RHNO1,ENSG00000171792,Cg25_male,Cg25,male,DTE,DGE:DTE,ENSG00000171792,not_gwas +male,ENSG00000099917,MED15,ENSG00000099917,Cg25_male,Cg25,male,DGE,DGE,ENSG00000099917,not_gwas +male,ENSG00000213569,GTF3C6P2,ENSG00000213569,Cg25_male,Cg25,male,DGE,DGE,ENSG00000213569,not_gwas +male,ENSG00000113460,BRIX1,ENSG00000113460,Cg25_male,Cg25,male,DGE,DGE,ENSG00000113460,not_gwas +male,ENSG00000008323,PLEKHG6,ENSG00000008323,Cg25_male,Cg25,male,DGE,DGE,ENSG00000008323,not_gwas +male,ENSG00000197380,DACT3,ENSG00000197380,Cg25_male,Cg25,male,DGE,DGE,ENSG00000197380,not_gwas +male,ENSG00000128298,BAIAP2L2,ENSG00000128298,Cg25_male,Cg25,male,DGE,DGE,ENSG00000128298,not_gwas +male,ENSG00000128000,ZNF780B,ENSG00000128000,Cg25_male,Cg25,male,DGE,DGE,ENSG00000128000,not_gwas +male,ENSG00000141499,WRAP53,ENSG00000141499,Cg25_male,Cg25,male,DGE,DGE,ENSG00000141499,not_gwas +male,ENSG00000184524,CEND1,ENSG00000184524,Cg25_male,Cg25,male,DGE,DGE:DTE,ENSG00000184524,not_gwas +male,ENSG00000184524,CEND1,ENSG00000184524,Cg25_male,Cg25,male,DTE,DGE:DTE,ENSG00000184524,not_gwas +male,ENSG00000146416,AIG1,ENSG00000146416,Cg25_male,Cg25,male,DGE,DGE:DTE:DTU,ENSG00000146416,not_gwas +male,ENSG00000146416,AIG1,ENSG00000146416,Cg25_male,Cg25,male,DTE,DGE:DTE:DTU,ENSG00000146416,not_gwas +male,ENSG00000146416,AIG1,ENSG00000146416,Cg25_male,Cg25,male,DTU,DGE:DTE:DTU,ENSG00000146416,not_gwas +male,ENSG00000105143,SLC1A6,ENSG00000105143,Cg25_male,Cg25,male,DGE,DGE,ENSG00000105143,not_gwas +male,ENSG00000149925,ALDOA,ENSG00000149925,Cg25_male,Cg25,male,DGE,DGE,ENSG00000149925,not_gwas +male,ENSG00000184897,H1-10,ENSG00000184897,Cg25_male,Cg25,male,DGE,DGE,ENSG00000184897,not_gwas +male,ENSG00000117013,KCNQ4,ENSG00000117013,Cg25_male,Cg25,male,DGE,DGE,ENSG00000117013,not_gwas +male,ENSG00000123329,ARHGAP9,ENSG00000123329,Cg25_male,Cg25,male,DGE,DGE,ENSG00000123329,not_gwas +male,ENSG00000197121,PGAP1,ENSG00000197121,Cg25_male,Cg25,male,DGE,DGE,ENSG00000197121,not_gwas +male,ENSG00000214274,ANG,ENSG00000214274,Cg25_male,Cg25,male,DGE,DGE,ENSG00000214274,not_gwas +male,ENSG00000230097,ME2P1,ENSG00000230097,Cg25_male,Cg25,male,DGE,DGE,ENSG00000230097,not_gwas +male,ENSG00000117425,PTCH2,ENSG00000117425,Cg25_male,Cg25,male,DGE,DGE,ENSG00000117425,not_gwas +male,ENSG00000114544,SLC41A3,ENSG00000114544,Cg25_male,Cg25,male,DGE,DGE,ENSG00000114544,not_gwas +male,ENSG00000237440,ZNF737,ENSG00000237440,Cg25_male,Cg25,male,DGE,DGE,ENSG00000237440,not_gwas +male,ENSG00000197566,ZNF624,ENSG00000197566,Cg25_male,Cg25,male,DGE,DGE,ENSG00000197566,not_gwas +male,ENSG00000083457,ITGAE,ENSG00000083457,Cg25_male,Cg25,male,DGE,DGE,ENSG00000083457,not_gwas +male,ENSG00000147604,RPL7,ENSG00000147604,Cg25_male,Cg25,male,DGE,DGE,ENSG00000147604,not_gwas +male,ENSG00000114391,RPL24,ENSG00000114391,Cg25_male,Cg25,male,DGE,DGE,ENSG00000114391,not_gwas +male,ENSG00000172361,CFAP53,ENSG00000172361,Cg25_male,Cg25,male,DGE,DGE,ENSG00000172361,not_gwas +male,ENSG00000102804,TSC22D1,ENSG00000102804,Cg25_male,Cg25,male,DGE,DGE,ENSG00000102804,not_gwas +male,ENSG00000174197,MGA,ENSG00000174197,Cg25_male,Cg25,male,DGE,DGE,ENSG00000174197,not_gwas +male,ENSG00000197050,ZNF420,ENSG00000197050,Cg25_male,Cg25,male,DGE,DGE,ENSG00000197050,not_gwas +male,ENSG00000130224,LRCH2,ENSG00000130224,Cg25_male,Cg25,male,DGE,DGE,ENSG00000130224,not_gwas +male,ENSG00000167674,HDGFL2,ENSG00000167674,Cg25_male,Cg25,male,DGE,DGE:DTU,ENSG00000167674,not_gwas +male,ENSG00000167674,HDGFL2,ENSG00000167674,Cg25_male,Cg25,male,DTU,DGE:DTU,ENSG00000167674,not_gwas +male,ENSG00000219507,FTH1P8,ENSG00000219507,Cg25_male,Cg25,male,DGE,DGE,ENSG00000219507,not_gwas +male,ENSG00000177954,RPS27,ENSG00000177954,Cg25_male,Cg25,male,DGE,DGE,ENSG00000177954,not_gwas +male,ENSG00000180155,LYNX1,ENSG00000180155,Cg25_male,Cg25,male,DGE,DGE,ENSG00000180155,not_gwas +male,ENSG00000147654,EBAG9,ENSG00000147654,Cg25_male,Cg25,male,DGE,DGE,ENSG00000147654,not_gwas +male,ENSG00000198618,PPIAP22,ENSG00000198618,Cg25_male,Cg25,male,DGE,DGE,ENSG00000198618,not_gwas +male,ENSG00000070423,RNF126,ENSG00000070423,Cg25_male,Cg25,male,DGE,DGE,ENSG00000070423,not_gwas +male,ENSG00000163141,BNIPL,ENSG00000163141,Cg25_male,Cg25,male,DGE,DGE,ENSG00000163141,not_gwas +male,ENSG00000133265,HSPBP1,ENSG00000133265,Cg25_male,Cg25,male,DGE,DGE,ENSG00000133265,not_gwas +male,ENSG00000168453,HR,ENSG00000168453,Cg25_male,Cg25,male,DGE,DGE,ENSG00000168453,not_gwas +male,ENSG00000205593,DENND6B,ENSG00000205593,Cg25_male,Cg25,male,DGE,DGE,ENSG00000205593,not_gwas +male,ENSG00000179855,GIPC3,ENSG00000179855,Cg25_male,Cg25,male,DGE,DGE,ENSG00000179855,not_gwas +male,ENSG00000176222,ZNF404,ENSG00000176222,Cg25_male,Cg25,male,DGE,DGE,ENSG00000176222,not_gwas +male,ENSG00000132128,LRRC41,ENSG00000132128,Cg25_male,Cg25,male,DGE,DGE,ENSG00000132128,not_gwas +male,ENSG00000270800,RPS10-NUDT3,ENSG00000270800,Cg25_male,Cg25,male,DGE,DGE,ENSG00000270800,not_gwas +male,ENSG00000157873,TNFRSF14,ENSG00000157873,Cg25_male,Cg25,male,DGE,DGE,ENSG00000157873,not_gwas +male,ENSG00000154473,BUB3,ENSG00000154473,Cg25_male,Cg25,male,DGE,DGE:DTE,ENSG00000154473,not_gwas +male,ENSG00000154473,BUB3,ENSG00000154473,Cg25_male,Cg25,male,DTE,DGE:DTE,ENSG00000154473,not_gwas +male,ENSG00000138777,PPA2,ENSG00000138777,Cg25_male,Cg25,male,DGE,DGE,ENSG00000138777,not_gwas +male,ENSG00000198821,CD247,ENSG00000198821,Cg25_male,Cg25,male,DGE,DGE,ENSG00000198821,not_gwas +male,ENSG00000115548,KDM3A,ENSG00000115548,Cg25_male,Cg25,male,DGE,DGE,ENSG00000115548,not_gwas +male,ENSG00000112763,BTN2A1,ENSG00000112763,Cg25_male,Cg25,male,DGE,DGE:DTE,ENSG00000112763,not_gwas +male,ENSG00000112763,BTN2A1,ENSG00000112763,Sub_male,Sub,male,DTE,DGE:DTE,ENSG00000112763,not_gwas +male,ENSG00000184863,RBM33,ENSG00000184863,Cg25_male,Cg25,male,DGE,DGE:DTE,ENSG00000184863,not_gwas +male,ENSG00000184863,RBM33,ENSG00000184863,Cg25_male,Cg25,male,DTE,DGE:DTE,ENSG00000184863,not_gwas +male,ENSG00000122691,TWIST1,ENSG00000122691,Cg25_male,Cg25,male,DGE,DGE:DTE,ENSG00000122691,not_gwas +male,ENSG00000122691,TWIST1,ENSG00000122691,Cg25_male,Cg25,male,DTE,DGE:DTE,ENSG00000122691,not_gwas +male,ENSG00000275048,BSNDP1,ENSG00000275048,Cg25_male,Cg25,male,DGE,DGE,ENSG00000275048,not_gwas +male,ENSG00000256310,NDUFA5P6,ENSG00000256310,Cg25_male,Cg25,male,DGE,DGE,ENSG00000256310,not_gwas +male,ENSG00000197748,CFAP43,ENSG00000197748,Cg25_male,Cg25,male,DGE,DGE,ENSG00000197748,not_gwas +male,ENSG00000042753,AP2S1,ENSG00000042753,Cg25_male,Cg25,male,DGE,DGE,ENSG00000042753,not_gwas +male,ENSG00000138688,BLTP1,ENSG00000138688,Cg25_male,Cg25,male,DGE,DGE,ENSG00000138688,gwas +male,ENSG00000118514,ALDH8A1,ENSG00000118514,Cg25_male,Cg25,male,DGE,DGE,ENSG00000118514,not_gwas +male,ENSG00000013725,CD6,ENSG00000013725,Cg25_male,Cg25,male,DGE,DGE,ENSG00000013725,not_gwas +male,ENSG00000168000,BSCL2,ENSG00000168000,Cg25_male,Cg25,male,DGE,DGE,ENSG00000168000,not_gwas +male,ENSG00000144278,GALNT13,ENSG00000144278,Cg25_male,Cg25,male,DGE,DGE,ENSG00000144278,not_gwas +male,ENSG00000198794,SCAMP5,ENSG00000198794,Cg25_male,Cg25,male,DGE,DGE,ENSG00000198794,not_gwas +male,ENSG00000133640,LRRIQ1,ENSG00000133640,Cg25_male,Cg25,male,DGE,DGE,ENSG00000133640,not_gwas +male,ENSG00000166165,CKB,ENSG00000166165,Cg25_male,Cg25,male,DGE,DGE,ENSG00000166165,not_gwas +male,ENSG00000214076,CPSF1P1,ENSG00000214076,Cg25_male,Cg25,male,DGE,DGE,ENSG00000214076,not_gwas +male,ENSG00000214076,CPSF1P1,ENSG00000214076,Sub_male,Sub,male,DGE,DGE,ENSG00000214076,not_gwas +male,ENSG00000133067,LGR6,ENSG00000133067,Cg25_male,Cg25,male,DGE,DGE,ENSG00000133067,not_gwas +male,ENSG00000118412,CASP8AP2,ENSG00000118412,Cg25_male,Cg25,male,DGE,DGE,ENSG00000118412,not_gwas +male,ENSG00000187481,HSD3BP1,ENSG00000187481,Cg25_male,Cg25,male,DGE,DGE,ENSG00000187481,not_gwas +male,ENSG00000139675,HNRNPA1L2,ENSG00000139675,Cg25_male,Cg25,male,DGE,DGE,ENSG00000139675,not_gwas +male,ENSG00000215867,KRT18P57,ENSG00000215867,Cg25_male,Cg25,male,DGE,DGE,ENSG00000215867,not_gwas +male,ENSG00000135315,CEP162,ENSG00000135315,Cg25_male,Cg25,male,DGE,DGE,ENSG00000135315,not_gwas +male,ENSG00000065243,PKN2,ENSG00000065243,Cg25_male,Cg25,male,DGE,DGE,ENSG00000065243,not_gwas +male,ENSG00000203855,HSD3BP4,ENSG00000203855,Cg25_male,Cg25,male,DGE,DGE,ENSG00000203855,not_gwas +male,ENSG00000121989,ACVR2A,ENSG00000121989,Cg25_male,Cg25,male,DGE,DGE,ENSG00000121989,not_gwas +male,ENSG00000009694,TENM1,ENSG00000009694,Cg25_male,Cg25,male,DGE,DGE,ENSG00000009694,not_gwas +male,ENSG00000177963,RIC8A,ENSG00000177963,Cg25_male,Cg25,male,DGE,DGE,ENSG00000177963,not_gwas +male,ENSG00000220563,PKMP3,ENSG00000220563,Cg25_male,Cg25,male,DGE,DGE,ENSG00000220563,not_gwas +male,ENSG00000179611,DGKZP1,ENSG00000179611,Cg25_male,Cg25,male,DGE,DGE,ENSG00000179611,not_gwas +male,ENSG00000129317,PUS7L,ENSG00000129317,Cg25_male,Cg25,male,DGE,DGE,ENSG00000129317,not_gwas +male,ENSG00000186577,SMIM29,ENSG00000186577,Cg25_male,Cg25,male,DGE,DGE,ENSG00000186577,not_gwas +male,ENSG00000164074,ABHD18,ENSG00000164074,Cg25_male,Cg25,male,DGE,DGE,ENSG00000164074,not_gwas +male,ENSG00000171944,OR52A5,ENSG00000171944,Cg25_male,Cg25,male,DGE,DGE,ENSG00000171944,not_gwas +male,ENSG00000006015,REX1BD,ENSG00000006015,Cg25_male,Cg25,male,DGE,DGE:DTE,ENSG00000006015,not_gwas +male,ENSG00000006015,REX1BD,ENSG00000006015,Nac_male,Nac,male,DTE,DGE:DTE,ENSG00000006015,not_gwas +male,ENSG00000187416,LHFPL3,ENSG00000187416,Cg25_male,Cg25,male,DGE,DGE,ENSG00000187416,not_gwas +male,ENSG00000168539,CHRM1,ENSG00000168539,Cg25_male,Cg25,male,DGE,DGE,ENSG00000168539,not_gwas +male,ENSG00000167578,RAB4B,ENSG00000167578,Cg25_male,Cg25,male,DGE,DGE,ENSG00000167578,not_gwas +male,ENSG00000075292,ZNF638,ENSG00000075292,Cg25_male,Cg25,male,DGE,DGE,ENSG00000075292,not_gwas +male,ENSG00000143393,PI4KB,ENSG00000143393,Cg25_male,Cg25,male,DGE,DGE,ENSG00000143393,not_gwas +male,ENSG00000166575,TMEM135,ENSG00000166575,Cg25_male,Cg25,male,DGE,DGE,ENSG00000166575,not_gwas +male,ENSG00000235141,COX6CP17,ENSG00000235141,Cg25_male,Cg25,male,DGE,DGE,ENSG00000235141,not_gwas +male,ENSG00000267508,ZNF285,ENSG00000267508,Cg25_male,Cg25,male,DGE,DGE,ENSG00000267508,not_gwas +male,ENSG00000172059,KLF11,ENSG00000172059,Cg25_male,Cg25,male,DGE,DGE,ENSG00000172059,not_gwas +male,ENSG00000149582,TMEM25,ENSG00000149582,Cg25_male,Cg25,male,DGE,DGE,ENSG00000149582,not_gwas +male,ENSG00000181220,ZNF746,ENSG00000181220,Cg25_male,Cg25,male,DGE,DGE,ENSG00000181220,not_gwas +male,ENSG00000071889,FAM3A,ENSG00000071889,Cg25_male,Cg25,male,DGE,DGE,ENSG00000071889,not_gwas +male,ENSG00000136770,DNAJC1,ENSG00000136770,Cg25_male,Cg25,male,DGE,DGE,ENSG00000136770,not_gwas +male,ENSG00000153487,ING1,ENSG00000153487,Cg25_male,Cg25,male,DGE,DGE,ENSG00000153487,not_gwas +male,ENSG00000189127,ANKRD34B,ENSG00000189127,Cg25_male,Cg25,male,DGE,DGE,ENSG00000189127,not_gwas +male,ENSG00000082805,ERC1,ENSG00000082805,Cg25_male,Cg25,male,DGE,DGE,ENSG00000082805,not_gwas +male,ENSG00000203780,FANK1,ENSG00000203780,Cg25_male,Cg25,male,DGE,DGE,ENSG00000203780,not_gwas +male,ENSG00000115761,NOL10,ENSG00000115761,Cg25_male,Cg25,male,DGE,DGE,ENSG00000115761,not_gwas +male,ENSG00000113356,POLR3G,ENSG00000113356,Cg25_male,Cg25,male,DGE,DGE,ENSG00000113356,not_gwas +male,ENSG00000116663,FBXO6,ENSG00000116663,Cg25_male,Cg25,male,DGE,DGE,ENSG00000116663,not_gwas +male,ENSG00000196961,AP2A1,ENSG00000196961,Cg25_male,Cg25,male,DGE,DGE,ENSG00000196961,not_gwas +male,ENSG00000154479,CFAP210,ENSG00000154479,Cg25_male,Cg25,male,DGE,DGE,ENSG00000154479,not_gwas +male,ENSG00000198478,SH3BGRL2,ENSG00000198478,Cg25_male,Cg25,male,DGE,DGE,ENSG00000198478,not_gwas +male,ENSG00000236565,HNRNPA3P5,ENSG00000236565,Cg25_male,Cg25,male,DGE,DGE,ENSG00000236565,not_gwas +male,ENSG00000172171,TEFM,ENSG00000172171,Cg25_male,Cg25,male,DGE,DGE,ENSG00000172171,not_gwas +male,ENSG00000142186,SCYL1,ENSG00000142186,Cg25_male,Cg25,male,DGE,DGE,ENSG00000142186,not_gwas +male,ENSG00000127580,WDR24,ENSG00000127580,Cg25_male,Cg25,male,DGE,DGE,ENSG00000127580,not_gwas +male,ENSG00000215472,RPL17-C18orf32,ENSG00000215472,Cg25_male,Cg25,male,DGE,DGE,ENSG00000215472,not_gwas +male,ENSG00000141580,WDR45B,ENSG00000141580,Cg25_male,Cg25,male,DGE,DGE,ENSG00000141580,not_gwas +male,ENSG00000177200,CHD9,ENSG00000177200,Cg25_male,Cg25,male,DGE,DGE,ENSG00000177200,not_gwas +male,ENSG00000116251,RPL22,ENSG00000116251,Cg25_male,Cg25,male,DGE,DGE,ENSG00000116251,not_gwas +male,ENSG00000138180,CEP55,ENSG00000138180,Cg25_male,Cg25,male,DGE,DGE,ENSG00000138180,not_gwas +male,ENSG00000178015,GPR150,ENSG00000178015,Cg25_male,Cg25,male,DGE,DGE,ENSG00000178015,not_gwas +male,ENSG00000174516,PELI3,ENSG00000174516,Cg25_male,Cg25,male,DGE,DGE,ENSG00000174516,not_gwas +male,ENSG00000170222,ADPRM,ENSG00000170222,Cg25_male,Cg25,male,DGE,DGE,ENSG00000170222,not_gwas +male,ENSG00000091831,ESR1,ENSG00000091831,Cg25_male,Cg25,male,DGE,DGE,ENSG00000091831,not_gwas +male,ENSG00000180777,ANKRD30B,ENSG00000180777,Cg25_male,Cg25,male,DGE,DGE:DTU,ENSG00000180777,not_gwas +male,ENSG00000180777,ANKRD30B,ENSG00000180777,Cg25_male,Cg25,male,DTU,DGE:DTU,ENSG00000180777,not_gwas +male,ENSG00000155511,GRIA1,ENSG00000155511,Sub_male,Sub,male,DGE,DGE:DTE,ENSG00000155511,not_gwas +male,ENSG00000155511,GRIA1,ENSG00000155511,Sub_male,Sub,male,DTE,DGE:DTE,ENSG00000155511,not_gwas +male,ENSG00000183665,TRMT12,ENSG00000183665,Sub_male,Sub,male,DGE,DGE:DTE,ENSG00000183665,not_gwas +male,ENSG00000183665,TRMT12,ENSG00000183665,Sub_male,Sub,male,DTE,DGE:DTE,ENSG00000183665,not_gwas +male,ENSG00000053438,NNAT,ENSG00000053438,Sub_male,Sub,male,DGE,DGE:DTE,ENSG00000053438,not_gwas +male,ENSG00000053438,NNAT,ENSG00000053438,Sub_male,Sub,male,DTE,DGE:DTE,ENSG00000053438,not_gwas +male,ENSG00000183287,CCBE1,ENSG00000183287,Sub_male,Sub,male,DGE,DGE,ENSG00000183287,not_gwas +male,ENSG00000119698,PPP4R4,ENSG00000119698,Sub_male,Sub,male,DGE,DGE,ENSG00000119698,not_gwas +male,ENSG00000106069,CHN2,ENSG00000106069,Sub_male,Sub,male,DGE,DGE,ENSG00000106069,not_gwas +male,ENSG00000178163,ZNF518B,ENSG00000178163,Sub_male,Sub,male,DGE,DGE,ENSG00000178163,not_gwas +male,ENSG00000089847,ANKRD24,ENSG00000089847,Sub_male,Sub,male,DGE,DGE,ENSG00000089847,not_gwas +male,ENSG00000198046,ZNF667,ENSG00000198046,Sub_male,Sub,male,DGE,DGE,ENSG00000198046,not_gwas +male,ENSG00000147041,SYTL5,ENSG00000147041,Sub_male,Sub,male,DGE,DGE,ENSG00000147041,not_gwas +male,ENSG00000220804,LINC01881,ENSG00000220804,Sub_male,Sub,male,DGE,DGE,ENSG00000220804,not_gwas +male,ENSG00000128573,FOXP2,ENSG00000128573,Sub_male,Sub,male,DGE,DGE,ENSG00000128573,gwas +male,ENSG00000185052,SLC24A3,ENSG00000185052,Sub_male,Sub,male,DGE,DGE,ENSG00000185052,not_gwas +male,ENSG00000211896,IGHG1,ENSG00000211896,Sub_male,Sub,male,DGE,DGE,ENSG00000211896,not_gwas +male,ENSG00000156140,ADAMTS3,ENSG00000156140,Sub_male,Sub,male,DGE,DGE,ENSG00000156140,not_gwas +male,ENSG00000215388,ACTG1P3,ENSG00000215388,Sub_male,Sub,male,DGE,DGE,ENSG00000215388,not_gwas +male,ENSG00000146386,ABRACL,ENSG00000146386,Sub_male,Sub,male,DGE,DGE:DTE,ENSG00000146386,not_gwas +male,ENSG00000146386,ABRACL,ENSG00000146386,Sub_male,Sub,male,DTE,DGE:DTE,ENSG00000146386,not_gwas +male,ENSG00000163491,NEK10,ENSG00000163491,Sub_male,Sub,male,DGE,DGE,ENSG00000163491,not_gwas +male,ENSG00000168538,TRAPPC11,ENSG00000168538,Sub_male,Sub,male,DGE,DGE,ENSG00000168538,not_gwas +male,ENSG00000105518,TMEM205,ENSG00000105518,Sub_male,Sub,male,DGE,DGE,ENSG00000105518,not_gwas +male,ENSG00000114654,EFCC1,ENSG00000114654,Sub_male,Sub,male,DGE,DGE:DTE,ENSG00000114654,not_gwas +male,ENSG00000114654,EFCC1,ENSG00000114654,Nac_male,Nac,male,DTE,DGE:DTE,ENSG00000114654,not_gwas +male,ENSG00000109689,STIM2,ENSG00000109689,Sub_male,Sub,male,DGE,DGE,ENSG00000109689,not_gwas +male,ENSG00000068366,ACSL4,ENSG00000068366,Sub_male,Sub,male,DGE,DGE,ENSG00000068366,not_gwas +male,ENSG00000162066,AMDHD2,ENSG00000162066,Sub_male,Sub,male,DGE,DGE,ENSG00000162066,not_gwas +male,ENSG00000028839,TBPL1,ENSG00000028839,Sub_male,Sub,male,DGE,DGE,ENSG00000028839,not_gwas +male,ENSG00000263142,LRRC37A17P,ENSG00000263142,Sub_male,Sub,male,DGE,DGE,ENSG00000263142,not_gwas +male,ENSG00000119401,TRIM32,ENSG00000119401,Sub_male,Sub,male,DGE,DGE,ENSG00000119401,not_gwas +male,ENSG00000147400,CETN2,ENSG00000147400,Sub_male,Sub,male,DGE,DGE:DTE,ENSG00000147400,not_gwas +male,ENSG00000147400,CETN2,ENSG00000147400,Sub_male,Sub,male,DTE,DGE:DTE,ENSG00000147400,not_gwas +male,ENSG00000181467,RAP2B,ENSG00000181467,Sub_male,Sub,male,DGE,DGE,ENSG00000181467,not_gwas +male,ENSG00000151490,PTPRO,ENSG00000151490,Sub_male,Sub,male,DGE,DGE,ENSG00000151490,not_gwas +male,ENSG00000162437,RAVER2,ENSG00000162437,Sub_male,Sub,male,DGE,DGE,ENSG00000162437,not_gwas +male,ENSG00000103047,TANGO6,ENSG00000103047,Sub_male,Sub,male,DGE,DGE,ENSG00000103047,not_gwas +male,ENSG00000130347,RTN4IP1,ENSG00000130347,Sub_male,Sub,male,DGE,DGE,ENSG00000130347,not_gwas +male,ENSG00000159685,CHCHD6,ENSG00000159685,Sub_male,Sub,male,DGE,DGE,ENSG00000159685,not_gwas +male,ENSG00000136986,DERL1,ENSG00000136986,Sub_male,Sub,male,DGE,DGE,ENSG00000136986,not_gwas +male,ENSG00000109466,KLHL2,ENSG00000109466,Sub_male,Sub,male,DGE,DGE,ENSG00000109466,not_gwas +male,ENSG00000175182,FAM131A,ENSG00000175182,Sub_male,Sub,male,DGE,DGE,ENSG00000175182,not_gwas +male,ENSG00000059758,CDK17,ENSG00000059758,Sub_male,Sub,male,DGE,DGE,ENSG00000059758,not_gwas +male,ENSG00000140623,SEPTIN12,ENSG00000140623,Sub_male,Sub,male,DGE,DGE,ENSG00000140623,not_gwas +male,ENSG00000184307,ZDHHC23,ENSG00000184307,Sub_male,Sub,male,DGE,DGE,ENSG00000184307,not_gwas +male,ENSG00000154654,NCAM2,ENSG00000154654,Sub_male,Sub,male,DGE,DGE,ENSG00000154654,not_gwas +male,ENSG00000115091,ACTR3,ENSG00000115091,Sub_male,Sub,male,DGE,DGE,ENSG00000115091,not_gwas +male,ENSG00000163468,CCT3,ENSG00000163468,Sub_male,Sub,male,DGE,DGE,ENSG00000163468,not_gwas +male,ENSG00000008083,JARID2,ENSG00000008083,Sub_male,Sub,male,DGE,DGE,ENSG00000008083,not_gwas +male,ENSG00000164603,BMT2,ENSG00000164603,Sub_male,Sub,male,DGE,DGE,ENSG00000164603,not_gwas +male,ENSG00000117069,ST6GALNAC5,ENSG00000117069,Sub_male,Sub,male,DGE,DGE,ENSG00000117069,not_gwas +male,ENSG00000239649,MYADML,ENSG00000239649,Sub_male,Sub,male,DGE,DGE,ENSG00000239649,not_gwas +male,ENSG00000156414,TDRD9,ENSG00000156414,Sub_male,Sub,male,DGE,DGE,ENSG00000156414,not_gwas +male,ENSG00000102078,SLC25A14,ENSG00000102078,Sub_male,Sub,male,DGE,DGE,ENSG00000102078,not_gwas +male,ENSG00000156261,CCT8,ENSG00000156261,Sub_male,Sub,male,DGE,DGE,ENSG00000156261,not_gwas +male,ENSG00000174684,B4GAT1,ENSG00000174684,Sub_male,Sub,male,DGE,DGE,ENSG00000174684,not_gwas +male,ENSG00000271207,MTCO1P22,ENSG00000271207,Sub_male,Sub,male,DGE,DGE,ENSG00000271207,not_gwas +male,ENSG00000131747,TOP2A,ENSG00000131747,Sub_male,Sub,male,DGE,DGE,ENSG00000131747,not_gwas +male,ENSG00000219294,PIP5K1P1,ENSG00000219294,Sub_male,Sub,male,DGE,DGE,ENSG00000219294,not_gwas +male,ENSG00000198185,ZNF334,ENSG00000198185,Sub_male,Sub,male,DGE,DGE,ENSG00000198185,not_gwas +male,ENSG00000071127,WDR1,ENSG00000071127,Sub_male,Sub,male,DGE,DGE,ENSG00000071127,not_gwas +male,ENSG00000197859,ADAMTSL2,ENSG00000197859,Sub_male,Sub,male,DGE,DGE,ENSG00000197859,not_gwas +male,ENSG00000105173,CCNE1,ENSG00000105173,Sub_male,Sub,male,DGE,DGE,ENSG00000105173,not_gwas +male,ENSG00000250982,GAPDHP35,ENSG00000250982,Sub_male,Sub,male,DGE,DGE,ENSG00000250982,not_gwas +male,ENSG00000011009,LYPLA2,ENSG00000011009,Sub_male,Sub,male,DGE,DGE,ENSG00000011009,not_gwas +male,ENSG00000047249,ATP6V1H,ENSG00000047249,Sub_male,Sub,male,DGE,DGE:DTE,ENSG00000047249,not_gwas +male,ENSG00000047249,ATP6V1H,ENSG00000047249,Sub_male,Sub,male,DTE,DGE:DTE,ENSG00000047249,not_gwas +male,ENSG00000121073,SLC35B1,ENSG00000121073,Sub_male,Sub,male,DGE,DGE,ENSG00000121073,not_gwas +male,ENSG00000157211,CDCP2,ENSG00000157211,Sub_male,Sub,male,DGE,DGE,ENSG00000157211,not_gwas +male,ENSG00000102753,KPNA3,ENSG00000102753,Sub_male,Sub,male,DGE,DGE,ENSG00000102753,not_gwas +male,ENSG00000170881,RNF139,ENSG00000170881,Sub_male,Sub,male,DGE,DGE,ENSG00000170881,not_gwas +male,ENSG00000117477,CCDC181,ENSG00000117477,Sub_male,Sub,male,DGE,DGE,ENSG00000117477,not_gwas +male,ENSG00000229184,ATP5PDP2,ENSG00000229184,Sub_male,Sub,male,DGE,DGE,ENSG00000229184,not_gwas +male,ENSG00000145050,MANF,ENSG00000145050,Sub_male,Sub,male,DGE,DGE,ENSG00000145050,not_gwas +male,ENSG00000128595,CALU,ENSG00000128595,Sub_male,Sub,male,DGE,DGE,ENSG00000128595,not_gwas +male,ENSG00000206145,P2RX6P,ENSG00000206145,Sub_male,Sub,male,DGE,DGE,ENSG00000206145,not_gwas +male,ENSG00000160087,UBE2J2,ENSG00000160087,Sub_male,Sub,male,DGE,DGE,ENSG00000160087,not_gwas +male,ENSG00000176956,LY6H,ENSG00000176956,Sub_male,Sub,male,DGE,DGE:DTE,ENSG00000176956,not_gwas +male,ENSG00000176956,LY6H,ENSG00000176956,aINS_male,aINS,male,DTE,DGE:DTE,ENSG00000176956,not_gwas +male,ENSG00000169976,SF3B5,ENSG00000169976,Sub_male,Sub,male,DGE,DGE,ENSG00000169976,not_gwas +male,ENSG00000079689,SCGN,ENSG00000079689,Sub_male,Sub,male,DGE,DGE,ENSG00000079689,not_gwas +male,ENSG00000242372,EIF6,ENSG00000242372,Sub_male,Sub,male,DGE,DGE,ENSG00000242372,not_gwas +male,ENSG00000168036,CTNNB1,ENSG00000168036,Sub_male,Sub,male,DGE,DGE,ENSG00000168036,not_gwas +male,ENSG00000270326,SMIM15P2,ENSG00000270326,Sub_male,Sub,male,DGE,DGE,ENSG00000270326,not_gwas +male,ENSG00000133872,SARAF,ENSG00000133872,Sub_male,Sub,male,DGE,DGE,ENSG00000133872,not_gwas +male,ENSG00000108256,NUFIP2,ENSG00000108256,Sub_male,Sub,male,DGE,DGE,ENSG00000108256,not_gwas +male,ENSG00000164080,RAD54L2,ENSG00000164080,Sub_male,Sub,male,DGE,DGE,ENSG00000164080,not_gwas +male,ENSG00000259330,INAFM2,ENSG00000259330,Sub_male,Sub,male,DGE,DGE,ENSG00000259330,not_gwas +male,ENSG00000165905,LARGE2,ENSG00000165905,Sub_male,Sub,male,DGE,DGE,ENSG00000165905,not_gwas +male,ENSG00000277883,NLRP3P1,ENSG00000277883,Sub_male,Sub,male,DGE,DGE,ENSG00000277883,not_gwas +male,ENSG00000117543,DPH5,ENSG00000117543,Sub_male,Sub,male,DGE,DGE,ENSG00000117543,not_gwas +male,ENSG00000185272,RBM11,ENSG00000185272,Sub_male,Sub,male,DGE,DGE,ENSG00000185272,not_gwas +male,ENSG00000189369,GSPT2,ENSG00000189369,Sub_male,Sub,male,DGE,DGE,ENSG00000189369,not_gwas +male,ENSG00000114480,GBE1,ENSG00000114480,Sub_male,Sub,male,DGE,DGE,ENSG00000114480,not_gwas +male,ENSG00000154262,ABCA6,ENSG00000154262,Sub_male,Sub,male,DGE,DGE,ENSG00000154262,not_gwas +male,ENSG00000160973,FOXH1,ENSG00000160973,Sub_male,Sub,male,DGE,DGE,ENSG00000160973,not_gwas +male,ENSG00000185187,SIGIRR,ENSG00000185187,Sub_male,Sub,male,DGE,DGE,ENSG00000185187,not_gwas +male,ENSG00000174567,GOLT1A,ENSG00000174567,Sub_male,Sub,male,DGE,DGE,ENSG00000174567,not_gwas +male,ENSG00000161960,EIF4A1,ENSG00000161960,Sub_male,Sub,male,DGE,DGE,ENSG00000161960,not_gwas +male,ENSG00000108641,B9D1,ENSG00000108641,Sub_male,Sub,male,DGE,DGE,ENSG00000108641,not_gwas +male,ENSG00000065183,WDR3,ENSG00000065183,Sub_male,Sub,male,DGE,DGE,ENSG00000065183,not_gwas +male,ENSG00000189045,ANKDD1B,ENSG00000189045,Sub_male,Sub,male,DGE,DGE,ENSG00000189045,not_gwas +male,ENSG00000059769,DNAJC25,ENSG00000059769,Sub_male,Sub,male,DGE,DGE,ENSG00000059769,not_gwas +male,ENSG00000163630,SYNPR,ENSG00000163630,Sub_male,Sub,male,DGE,DGE,ENSG00000163630,not_gwas +male,ENSG00000132463,GRSF1,ENSG00000132463,Sub_male,Sub,male,DGE,DGE,ENSG00000132463,not_gwas +male,ENSG00000116906,GNPAT,ENSG00000116906,Sub_male,Sub,male,DGE,DGE,ENSG00000116906,not_gwas +male,ENSG00000089169,RPH3A,ENSG00000089169,Sub_male,Sub,male,DGE,DGE,ENSG00000089169,not_gwas +male,ENSG00000125870,SNRPB2,ENSG00000125870,Sub_male,Sub,male,DGE,DGE,ENSG00000125870,not_gwas +male,ENSG00000253729,PRKDC,ENSG00000253729,Sub_male,Sub,male,DGE,DGE,ENSG00000253729,not_gwas +male,ENSG00000123496,IL13RA2,ENSG00000123496,Sub_male,Sub,male,DGE,DGE,ENSG00000123496,not_gwas +male,ENSG00000169282,KCNAB1,ENSG00000169282,Sub_male,Sub,male,DGE,DGE,ENSG00000169282,not_gwas +male,ENSG00000165688,PMPCA,ENSG00000165688,Sub_male,Sub,male,DGE,DGE,ENSG00000165688,not_gwas +male,ENSG00000166128,RAB8B,ENSG00000166128,Sub_male,Sub,male,DGE,DGE,ENSG00000166128,not_gwas +male,ENSG00000274286,ADRA2B,ENSG00000274286,Sub_male,Sub,male,DGE,DGE,ENSG00000274286,not_gwas +male,ENSG00000221968,FADS3,ENSG00000221968,Nac_male,Nac,male,DTE,DTE,ENSG00000221968,not_gwas +male,ENSG00000144550,CPNE9,ENSG00000144550,Nac_male,Nac,male,DTE,DTE,ENSG00000144550,not_gwas +male,ENSG00000132386,SERPINF1,ENSG00000132386,Nac_male,Nac,male,DTE,DTE,ENSG00000132386,not_gwas +male,ENSG00000166257,SCN3B,ENSG00000166257,Nac_male,Nac,male,DTE,DTE,ENSG00000166257,not_gwas +male,ENSG00000144868,TMEM108,ENSG00000144868,Nac_male,Nac,male,DTE,DTE,ENSG00000144868,not_gwas +male,ENSG00000103245,CIAO3,ENSG00000103245,Nac_male,Nac,male,DTE,DTE,ENSG00000103245,not_gwas +male,ENSG00000162601,MYSM1,ENSG00000162601,Nac_male,Nac,male,DTE,DTE,ENSG00000162601,not_gwas +male,ENSG00000178719,GRINA,ENSG00000178719,Nac_male,Nac,male,DTE,DTE,ENSG00000178719,not_gwas +male,ENSG00000132640,BTBD3,ENSG00000132640,Nac_male,Nac,male,DTE,DTE,ENSG00000132640,not_gwas +male,ENSG00000174996,KLC2,ENSG00000174996,Nac_male,Nac,male,DTE,DTE,ENSG00000174996,not_gwas +male,ENSG00000145715,RASA1,ENSG00000145715,Nac_male,Nac,male,DTE,DTE,ENSG00000145715,not_gwas +male,ENSG00000006283,CACNA1G,ENSG00000006283,Nac_male,Nac,male,DTE,DTE,ENSG00000006283,not_gwas +male,ENSG00000105711,SCN1B,ENSG00000105711,Nac_male,Nac,male,DTE,DTE,ENSG00000105711,not_gwas +male,ENSG00000157214,STEAP2,ENSG00000157214,Nac_male,Nac,male,DTE,DTE,ENSG00000157214,not_gwas +male,ENSG00000176697,BDNF,ENSG00000176697,Nac_male,Nac,male,DTE,DTE,ENSG00000176697,not_gwas +male,ENSG00000162300,ZFPL1,ENSG00000162300,Nac_male,Nac,male,DTE,DTE,ENSG00000162300,not_gwas +male,ENSG00000040608,RTN4R,ENSG00000040608,Nac_male,Nac,male,DTE,DTE,ENSG00000040608,not_gwas +male,ENSG00000179603,GRM8,ENSG00000179603,Nac_male,Nac,male,DTE,DTE,ENSG00000179603,not_gwas +male,ENSG00000162520,SYNC,ENSG00000162520,Nac_male,Nac,male,DTE,DTE,ENSG00000162520,not_gwas +male,ENSG00000073849,ST6GAL1,ENSG00000073849,Nac_male,Nac,male,DTE,DTE,ENSG00000073849,not_gwas +male,ENSG00000116991,SIPA1L2,ENSG00000116991,Nac_male,Nac,male,DTE,DTE,ENSG00000116991,not_gwas +male,ENSG00000165804,ZNF219,ENSG00000165804,Nac_male,Nac,male,DTE,DTE,ENSG00000165804,not_gwas +male,ENSG00000205221,VIT,ENSG00000205221,Nac_male,Nac,male,DTE,DTE,ENSG00000205221,not_gwas +male,ENSG00000121064,SCPEP1,ENSG00000121064,Nac_male,Nac,male,DTE,DTE,ENSG00000121064,not_gwas +male,ENSG00000164294,GPX8,ENSG00000164294,Nac_male,Nac,male,DTE,DTE,ENSG00000164294,not_gwas +male,ENSG00000105204,DYRK1B,ENSG00000105204,Nac_male,Nac,male,DTE,DTE,ENSG00000105204,not_gwas +male,ENSG00000166558,SLC38A8,ENSG00000166558,Nac_male,Nac,male,DTE,DTE,ENSG00000166558,not_gwas +male,ENSG00000125656,CLPP,ENSG00000125656,Nac_male,Nac,male,DTE,DTE,ENSG00000125656,not_gwas +male,ENSG00000176383,B3GNT4,ENSG00000176383,Nac_male,Nac,male,DTE,DTE,ENSG00000176383,not_gwas +male,ENSG00000106689,LHX2,ENSG00000106689,Nac_male,Nac,male,DTE,DTE,ENSG00000106689,not_gwas +male,ENSG00000203734,ECT2L,ENSG00000203734,Nac_male,Nac,male,DTE,DTE,ENSG00000203734,not_gwas +male,ENSG00000153395,LPCAT1,ENSG00000153395,Nac_male,Nac,male,DTE,DTE,ENSG00000153395,not_gwas +male,ENSG00000108219,TSPAN14,ENSG00000108219,Nac_male,Nac,male,DTE,DTE,ENSG00000108219,not_gwas +male,ENSG00000143093,STRIP1,ENSG00000143093,Nac_male,Nac,male,DTE,DTE,ENSG00000143093,not_gwas +male,ENSG00000159110,IFNAR2,ENSG00000159110,Nac_male,Nac,male,DTE,DTE,ENSG00000159110,not_gwas +male,ENSG00000143740,SNAP47,ENSG00000143740,Nac_male,Nac,male,DTE,DTE,ENSG00000143740,not_gwas +male,ENSG00000117632,STMN1,ENSG00000117632,Nac_male,Nac,male,DTE,DTE,ENSG00000117632,not_gwas +male,ENSG00000277161,PIGW,ENSG00000277161,Nac_male,Nac,male,DTE,DTE,ENSG00000277161,not_gwas +male,ENSG00000104341,LAPTM4B,ENSG00000104341,Nac_male,Nac,male,DTE,DTE,ENSG00000104341,not_gwas +male,ENSG00000147457,CHMP7,ENSG00000147457,Nac_male,Nac,male,DTE,DTE,ENSG00000147457,not_gwas +male,ENSG00000148832,PAOX,ENSG00000148832,Nac_male,Nac,male,DTE,DTE,ENSG00000148832,not_gwas +male,ENSG00000265366,GLUD1P2,ENSG00000265366,Nac_male,Nac,male,DTE,DTE,ENSG00000265366,not_gwas +male,ENSG00000178404,CEP295NL,ENSG00000178404,Nac_male,Nac,male,DTE,DTE,ENSG00000178404,not_gwas +male,ENSG00000104976,SNAPC2,ENSG00000104976,Nac_male,Nac,male,DTE,DTE,ENSG00000104976,not_gwas +male,ENSG00000238227,TMEM250,ENSG00000238227,Nac_male,Nac,male,DTE,DTE,ENSG00000238227,not_gwas +male,ENSG00000198483,ANKRD35,ENSG00000198483,Nac_male,Nac,male,DTE,DTE,ENSG00000198483,not_gwas +male,ENSG00000106236,NPTX2,ENSG00000106236,Nac_male,Nac,male,DTE,DTE,ENSG00000106236,not_gwas +male,ENSG00000143630,HCN3,ENSG00000143630,Nac_male,Nac,male,DTE,DTE,ENSG00000143630,not_gwas +male,ENSG00000143630,HCN3,ENSG00000143630,dlPFC_male,dlPFC,male,DTE,DTE,ENSG00000143630,not_gwas +male,ENSG00000160949,TONSL,ENSG00000160949,Nac_male,Nac,male,DTE,DTE,ENSG00000160949,not_gwas +male,ENSG00000101333,PLCB4,ENSG00000101333,Nac_male,Nac,male,DTE,DTE,ENSG00000101333,not_gwas +male,ENSG00000188878,FBF1,ENSG00000188878,OFC_male,OFC,male,DTE,DTE,ENSG00000188878,not_gwas +male,ENSG00000217128,FNIP1,ENSG00000217128,OFC_male,OFC,male,DTE,DTE,ENSG00000217128,not_gwas +male,ENSG00000137411,VARS2,ENSG00000137411,OFC_male,OFC,male,DTE,DTE,ENSG00000137411,not_gwas +male,ENSG00000163016,ALMS1P1,ENSG00000163016,OFC_male,OFC,male,DTE,DTE,ENSG00000163016,not_gwas +male,ENSG00000154358,OBSCN,ENSG00000154358,OFC_male,OFC,male,DTE,DTE,ENSG00000154358,not_gwas +male,ENSG00000188343,CIBAR1,ENSG00000188343,OFC_male,OFC,male,DTE,DTE,ENSG00000188343,not_gwas +male,ENSG00000117153,KLHL12,ENSG00000117153,OFC_male,OFC,male,DTE,DTE,ENSG00000117153,not_gwas +male,ENSG00000104883,PEX11G,ENSG00000104883,OFC_male,OFC,male,DTE,DTE:DTU,ENSG00000104883,not_gwas +male,ENSG00000104883,PEX11G,ENSG00000104883,OFC_male,OFC,male,DTU,DTE:DTU,ENSG00000104883,not_gwas +male,ENSG00000174292,TNK1,ENSG00000174292,OFC_male,OFC,male,DTE,DTE,ENSG00000174292,not_gwas +male,ENSG00000159247,TUBBP5,ENSG00000159247,OFC_male,OFC,male,DTE,DTE,ENSG00000159247,not_gwas +male,ENSG00000185803,SLC52A2,ENSG00000185803,OFC_male,OFC,male,DTE,DTE,ENSG00000185803,not_gwas +male,ENSG00000140835,CHST4,ENSG00000140835,OFC_male,OFC,male,DTE,DTE,ENSG00000140835,not_gwas +male,ENSG00000133105,RXFP2,ENSG00000133105,OFC_male,OFC,male,DTE,DTE,ENSG00000133105,not_gwas +male,ENSG00000133105,RXFP2,ENSG00000133105,aINS_male,aINS,male,DTE,DTE,ENSG00000133105,not_gwas +male,ENSG00000170579,DLGAP1,ENSG00000170579,dlPFC_male,dlPFC,male,DTE,DTE,ENSG00000170579,not_gwas +male,ENSG00000165874,SHLD2P1,ENSG00000165874,dlPFC_male,dlPFC,male,DTE,DTE,ENSG00000165874,not_gwas +male,ENSG00000173598,NUDT4,ENSG00000173598,dlPFC_male,dlPFC,male,DTE,DTE,ENSG00000173598,not_gwas +male,ENSG00000100138,SNU13,ENSG00000100138,dlPFC_male,dlPFC,male,DTE,DTE,ENSG00000100138,not_gwas +male,ENSG00000141404,GNAL,ENSG00000141404,dlPFC_male,dlPFC,male,DTE,DTE,ENSG00000141404,not_gwas +male,ENSG00000152672,CLEC4F,ENSG00000152672,dlPFC_male,dlPFC,male,DTE,DTE,ENSG00000152672,not_gwas +male,ENSG00000172969,FRG2C,ENSG00000172969,Cg25_male,Cg25,male,DTE,DTE,ENSG00000172969,not_gwas +male,ENSG00000070961,ATP2B1,ENSG00000070961,Cg25_male,Cg25,male,DTE,DTE,ENSG00000070961,not_gwas +male,ENSG00000213047,DENND1B,ENSG00000213047,Cg25_male,Cg25,male,DTE,DTE,ENSG00000213047,gwas +male,ENSG00000109971,HSPA8,ENSG00000109971,Cg25_male,Cg25,male,DTE,DTE,ENSG00000109971,not_gwas +male,ENSG00000205609,EIF3CL,ENSG00000205609,Cg25_male,Cg25,male,DTE,DTE,ENSG00000205609,not_gwas +male,ENSG00000074317,SNCB,ENSG00000074317,Cg25_male,Cg25,male,DTE,DTE,ENSG00000074317,not_gwas +male,ENSG00000196498,NCOR2,ENSG00000196498,Cg25_male,Cg25,male,DTE,DTE,ENSG00000196498,not_gwas +male,ENSG00000164483,SAMD3,ENSG00000164483,Cg25_male,Cg25,male,DTE,DTE,ENSG00000164483,not_gwas +male,ENSG00000172809,RPL38,ENSG00000172809,Cg25_male,Cg25,male,DTE,DTE,ENSG00000172809,not_gwas +male,ENSG00000076248,UNG,ENSG00000076248,Cg25_male,Cg25,male,DTE,DTE,ENSG00000076248,not_gwas +male,ENSG00000076248,UNG,ENSG00000076248,Sub_male,Sub,male,DTE,DTE,ENSG00000076248,not_gwas +male,ENSG00000084207,GSTP1,ENSG00000084207,Cg25_male,Cg25,male,DTE,DTE,ENSG00000084207,not_gwas +male,ENSG00000152208,GRID2,ENSG00000152208,Cg25_male,Cg25,male,DTE,DTE,ENSG00000152208,not_gwas +male,ENSG00000153207,AHCTF1,ENSG00000153207,Cg25_male,Cg25,male,DTE,DTE,ENSG00000153207,not_gwas +male,ENSG00000130204,TOMM40,ENSG00000130204,Cg25_male,Cg25,male,DTE,DTE:DTU,ENSG00000130204,not_gwas +male,ENSG00000130204,TOMM40,ENSG00000130204,Cg25_male,Cg25,male,DTU,DTE:DTU,ENSG00000130204,not_gwas +male,ENSG00000135686,KLHL36,ENSG00000135686,Cg25_male,Cg25,male,DTE,DTE,ENSG00000135686,not_gwas +male,ENSG00000139200,PIANP,ENSG00000139200,Cg25_male,Cg25,male,DTE,DTE,ENSG00000139200,not_gwas +male,ENSG00000145826,LECT2,ENSG00000145826,Cg25_male,Cg25,male,DTE,DTE,ENSG00000145826,not_gwas +male,ENSG00000163596,ICA1L,ENSG00000163596,Cg25_male,Cg25,male,DTE,DTE,ENSG00000163596,not_gwas +male,ENSG00000242173,ARHGDIG,ENSG00000242173,Cg25_male,Cg25,male,DTE,DTE,ENSG00000242173,not_gwas +male,ENSG00000124172,ATP5F1E,ENSG00000124172,Cg25_male,Cg25,male,DTE,DTE,ENSG00000124172,not_gwas +male,ENSG00000186350,RXRA,ENSG00000186350,aINS_male,aINS,male,DTE,DTE,ENSG00000186350,not_gwas +male,ENSG00000151718,WWC2,ENSG00000151718,aINS_male,aINS,male,DTE,DTE,ENSG00000151718,not_gwas +male,ENSG00000008382,MPND,ENSG00000008382,aINS_male,aINS,male,DTE,DTE,ENSG00000008382,not_gwas +male,ENSG00000157557,ETS2,ENSG00000157557,aINS_male,aINS,male,DTE,DTE,ENSG00000157557,not_gwas +male,ENSG00000099364,FBXL19,ENSG00000099364,aINS_male,aINS,male,DTE,DTE,ENSG00000099364,not_gwas +male,ENSG00000090097,PCBP4,ENSG00000090097,Sub_male,Sub,male,DTE,DTE,ENSG00000090097,not_gwas +male,ENSG00000145526,CDH18,ENSG00000145526,Sub_male,Sub,male,DTE,DTE,ENSG00000145526,not_gwas +male,ENSG00000141013,GAS8,ENSG00000141013,Sub_male,Sub,male,DTE,DTE,ENSG00000141013,not_gwas +male,ENSG00000221882,OR3A2,ENSG00000221882,Sub_male,Sub,male,DTE,DTE,ENSG00000221882,not_gwas +male,ENSG00000143156,NME7,ENSG00000143156,Sub_male,Sub,male,DTE,DTE,ENSG00000143156,not_gwas +male,ENSG00000164099,PRSS12,ENSG00000164099,Sub_male,Sub,male,DTE,DTE,ENSG00000164099,not_gwas +male,ENSG00000120500,ARR3,ENSG00000120500,Sub_male,Sub,male,DTE,DTE,ENSG00000120500,not_gwas +male,ENSG00000057294,PKP2,ENSG00000057294,Sub_male,Sub,male,DTE,DTE,ENSG00000057294,not_gwas +male,ENSG00000144668,ITGA9,ENSG00000144668,Sub_male,Sub,male,DTE,DTE,ENSG00000144668,not_gwas +male,ENSG00000186204,CYP4F12,ENSG00000186204,Sub_male,Sub,male,DTE,DTE,ENSG00000186204,not_gwas +male,ENSG00000115649,CNPPD1,ENSG00000115649,Sub_male,Sub,male,DTE,DTE,ENSG00000115649,not_gwas +male,ENSG00000184009,ACTG1,ENSG00000184009,Cg25_male,Cg25,male,DTU,DTU,ENSG00000184009,not_gwas +male,ENSG00000140873,ADAMTS18,ENSG00000140873,Cg25_male,Cg25,male,DTU,DTU,ENSG00000140873,not_gwas +male,ENSG00000173567,ADGRF3,ENSG00000173567,Cg25_male,Cg25,male,DTU,DTU,ENSG00000173567,not_gwas +male,ENSG00000112414,ADGRG6,ENSG00000112414,Cg25_male,Cg25,male,DTU,DTU,ENSG00000112414,not_gwas +male,ENSG00000162618,ADGRL4,ENSG00000162618,Cg25_male,Cg25,male,DTU,DTU,ENSG00000162618,not_gwas +male,ENSG00000106624,AEBP1,ENSG00000106624,Cg25_male,Cg25,male,DTU,DTU,ENSG00000106624,not_gwas +male,ENSG00000057663,ATG5,ENSG00000057663,Cg25_male,Cg25,male,DTU,DTU,ENSG00000057663,not_gwas +male,ENSG00000139044,B4GALNT3,ENSG00000139044,Cg25_male,Cg25,male,DTU,DTU,ENSG00000139044,not_gwas +male,ENSG00000152611,CAPSL,ENSG00000152611,Cg25_male,Cg25,male,DTU,DTU,ENSG00000152611,not_gwas +male,ENSG00000291173,CASP17P,ENSG00000291173,Cg25_male,Cg25,male,DTU,DTU,ENSG00000291173,not_gwas +male,ENSG00000141570,CBX8,ENSG00000141570,Cg25_male,Cg25,male,DTU,DTU,ENSG00000141570,not_gwas +male,ENSG00000134057,CCNB1,ENSG00000134057,Cg25_male,Cg25,male,DTU,DTU,ENSG00000134057,not_gwas +male,ENSG00000107443,CCNJ,ENSG00000107443,Cg25_male,Cg25,male,DTU,DTU,ENSG00000107443,not_gwas +male,ENSG00000116815,CD58,ENSG00000116815,Cg25_male,Cg25,male,DTU,DTU,ENSG00000116815,not_gwas +male,ENSG00000166091,CMTM5,ENSG00000166091,Cg25_male,Cg25,male,DTU,DTU,ENSG00000166091,not_gwas +male,ENSG00000102879,CORO1A,ENSG00000102879,Cg25_male,Cg25,male,DTU,DTU,ENSG00000102879,not_gwas +male,ENSG00000116133,DHCR24,ENSG00000116133,Cg25_male,Cg25,male,DTU,DTU,ENSG00000116133,not_gwas +male,ENSG00000134516,DOCK2,ENSG00000134516,Cg25_male,Cg25,male,DTU,DTU,ENSG00000134516,not_gwas +male,ENSG00000100129,EIF3L,ENSG00000100129,Cg25_male,Cg25,male,DTU,DTU,ENSG00000100129,not_gwas +male,ENSG00000240445,FOXO3B,ENSG00000240445,Cg25_male,Cg25,male,DTU,DTU,ENSG00000240445,not_gwas +male,ENSG00000105255,FSD1,ENSG00000105255,Cg25_male,Cg25,male,DTU,DTU,ENSG00000105255,not_gwas +male,ENSG00000226124,FTCDNL1,ENSG00000226124,Cg25_male,Cg25,male,DTU,DTU,ENSG00000226124,not_gwas +male,ENSG00000144591,GMPPA,ENSG00000144591,Cg25_male,Cg25,male,DTU,DTU,ENSG00000144591,not_gwas +male,ENSG00000102241,HTATSF1,ENSG00000102241,Cg25_male,Cg25,male,DTU,DTU,ENSG00000102241,not_gwas +male,ENSG00000110324,IL10RA,ENSG00000110324,Cg25_male,Cg25,male,DTU,DTU,ENSG00000110324,not_gwas +male,ENSG00000148943,LIN7C,ENSG00000148943,Cg25_male,Cg25,male,DTU,DTU,ENSG00000148943,not_gwas +male,ENSG00000146006,LRRTM2,ENSG00000146006,Cg25_male,Cg25,male,DTU,DTU,ENSG00000146006,not_gwas +male,ENSG00000168067,MAP4K2,ENSG00000168067,Cg25_male,Cg25,male,DTU,DTU,ENSG00000168067,not_gwas +male,ENSG00000090971,"NAT14",ENSG00000090971,Cg25_male,Cg25,male,DTU,DTU,ENSG00000090971,not_gwas +male,ENSG00000178685,PARP10,ENSG00000178685,Cg25_male,Cg25,male,DTU,DTU,ENSG00000178685,not_gwas +male,ENSG00000174827,PDZK1,ENSG00000174827,Cg25_male,Cg25,male,DTU,DTU,ENSG00000174827,not_gwas +male,ENSG00000183571,PGPEP1L,ENSG00000183571,Cg25_male,Cg25,male,DTU,DTU,ENSG00000183571,not_gwas +male,ENSG00000166428,PLD4,ENSG00000166428,Cg25_male,Cg25,male,DTU,DTU,ENSG00000166428,not_gwas +male,ENSG00000163932,PRKCD,ENSG00000163932,Cg25_male,Cg25,male,DTU,DTU,ENSG00000163932,not_gwas +male,ENSG00000204628,RACK1,ENSG00000204628,Cg25_male,Cg25,male,DTU,DTU,ENSG00000204628,not_gwas +male,ENSG00000117602,RCAN3,ENSG00000117602,Cg25_male,Cg25,male,DTU,DTU,ENSG00000117602,not_gwas +male,ENSG00000137275,RIPK1,ENSG00000137275,Cg25_male,Cg25,male,DTU,DTU,ENSG00000137275,not_gwas +male,ENSG00000164610,RP9,ENSG00000164610,Cg25_male,Cg25,male,DTU,DTU,ENSG00000164610,not_gwas +male,ENSG00000149273,RPS3,ENSG00000149273,Cg25_male,Cg25,male,DTU,DTU,ENSG00000149273,not_gwas +male,ENSG00000063015,SEZ6,ENSG00000063015,Cg25_male,Cg25,male,DTU,DTU,ENSG00000063015,not_gwas +male,ENSG00000167447,SMG8,ENSG00000167447,Cg25_male,Cg25,male,DTU,DTU,ENSG00000167447,not_gwas +male,ENSG00000250317,SMIM20,ENSG00000250317,Cg25_male,Cg25,male,DTU,DTU,ENSG00000250317,not_gwas +male,ENSG00000077312,SNRPA,ENSG00000077312,Cg25_male,Cg25,male,DTU,DTU,ENSG00000077312,not_gwas +male,ENSG00000162236,STX5,ENSG00000162236,Cg25_male,Cg25,male,DTU,DTU,ENSG00000162236,not_gwas +male,ENSG00000132604,TERF2,ENSG00000132604,Cg25_male,Cg25,male,DTU,DTU,ENSG00000132604,not_gwas +male,ENSG00000145107,TM4SF19,ENSG00000145107,Cg25_male,Cg25,male,DTU,DTU,ENSG00000145107,not_gwas +male,ENSG00000118271,TTR,ENSG00000118271,Cg25_male,Cg25,male,DTU,DTU,ENSG00000118271,not_gwas +male,ENSG00000140367,UBE2Q2,ENSG00000140367,Cg25_male,Cg25,male,DTU,DTU,ENSG00000140367,not_gwas +male,ENSG00000167671,UBXN6,ENSG00000167671,Cg25_male,Cg25,male,DTU,DTU,ENSG00000167671,not_gwas +male,ENSG00000111186,WNT5B,ENSG00000111186,Cg25_male,Cg25,male,DTU,DTU,ENSG00000111186,not_gwas +male,ENSG00000198538,ZNF28,ENSG00000198538,Cg25_male,Cg25,male,DTU,DTU,ENSG00000198538,not_gwas +male,ENSG00000167772,ANGPTL4,ENSG00000167772,dlPFC_male,dlPFC,male,DTU,DTU,ENSG00000167772,not_gwas +male,ENSG00000185689,C6orf201,ENSG00000185689,dlPFC_male,dlPFC,male,DTU,DTU,ENSG00000185689,not_gwas +male,ENSG00000147437,GNRH1,ENSG00000147437,dlPFC_male,dlPFC,male,DTU,DTU,ENSG00000147437,not_gwas +male,ENSG00000116962,NID1,ENSG00000116962,dlPFC_male,dlPFC,male,DTU,DTU,ENSG00000116962,not_gwas +male,ENSG00000163710,PCOLCE2,ENSG00000163710,dlPFC_male,dlPFC,male,DTU,DTU,ENSG00000163710,not_gwas +male,ENSG00000056487,PHF21B,ENSG00000056487,dlPFC_male,dlPFC,male,DTU,DTU,ENSG00000056487,not_gwas +male,ENSG00000174136,RGMB,ENSG00000174136,dlPFC_male,dlPFC,male,DTU,DTU,ENSG00000174136,not_gwas +male,ENSG00000167550,RHEBL1,ENSG00000167550,dlPFC_male,dlPFC,male,DTU,DTU,ENSG00000167550,not_gwas +male,ENSG00000116649,SRM,ENSG00000116649,dlPFC_male,dlPFC,male,DTU,DTU,ENSG00000116649,not_gwas +male,ENSG00000248477,AC139495,ENSG00000248477,Nac_male,Nac,male,DTU,DTU,ENSG00000248477,not_gwas +male,ENSG00000250687,AC146944,ENSG00000250687,Nac_male,Nac,male,DTU,DTU,ENSG00000250687,not_gwas +male,ENSG00000008300,CELSR3,ENSG00000008300,Nac_male,Nac,male,DTU,DTU,ENSG00000008300,not_gwas +male,ENSG00000185885,IFITM1,ENSG00000185885,Nac_male,Nac,male,DTU,DTU,ENSG00000185885,not_gwas +male,ENSG00000073150,PANX2,ENSG00000073150,Nac_male,Nac,male,DTU,DTU,ENSG00000073150,not_gwas +male,ENSG00000225973,PIGBOS1,ENSG00000225973,Nac_male,Nac,male,DTU,DTU,ENSG00000225973,not_gwas +male,ENSG00000061492,WNT8A,ENSG00000061492,Nac_male,Nac,male,DTU,DTU,ENSG00000061492,not_gwas +male,ENSG00000100601,ALKBH1,ENSG00000100601,OFC_male,OFC,male,DTU,DTU,ENSG00000100601,not_gwas +male,ENSG00000215217,C5orf49,ENSG00000215217,OFC_male,OFC,male,DTU,DTU,ENSG00000215217,not_gwas +male,ENSG00000103326,CAPN15,ENSG00000103326,OFC_male,OFC,male,DTU,DTU,ENSG00000103326,not_gwas +male,ENSG00000105479,CCDC114,ENSG00000105479,OFC_male,OFC,male,DTU,DTU,ENSG00000105479,not_gwas +male,ENSG00000248698,LINC01085,ENSG00000248698,OFC_male,OFC,male,DTU,DTU,ENSG00000248698,not_gwas +male,ENSG00000125841,NRSN2,ENSG00000125841,OFC_male,OFC,male,DTU,DTU,ENSG00000125841,not_gwas +male,ENSG00000100300,TSPO,ENSG00000100300,OFC_male,OFC,male,DTU,DTU,ENSG00000100300,not_gwas +male,ENSG00000160685,ZBTB7B,ENSG00000160685,OFC_male,OFC,male,DTU,DTU,ENSG00000160685,not_gwas +male,ENSG00000184887,BTBD6,ENSG00000184887,Sub_male,Sub,male,DTU,DTU,ENSG00000184887,not_gwas +male,ENSG00000177627,C12orf54,ENSG00000177627,Sub_male,Sub,male,DTU,DTU,ENSG00000177627,not_gwas +male,ENSG00000221986,MYBPHL,ENSG00000221986,Sub_male,Sub,male,DTU,DTU,ENSG00000221986,not_gwas +male,ENSG00000205220,PSMB10,ENSG00000205220,Sub_male,Sub,male,DTU,DTU,ENSG00000205220,not_gwas +male,ENSG00000165480,SKA3,ENSG00000165480,Sub_male,Sub,male,DTU,DTU,ENSG00000165480,not_gwas +male,ENSG00000095970,TREM2,ENSG00000095970,Sub_male,Sub,male,DTU,DTU,ENSG00000095970,not_gwas +male,ENSG00000170703,TTLL6,ENSG00000170703,Sub_male,Sub,male,DTU,DTU,ENSG00000170703,not_gwas +female,ENSG00000197057,DTHD1,ENSG00000197057,Nac_female,Nac,female,DGE,DGE,ENSG00000197057,not_gwas +female,ENSG00000179813,FAM216B,ENSG00000179813,Nac_female,Nac,female,DGE,DGE,ENSG00000179813,not_gwas +female,ENSG00000213085,CFAP45,ENSG00000213085,Nac_female,Nac,female,DGE,DGE,ENSG00000213085,not_gwas +female,ENSG00000268500,SIGLEC5,ENSG00000268500,Nac_female,Nac,female,DGE,DGE,ENSG00000268500,not_gwas +female,ENSG00000089041,P2RX7,ENSG00000089041,Nac_female,Nac,female,DGE,DGE,ENSG00000089041,not_gwas +female,ENSG00000170160,CCDC144A,ENSG00000170160,Nac_female,Nac,female,DGE,DGE,ENSG00000170160,not_gwas +female,ENSG00000197171,LINC03003,ENSG00000197171,Nac_female,Nac,female,DGE,DGE,ENSG00000197171,not_gwas +female,ENSG00000188933,USP32P1,ENSG00000188933,Nac_female,Nac,female,DGE,DGE,ENSG00000188933,not_gwas +female,ENSG00000077327,SPAG6,ENSG00000077327,Nac_female,Nac,female,DGE,DGE,ENSG00000077327,not_gwas +female,ENSG00000118492,ADGB,ENSG00000118492,Nac_female,Nac,female,DGE,DGE,ENSG00000118492,not_gwas +female,ENSG00000112761,CCN6,ENSG00000112761,Nac_female,Nac,female,DGE,DGE,ENSG00000112761,not_gwas +female,ENSG00000166387,PPFIBP2,ENSG00000166387,Nac_female,Nac,female,DGE,DGE,ENSG00000166387,not_gwas +female,ENSG00000155287,SLC25A28,ENSG00000155287,Nac_female,Nac,female,DGE,DGE,ENSG00000155287,not_gwas +female,ENSG00000183458,PKD1P3,ENSG00000183458,Nac_female,Nac,female,DGE,DGE,ENSG00000183458,not_gwas +female,ENSG00000197177,ADGRA1,ENSG00000197177,Nac_female,Nac,female,DGE,DGE:DTE,ENSG00000197177,not_gwas +female,ENSG00000197177,ADGRA1,ENSG00000197177,Nac_female,Nac,female,DTE,DGE:DTE,ENSG00000197177,not_gwas +female,ENSG00000131002,TXLNGY,ENSG00000131002,Nac_female,Nac,female,DGE,DGE,ENSG00000131002,not_gwas +female,ENSG00000169258,GPRIN1,ENSG00000169258,Nac_female,Nac,female,DGE,DGE,ENSG00000169258,not_gwas +female,ENSG00000100625,SIX4,ENSG00000100625,Nac_female,Nac,female,DGE,DGE,ENSG00000100625,not_gwas +female,ENSG00000114784,EIF1B,ENSG00000114784,Nac_female,Nac,female,DGE,DGE,ENSG00000114784,not_gwas +female,ENSG00000162643,DNAI3,ENSG00000162643,Nac_female,Nac,female,DGE,DGE,ENSG00000162643,not_gwas +female,ENSG00000241343,RPL36A,ENSG00000241343,OFC_female,OFC,female,DGE,DGE,ENSG00000241343,not_gwas +female,ENSG00000122566,HNRNPA2B1,ENSG00000122566,OFC_female,OFC,female,DGE,DGE,ENSG00000122566,not_gwas +female,ENSG00000089335,ZNF302,ENSG00000089335,OFC_female,OFC,female,DGE,DGE,ENSG00000089335,not_gwas +female,ENSG00000147145,LPAR4,ENSG00000147145,OFC_female,OFC,female,DGE,DGE,ENSG00000147145,not_gwas +female,ENSG00000147145,LPAR4,ENSG00000147145,Cg25_female,Cg25,female,DGE,DGE,ENSG00000147145,not_gwas +female,ENSG00000244687,UBE2V1,ENSG00000244687,OFC_female,OFC,female,DGE,DGE,ENSG00000244687,not_gwas +female,ENSG00000198938,MT-CO3,ENSG00000198938,OFC_female,OFC,female,DGE,DGE,ENSG00000198938,not_gwas +female,ENSG00000184208,C22orf46,ENSG00000184208,OFC_female,OFC,female,DGE,DGE,ENSG00000184208,not_gwas +female,ENSG00000196235,SUPT5H,ENSG00000196235,OFC_female,OFC,female,DGE,DGE,ENSG00000196235,not_gwas +female,ENSG00000112357,PEX7,ENSG00000112357,OFC_female,OFC,female,DGE,DGE:DTE,ENSG00000112357,not_gwas +female,ENSG00000112357,PEX7,ENSG00000112357,OFC_female,OFC,female,DTE,DGE:DTE,ENSG00000112357,not_gwas +female,ENSG00000180953,ST20,ENSG00000180953,OFC_female,OFC,female,DGE,DGE,ENSG00000180953,not_gwas +female,ENSG00000135486,HNRNPA1,ENSG00000135486,OFC_female,OFC,female,DGE,DGE:DTE,ENSG00000135486,not_gwas +female,ENSG00000135486,HNRNPA1,ENSG00000135486,OFC_female,OFC,female,DTE,DGE:DTE,ENSG00000135486,not_gwas +female,ENSG00000101972,STAG2,ENSG00000101972,OFC_female,OFC,female,DGE,DGE:DTE,ENSG00000101972,not_gwas +female,ENSG00000101972,STAG2,ENSG00000101972,Cg25_female,Cg25,female,DGE,DGE:DTE,ENSG00000101972,not_gwas +female,ENSG00000101972,STAG2,ENSG00000101972,OFC_female,OFC,female,DTE,DGE:DTE,ENSG00000101972,not_gwas +female,ENSG00000155506,LARP1,ENSG00000155506,OFC_female,OFC,female,DGE,DGE,ENSG00000155506,not_gwas +female,ENSG00000096746,HNRNPH3,ENSG00000096746,OFC_female,OFC,female,DGE,DGE,ENSG00000096746,not_gwas +female,ENSG00000182247,UBE2E2,ENSG00000182247,OFC_female,OFC,female,DGE,DGE,ENSG00000182247,not_gwas +female,ENSG00000162755,KLHDC9,ENSG00000162755,OFC_female,OFC,female,DGE,DGE,ENSG00000162755,not_gwas +female,ENSG00000105372,RPS19,ENSG00000105372,OFC_female,OFC,female,DGE,DGE,ENSG00000105372,not_gwas +female,ENSG00000189089,RIMKLBP1,ENSG00000189089,OFC_female,OFC,female,DGE,DGE,ENSG00000189089,not_gwas +female,ENSG00000099785,MARCHF2,ENSG00000099785,OFC_female,OFC,female,DGE,DGE,ENSG00000099785,not_gwas +female,ENSG00000125386,FAM193A,ENSG00000125386,OFC_female,OFC,female,DGE,DGE,ENSG00000125386,not_gwas +female,ENSG00000181038,METTL23,ENSG00000181038,OFC_female,OFC,female,DGE,DGE,ENSG00000181038,not_gwas +female,ENSG00000101361,NOP56,ENSG00000101361,OFC_female,OFC,female,DGE,DGE,ENSG00000101361,not_gwas +female,ENSG00000236523,NPM1P40,ENSG00000236523,OFC_female,OFC,female,DGE,DGE,ENSG00000236523,not_gwas +female,ENSG00000236523,NPM1P40,ENSG00000236523,Cg25_female,Cg25,female,DGE,DGE,ENSG00000236523,not_gwas +female,ENSG00000130816,DNMT1,ENSG00000130816,OFC_female,OFC,female,DGE,DGE,ENSG00000130816,not_gwas +female,ENSG00000179085,DPM3,ENSG00000179085,OFC_female,OFC,female,DGE,DGE,ENSG00000179085,not_gwas +female,ENSG00000166444,DENND2B,ENSG00000166444,OFC_female,OFC,female,DGE,DGE,ENSG00000166444,not_gwas +female,ENSG00000198918,RPL39,ENSG00000198918,OFC_female,OFC,female,DGE,DGE:DTE,ENSG00000198918,not_gwas +female,ENSG00000198918,RPL39,ENSG00000198918,OFC_female,OFC,female,DTE,DGE:DTE,ENSG00000198918,not_gwas +female,ENSG00000165215,CLDN3,ENSG00000165215,OFC_female,OFC,female,DGE,DGE,ENSG00000165215,not_gwas +female,ENSG00000166974,MAPRE2,ENSG00000166974,OFC_female,OFC,female,DGE,DGE,ENSG00000166974,not_gwas +female,ENSG00000184924,PTRHD1,ENSG00000184924,OFC_female,OFC,female,DGE,DGE:DTU,ENSG00000184924,not_gwas +female,ENSG00000184924,PTRHD1,ENSG00000184924,OFC_female,OFC,female,DTU,DGE:DTU,ENSG00000184924,not_gwas +female,ENSG00000186665,C17orf58,ENSG00000186665,OFC_female,OFC,female,DGE,DGE,ENSG00000186665,not_gwas +female,ENSG00000111752,PHC1,ENSG00000111752,OFC_female,OFC,female,DGE,DGE,ENSG00000111752,not_gwas +female,ENSG00000124614,RPS10,ENSG00000124614,OFC_female,OFC,female,DGE,DGE,ENSG00000124614,not_gwas +female,ENSG00000275023,MLLT6,ENSG00000275023,OFC_female,OFC,female,DGE,DGE,ENSG00000275023,not_gwas +female,ENSG00000213235,EEF1A1P16,ENSG00000213235,OFC_female,OFC,female,DGE,DGE,ENSG00000213235,not_gwas +female,ENSG00000249768,HSPE1P10,ENSG00000249768,OFC_female,OFC,female,DGE,DGE,ENSG00000249768,not_gwas +female,ENSG00000167257,RNF214,ENSG00000167257,OFC_female,OFC,female,DGE,DGE,ENSG00000167257,not_gwas +female,ENSG00000168056,LTBP3,ENSG00000168056,OFC_female,OFC,female,DGE,DGE,ENSG00000168056,gwas +female,ENSG00000254870,ATP6V1G2-DDX39B,ENSG00000254870,OFC_female,OFC,female,DGE,DGE,ENSG00000254870,not_gwas +female,ENSG00000112182,BACH2,ENSG00000112182,OFC_female,OFC,female,DGE,DGE,ENSG00000112182,not_gwas +female,ENSG00000117410,ATP6V0B,ENSG00000117410,OFC_female,OFC,female,DGE,DGE,ENSG00000117410,not_gwas +female,ENSG00000130939,UBE4B,ENSG00000130939,OFC_female,OFC,female,DGE,DGE,ENSG00000130939,not_gwas +female,ENSG00000108349,CASC3,ENSG00000108349,OFC_female,OFC,female,DGE,DGE,ENSG00000108349,not_gwas +female,ENSG00000136536,MARCHF7,ENSG00000136536,OFC_female,OFC,female,DGE,DGE,ENSG00000136536,not_gwas +female,ENSG00000126005,MMP24OS,ENSG00000126005,OFC_female,OFC,female,DGE,DGE,ENSG00000126005,not_gwas +female,ENSG00000248527,MTATP6P1,ENSG00000248527,OFC_female,OFC,female,DGE,DGE,ENSG00000248527,not_gwas +female,ENSG00000123213,NLN,ENSG00000123213,OFC_female,OFC,female,DGE,DGE,ENSG00000123213,not_gwas +female,ENSG00000127616,SMARCA4,ENSG00000127616,OFC_female,OFC,female,DGE,DGE,ENSG00000127616,not_gwas +female,ENSG00000183978,COA3,ENSG00000183978,OFC_female,OFC,female,DGE,DGE:DTE,ENSG00000183978,not_gwas +female,ENSG00000183978,COA3,ENSG00000183978,OFC_female,OFC,female,DTE,DGE:DTE,ENSG00000183978,not_gwas +female,ENSG00000116560,SFPQ,ENSG00000116560,OFC_female,OFC,female,DGE,DGE,ENSG00000116560,not_gwas +female,ENSG00000129480,DTD2,ENSG00000129480,OFC_female,OFC,female,DGE,DGE,ENSG00000129480,not_gwas +female,ENSG00000088367,EPB41L1,ENSG00000088367,OFC_female,OFC,female,DGE,DGE,ENSG00000088367,not_gwas +female,ENSG00000117713,ARID1A,ENSG00000117713,OFC_female,OFC,female,DGE,DGE,ENSG00000117713,not_gwas +female,ENSG00000110066,KMT5B,ENSG00000110066,OFC_female,OFC,female,DGE,DGE,ENSG00000110066,not_gwas +female,ENSG00000132478,UNK,ENSG00000132478,OFC_female,OFC,female,DGE,DGE,ENSG00000132478,not_gwas +female,ENSG00000184640,SEPTIN9,ENSG00000184640,OFC_female,OFC,female,DGE,DGE,ENSG00000184640,not_gwas +female,ENSG00000213018,PABPN1P1,ENSG00000213018,OFC_female,OFC,female,DGE,DGE,ENSG00000213018,not_gwas +female,ENSG00000115053,NCL,ENSG00000115053,OFC_female,OFC,female,DGE,DGE:DTE,ENSG00000115053,not_gwas +female,ENSG00000115053,NCL,ENSG00000115053,OFC_female,OFC,female,DTE,DGE:DTE,ENSG00000115053,not_gwas +female,ENSG00000140995,DEF8,ENSG00000140995,OFC_female,OFC,female,DGE,DGE,ENSG00000140995,not_gwas +female,ENSG00000130749,ZC3H4,ENSG00000130749,OFC_female,OFC,female,DGE,DGE,ENSG00000130749,not_gwas +female,ENSG00000242221,PSG2,ENSG00000242221,OFC_female,OFC,female,DGE,DGE,ENSG00000242221,not_gwas +female,ENSG00000163382,"NAXE",ENSG00000163382,OFC_female,OFC,female,DGE,DGE,ENSG00000163382,not_gwas +female,ENSG00000188243,COMMD6,ENSG00000188243,OFC_female,OFC,female,DGE,DGE:DTE,ENSG00000188243,not_gwas +female,ENSG00000188243,COMMD6,ENSG00000188243,OFC_female,OFC,female,DTE,DGE:DTE,ENSG00000188243,not_gwas +female,ENSG00000175467,SART1,ENSG00000175467,OFC_female,OFC,female,DGE,DGE,ENSG00000175467,not_gwas +female,ENSG00000161328,LRRC56,ENSG00000161328,OFC_female,OFC,female,DGE,DGE,ENSG00000161328,not_gwas +female,ENSG00000225067,RPL23AP2,ENSG00000225067,OFC_female,OFC,female,DGE,DGE,ENSG00000225067,not_gwas +female,ENSG00000146067,FAM193B,ENSG00000146067,OFC_female,OFC,female,DGE,DGE,ENSG00000146067,not_gwas +female,ENSG00000170632,ARMC10,ENSG00000170632,OFC_female,OFC,female,DGE,DGE,ENSG00000170632,not_gwas +female,ENSG00000182809,CRIP2,ENSG00000182809,OFC_female,OFC,female,DGE,DGE,ENSG00000182809,not_gwas +female,ENSG00000164405,UQCRQ,ENSG00000164405,OFC_female,OFC,female,DGE,DGE:DTU,ENSG00000164405,not_gwas +female,ENSG00000164405,UQCRQ,ENSG00000164405,OFC_female,OFC,female,DTU,DGE:DTU,ENSG00000164405,not_gwas +female,ENSG00000166197,NOLC1,ENSG00000166197,OFC_female,OFC,female,DGE,DGE,ENSG00000166197,not_gwas +female,ENSG00000178449,COX14,ENSG00000178449,OFC_female,OFC,female,DGE,DGE,ENSG00000178449,not_gwas +female,ENSG00000204923,FBXO48,ENSG00000204923,OFC_female,OFC,female,DGE,DGE,ENSG00000204923,not_gwas +female,ENSG00000132388,UBE2G1,ENSG00000132388,OFC_female,OFC,female,DGE,DGE,ENSG00000132388,not_gwas +female,ENSG00000227694,RPL23AP74,ENSG00000227694,OFC_female,OFC,female,DGE,DGE,ENSG00000227694,not_gwas +female,ENSG00000260266,PPIAP46,ENSG00000260266,OFC_female,OFC,female,DGE,DGE,ENSG00000260266,not_gwas +female,ENSG00000111843,TMEM14C,ENSG00000111843,OFC_female,OFC,female,DGE,DGE:DTE,ENSG00000111843,not_gwas +female,ENSG00000111843,TMEM14C,ENSG00000111843,OFC_female,OFC,female,DTE,DGE:DTE,ENSG00000111843,not_gwas +female,ENSG00000169902,TPST1,ENSG00000169902,OFC_female,OFC,female,DGE,DGE,ENSG00000169902,not_gwas +female,ENSG00000142039,CCDC97,ENSG00000142039,OFC_female,OFC,female,DGE,DGE,ENSG00000142039,not_gwas +female,ENSG00000177576,C18orf32,ENSG00000177576,OFC_female,OFC,female,DGE,DGE:DTE,ENSG00000177576,not_gwas +female,ENSG00000177576,C18orf32,ENSG00000177576,OFC_female,OFC,female,DTE,DGE:DTE,ENSG00000177576,not_gwas +female,ENSG00000127540,UQCR11,ENSG00000127540,OFC_female,OFC,female,DGE,DGE,ENSG00000127540,not_gwas +female,ENSG00000177144,NUDT4B,ENSG00000177144,OFC_female,OFC,female,DGE,DGE,ENSG00000177144,not_gwas +female,ENSG00000145833,DDX46,ENSG00000145833,OFC_female,OFC,female,DGE,DGE,ENSG00000145833,not_gwas +female,ENSG00000168066,SF1,ENSG00000168066,OFC_female,OFC,female,DGE,DGE,ENSG00000168066,not_gwas +female,ENSG00000181450,ZNF678,ENSG00000181450,OFC_female,OFC,female,DGE,DGE,ENSG00000181450,not_gwas +female,ENSG00000112983,BRD8,ENSG00000112983,OFC_female,OFC,female,DGE,DGE,ENSG00000112983,not_gwas +female,ENSG00000177464,GPR4,ENSG00000177464,OFC_female,OFC,female,DGE,DGE,ENSG00000177464,not_gwas +female,ENSG00000102390,PBDC1,ENSG00000102390,OFC_female,OFC,female,DGE,DGE,ENSG00000102390,not_gwas +female,ENSG00000229415,SFTA3,ENSG00000229415,OFC_female,OFC,female,DGE,DGE:DTE,ENSG00000229415,not_gwas +female,ENSG00000229415,SFTA3,ENSG00000229415,OFC_female,OFC,female,DTE,DGE:DTE,ENSG00000229415,not_gwas +female,ENSG00000143294,PRCC,ENSG00000143294,OFC_female,OFC,female,DGE,DGE,ENSG00000143294,not_gwas +female,ENSG00000152240,HAUS1,ENSG00000152240,OFC_female,OFC,female,DGE,DGE,ENSG00000152240,not_gwas +female,ENSG00000204060,FOXO6,ENSG00000204060,OFC_female,OFC,female,DGE,DGE,ENSG00000204060,not_gwas +female,ENSG00000167632,TRAPPC9,ENSG00000167632,OFC_female,OFC,female,DGE,DGE,ENSG00000167632,not_gwas +female,ENSG00000113845,TIMMDC1,ENSG00000113845,OFC_female,OFC,female,DGE,DGE,ENSG00000113845,not_gwas +female,ENSG00000205937,RNPS1,ENSG00000205937,OFC_female,OFC,female,DGE,DGE,ENSG00000205937,not_gwas +female,ENSG00000143569,UBAP2L,ENSG00000143569,OFC_female,OFC,female,DGE,DGE,ENSG00000143569,not_gwas +female,ENSG00000102524,TNFSF13B,ENSG00000102524,OFC_female,OFC,female,DGE,DGE,ENSG00000102524,not_gwas +female,ENSG00000134419,RPS15A,ENSG00000134419,OFC_female,OFC,female,DGE,DGE,ENSG00000134419,not_gwas +female,ENSG00000204370,SDHD,ENSG00000204370,OFC_female,OFC,female,DGE,DGE,ENSG00000204370,not_gwas +female,ENSG00000063177,RPL18,ENSG00000063177,OFC_female,OFC,female,DGE,DGE,ENSG00000063177,not_gwas +female,ENSG00000132153,DHX30,ENSG00000132153,OFC_female,OFC,female,DGE,DGE,ENSG00000132153,not_gwas +female,ENSG00000147138,GPR174,ENSG00000147138,OFC_female,OFC,female,DGE,DGE,ENSG00000147138,not_gwas +female,ENSG00000146063,TRIM41,ENSG00000146063,OFC_female,OFC,female,DGE,DGE,ENSG00000146063,not_gwas +female,ENSG00000178980,SELENOW,ENSG00000178980,OFC_female,OFC,female,DGE,DGE,ENSG00000178980,not_gwas +female,ENSG00000213420,GPC2,ENSG00000213420,OFC_female,OFC,female,DGE,DGE,ENSG00000213420,not_gwas +female,ENSG00000103254,ANTKMT,ENSG00000103254,OFC_female,OFC,female,DGE,DGE,ENSG00000103254,not_gwas +female,ENSG00000053254,FOXN3,ENSG00000053254,OFC_female,OFC,female,DGE,DGE,ENSG00000053254,not_gwas +female,ENSG00000168002,POLR2G,ENSG00000168002,OFC_female,OFC,female,DGE,DGE,ENSG00000168002,not_gwas +female,ENSG00000148337,CIZ1,ENSG00000148337,OFC_female,OFC,female,DGE,DGE,ENSG00000148337,not_gwas +female,ENSG00000197472,ZNF695,ENSG00000197472,OFC_female,OFC,female,DGE,DGE,ENSG00000197472,not_gwas +female,ENSG00000142408,CACNG8,ENSG00000142408,OFC_female,OFC,female,DGE,DGE,ENSG00000142408,not_gwas +female,ENSG00000136573,BLK,ENSG00000136573,OFC_female,OFC,female,DGE,DGE,ENSG00000136573,not_gwas +female,ENSG00000205544,TMEM256,ENSG00000205544,OFC_female,OFC,female,DGE,DGE:DTE,ENSG00000205544,not_gwas +female,ENSG00000205544,TMEM256,ENSG00000205544,OFC_female,OFC,female,DTE,DGE:DTE,ENSG00000205544,not_gwas +female,ENSG00000173559,"NABP1",ENSG00000173559,OFC_female,OFC,female,DGE,DGE,ENSG00000173559,not_gwas +female,ENSG00000203618,GP1BB,ENSG00000203618,OFC_female,OFC,female,DGE,DGE,ENSG00000203618,not_gwas +female,ENSG00000188186,LAMTOR4,ENSG00000188186,OFC_female,OFC,female,DGE,DGE,ENSG00000188186,not_gwas +female,ENSG00000054523,KIF1B,ENSG00000054523,OFC_female,OFC,female,DGE,DGE,ENSG00000054523,not_gwas +female,ENSG00000089050,RBBP9,ENSG00000089050,OFC_female,OFC,female,DGE,DGE,ENSG00000089050,not_gwas +female,ENSG00000126698,DNAJC8,ENSG00000126698,OFC_female,OFC,female,DGE,DGE,ENSG00000126698,not_gwas +female,ENSG00000114455,HHLA2,ENSG00000114455,OFC_female,OFC,female,DGE,DGE,ENSG00000114455,not_gwas +female,ENSG00000181873,IBA57,ENSG00000181873,OFC_female,OFC,female,DGE,DGE,ENSG00000181873,not_gwas +female,ENSG00000135363,LMO2,ENSG00000135363,OFC_female,OFC,female,DGE,DGE,ENSG00000135363,not_gwas +female,ENSG00000197006,METTL9,ENSG00000197006,OFC_female,OFC,female,DGE,DGE,ENSG00000197006,gwas +female,ENSG00000118900,UBN1,ENSG00000118900,OFC_female,OFC,female,DGE,DGE,ENSG00000118900,not_gwas +female,ENSG00000013619,MAMLD1,ENSG00000013619,OFC_female,OFC,female,DGE,DGE,ENSG00000013619,not_gwas +female,ENSG00000180264,ADGRD2,ENSG00000180264,OFC_female,OFC,female,DGE,DGE,ENSG00000180264,not_gwas +female,ENSG00000106803,SEC61B,ENSG00000106803,OFC_female,OFC,female,DGE,DGE,ENSG00000106803,not_gwas +female,ENSG00000005844,ITGAL,ENSG00000005844,OFC_female,OFC,female,DGE,DGE,ENSG00000005844,not_gwas +female,ENSG00000081154,PCNP,ENSG00000081154,OFC_female,OFC,female,DGE,DGE,ENSG00000081154,not_gwas +female,ENSG00000112293,GPLD1,ENSG00000112293,OFC_female,OFC,female,DGE,DGE,ENSG00000112293,not_gwas +female,ENSG00000198019,FCGR1BP,ENSG00000198019,OFC_female,OFC,female,DGE,DGE,ENSG00000198019,not_gwas +female,ENSG00000164393,ADGRF2,ENSG00000164393,OFC_female,OFC,female,DGE,DGE,ENSG00000164393,not_gwas +female,ENSG00000279800,BCLAF1P2,ENSG00000279800,OFC_female,OFC,female,DGE,DGE,ENSG00000279800,not_gwas +female,ENSG00000253488,SINHCAFP3,ENSG00000253488,OFC_female,OFC,female,DGE,DGE,ENSG00000253488,not_gwas +female,ENSG00000253488,SINHCAFP3,ENSG00000253488,Cg25_female,Cg25,female,DGE,DGE,ENSG00000253488,not_gwas +female,ENSG00000224578,HNRNPA1L3,ENSG00000224578,OFC_female,OFC,female,DGE,DGE,ENSG00000224578,not_gwas +female,ENSG00000176208,ATAD5,ENSG00000176208,OFC_female,OFC,female,DGE,DGE,ENSG00000176208,not_gwas +female,ENSG00000126456,IRF3,ENSG00000126456,OFC_female,OFC,female,DGE,DGE,ENSG00000126456,not_gwas +female,ENSG00000110025,SNX15,ENSG00000110025,OFC_female,OFC,female,DGE,DGE,ENSG00000110025,not_gwas +female,ENSG00000103507,BCKDK,ENSG00000103507,OFC_female,OFC,female,DGE,DGE,ENSG00000103507,not_gwas +female,ENSG00000172469,MANEA,ENSG00000172469,OFC_female,OFC,female,DGE,DGE:DTE,ENSG00000172469,not_gwas +female,ENSG00000172469,MANEA,ENSG00000172469,OFC_female,OFC,female,DTE,DGE:DTE,ENSG00000172469,not_gwas +female,ENSG00000141252,VPS53,ENSG00000141252,OFC_female,OFC,female,DGE,DGE,ENSG00000141252,not_gwas +female,ENSG00000144566,RAB5A,ENSG00000144566,OFC_female,OFC,female,DGE,DGE,ENSG00000144566,not_gwas +female,ENSG00000203950,RTL8A,ENSG00000203950,OFC_female,OFC,female,DGE,DGE,ENSG00000203950,not_gwas +female,ENSG00000124422,USP22,ENSG00000124422,OFC_female,OFC,female,DGE,DGE,ENSG00000124422,not_gwas +female,ENSG00000090266,NDUFB2,ENSG00000090266,OFC_female,OFC,female,DGE,DGE,ENSG00000090266,not_gwas +female,ENSG00000143774,GUK1,ENSG00000143774,OFC_female,OFC,female,DGE,DGE,ENSG00000143774,not_gwas +female,ENSG00000169221,TBC1D10B,ENSG00000169221,OFC_female,OFC,female,DGE,DGE,ENSG00000169221,not_gwas +female,ENSG00000143570,SLC39A1,ENSG00000143570,OFC_female,OFC,female,DGE,DGE,ENSG00000143570,not_gwas +female,ENSG00000167085,PHB1,ENSG00000167085,OFC_female,OFC,female,DGE,DGE,ENSG00000167085,not_gwas +female,ENSG00000170144,HNRNPA3,ENSG00000170144,OFC_female,OFC,female,DGE,DGE:DTE,ENSG00000170144,not_gwas +female,ENSG00000170144,HNRNPA3,ENSG00000170144,aINS_female,aINS,female,DTE,DGE:DTE,ENSG00000170144,not_gwas +female,ENSG00000214253,FIS1,ENSG00000214253,OFC_female,OFC,female,DGE,DGE,ENSG00000214253,not_gwas +female,ENSG00000136715,SAP130,ENSG00000136715,OFC_female,OFC,female,DGE,DGE,ENSG00000136715,not_gwas +female,ENSG00000204568,MRPS18B,ENSG00000204568,OFC_female,OFC,female,DGE,DGE,ENSG00000204568,not_gwas +female,ENSG00000134453,RBM17,ENSG00000134453,OFC_female,OFC,female,DGE,DGE,ENSG00000134453,not_gwas +female,ENSG00000183718,TRIM52,ENSG00000183718,OFC_female,OFC,female,DGE,DGE,ENSG00000183718,not_gwas +female,ENSG00000248592,STIMATE-MUSTN1,ENSG00000248592,OFC_female,OFC,female,DGE,DGE,ENSG00000248592,not_gwas +female,ENSG00000163041,H3-3A,ENSG00000163041,OFC_female,OFC,female,DGE,DGE,ENSG00000163041,not_gwas +female,ENSG00000156795,NTAQ1,ENSG00000156795,OFC_female,OFC,female,DGE,DGE,ENSG00000156795,not_gwas +female,ENSG00000183161,FANCF,ENSG00000183161,OFC_female,OFC,female,DGE,DGE,ENSG00000183161,not_gwas +female,ENSG00000276291,FRG1HP,ENSG00000276291,OFC_female,OFC,female,DGE,DGE,ENSG00000276291,not_gwas +female,ENSG00000178096,BOLA1,ENSG00000178096,OFC_female,OFC,female,DGE,DGE,ENSG00000178096,not_gwas +female,ENSG00000100804,PSMB5,ENSG00000100804,OFC_female,OFC,female,DGE,DGE,ENSG00000100804,not_gwas +female,ENSG00000079308,TNS1,ENSG00000079308,OFC_female,OFC,female,DGE,DGE,ENSG00000079308,not_gwas +female,ENSG00000173011,TADA2B,ENSG00000173011,OFC_female,OFC,female,DGE,DGE,ENSG00000173011,not_gwas +female,ENSG00000144820,ADGRG7,ENSG00000144820,OFC_female,OFC,female,DGE,DGE,ENSG00000144820,not_gwas +female,ENSG00000144820,ADGRG7,ENSG00000144820,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000144820,not_gwas +female,ENSG00000174780,SRP72,ENSG00000174780,OFC_female,OFC,female,DGE,DGE,ENSG00000174780,not_gwas +female,ENSG00000198780,FAM169A,ENSG00000198780,OFC_female,OFC,female,DGE,DGE,ENSG00000198780,not_gwas +female,ENSG00000107581,EIF3A,ENSG00000107581,OFC_female,OFC,female,DGE,DGE,ENSG00000107581,not_gwas +female,ENSG00000124469,CEACAM8,ENSG00000124469,OFC_female,OFC,female,DGE,DGE,ENSG00000124469,not_gwas +female,ENSG00000247627,MTND4P12,ENSG00000247627,OFC_female,OFC,female,DGE,DGE,ENSG00000247627,not_gwas +female,ENSG00000169964,TMEM42,ENSG00000169964,OFC_female,OFC,female,DGE,DGE,ENSG00000169964,not_gwas +female,ENSG00000170315,UBB,ENSG00000170315,OFC_female,OFC,female,DGE,DGE:DTE,ENSG00000170315,not_gwas +female,ENSG00000170315,UBB,ENSG00000170315,OFC_female,OFC,female,DTE,DGE:DTE,ENSG00000170315,not_gwas +female,ENSG00000112941,TENT4A,ENSG00000112941,OFC_female,OFC,female,DGE,DGE,ENSG00000112941,not_gwas +female,ENSG00000143222,UFC1,ENSG00000143222,OFC_female,OFC,female,DGE,DGE,ENSG00000143222,not_gwas +female,ENSG00000143379,SETDB1,ENSG00000143379,OFC_female,OFC,female,DGE,DGE,ENSG00000143379,not_gwas +female,ENSG00000137393,RNF144B,ENSG00000137393,OFC_female,OFC,female,DGE,DGE,ENSG00000137393,not_gwas +female,ENSG00000185215,TNFAIP2,ENSG00000185215,OFC_female,OFC,female,DGE,DGE,ENSG00000185215,not_gwas +female,ENSG00000077782,FGFR1,ENSG00000077782,OFC_female,OFC,female,DGE,DGE,ENSG00000077782,not_gwas +female,ENSG00000109113,RAB34,ENSG00000109113,OFC_female,OFC,female,DGE,DGE,ENSG00000109113,not_gwas +female,ENSG00000125691,RPL23,ENSG00000125691,OFC_female,OFC,female,DGE,DGE,ENSG00000125691,not_gwas +female,ENSG00000067704,IARS2,ENSG00000067704,OFC_female,OFC,female,DGE,DGE,ENSG00000067704,not_gwas +female,ENSG00000055070,SZRD1,ENSG00000055070,OFC_female,OFC,female,DGE,DGE,ENSG00000055070,not_gwas +female,ENSG00000198744,MTCO3P12,ENSG00000198744,OFC_female,OFC,female,DGE,DGE,ENSG00000198744,not_gwas +female,ENSG00000112706,IMPG1,ENSG00000112706,OFC_female,OFC,female,DGE,DGE,ENSG00000112706,not_gwas +female,ENSG00000183346,CABCOCO1,ENSG00000183346,OFC_female,OFC,female,DGE,DGE,ENSG00000183346,not_gwas +female,ENSG00000127184,COX7C,ENSG00000127184,OFC_female,OFC,female,DGE,DGE,ENSG00000127184,not_gwas +female,ENSG00000169740,ZNF32,ENSG00000169740,OFC_female,OFC,female,DGE,DGE,ENSG00000169740,not_gwas +female,ENSG00000147403,RPL10,ENSG00000147403,OFC_female,OFC,female,DGE,DGE,ENSG00000147403,not_gwas +female,ENSG00000136152,COG3,ENSG00000136152,OFC_female,OFC,female,DGE,DGE,ENSG00000136152,not_gwas +female,ENSG00000132792,CTNNBL1,ENSG00000132792,OFC_female,OFC,female,DGE,DGE,ENSG00000132792,not_gwas +female,ENSG00000152926,ZNF117,ENSG00000152926,OFC_female,OFC,female,DGE,DGE,ENSG00000152926,not_gwas +female,ENSG00000112992,NNT,ENSG00000112992,OFC_female,OFC,female,DGE,DGE,ENSG00000112992,not_gwas +female,ENSG00000168060,"NAALADL1",ENSG00000168060,OFC_female,OFC,female,DGE,DGE,ENSG00000168060,not_gwas +female,ENSG00000106244,PDAP1,ENSG00000106244,OFC_female,OFC,female,DGE,DGE,ENSG00000106244,not_gwas +female,ENSG00000241890,RPL13P4,ENSG00000241890,OFC_female,OFC,female,DGE,DGE,ENSG00000241890,not_gwas +female,ENSG00000111203,ITFG2,ENSG00000111203,OFC_female,OFC,female,DGE,DGE,ENSG00000111203,not_gwas +female,ENSG00000070444,MNT,ENSG00000070444,OFC_female,OFC,female,DGE,DGE,ENSG00000070444,not_gwas +female,ENSG00000123739,PLA2G12A,ENSG00000123739,OFC_female,OFC,female,DGE,DGE,ENSG00000123739,not_gwas +female,ENSG00000186106,ANKRD46,ENSG00000186106,OFC_female,OFC,female,DGE,DGE,ENSG00000186106,not_gwas +female,ENSG00000141298,SSH2,ENSG00000141298,OFC_female,OFC,female,DGE,DGE,ENSG00000141298,not_gwas +female,ENSG00000173041,ZNF680,ENSG00000173041,OFC_female,OFC,female,DGE,DGE,ENSG00000173041,not_gwas +female,ENSG00000213920,MDP1,ENSG00000213920,OFC_female,OFC,female,DGE,DGE,ENSG00000213920,not_gwas +female,ENSG00000233163,RPS12P17,ENSG00000233163,OFC_female,OFC,female,DGE,DGE,ENSG00000233163,not_gwas +female,ENSG00000104964,TLE5,ENSG00000104964,OFC_female,OFC,female,DGE,DGE,ENSG00000104964,not_gwas +female,ENSG00000177628,GBA1,ENSG00000177628,OFC_female,OFC,female,DGE,DGE:DTE,ENSG00000177628,not_gwas +female,ENSG00000177628,GBA1,ENSG00000177628,OFC_female,OFC,female,DTE,DGE:DTE,ENSG00000177628,not_gwas +female,ENSG00000171863,RPS7,ENSG00000171863,OFC_female,OFC,female,DGE,DGE,ENSG00000171863,not_gwas +female,ENSG00000241859,ANOS2P,ENSG00000241859,OFC_female,OFC,female,DGE,DGE,ENSG00000241859,not_gwas +female,ENSG00000124787,RPP40,ENSG00000124787,OFC_female,OFC,female,DGE,DGE,ENSG00000124787,not_gwas +female,ENSG00000111481,COPZ1,ENSG00000111481,OFC_female,OFC,female,DGE,DGE:DTE,ENSG00000111481,not_gwas +female,ENSG00000111481,COPZ1,ENSG00000111481,OFC_female,OFC,female,DTE,DGE:DTE,ENSG00000111481,not_gwas +female,ENSG00000049245,VAMP3,ENSG00000049245,OFC_female,OFC,female,DGE,DGE,ENSG00000049245,not_gwas +female,ENSG00000089737,DDX24,ENSG00000089737,OFC_female,OFC,female,DGE,DGE,ENSG00000089737,not_gwas +female,ENSG00000261740,BOLA2-SMG1P6,ENSG00000261740,OFC_female,OFC,female,DGE,DGE:DTU,ENSG00000261740,not_gwas +female,ENSG00000261740,BOLA2-SMG1P6,ENSG00000261740,OFC_female,OFC,female,DTU,DGE:DTU,ENSG00000261740,not_gwas +female,ENSG00000205765,RIMOC1,ENSG00000205765,OFC_female,OFC,female,DGE,DGE,ENSG00000205765,not_gwas +female,ENSG00000189337,KAZN,ENSG00000189337,OFC_female,OFC,female,DGE,DGE,ENSG00000189337,not_gwas +female,ENSG00000099783,HNRNPM,ENSG00000099783,OFC_female,OFC,female,DGE,DGE,ENSG00000099783,not_gwas +female,ENSG00000135709,KIAA0513,ENSG00000135709,OFC_female,OFC,female,DGE,DGE,ENSG00000135709,not_gwas +female,ENSG00000196832,OR11G2,ENSG00000196832,OFC_female,OFC,female,DGE,DGE,ENSG00000196832,not_gwas +female,ENSG00000115317,HTRA2,ENSG00000115317,OFC_female,OFC,female,DGE,DGE,ENSG00000115317,not_gwas +female,ENSG00000237350,CDC42P6,ENSG00000237350,OFC_female,OFC,female,DGE,DGE,ENSG00000237350,not_gwas +female,ENSG00000111361,EIF2B1,ENSG00000111361,OFC_female,OFC,female,DGE,DGE,ENSG00000111361,not_gwas +female,ENSG00000070814,TCOF1,ENSG00000070814,OFC_female,OFC,female,DGE,DGE,ENSG00000070814,not_gwas +female,ENSG00000061794,MRPS35,ENSG00000061794,OFC_female,OFC,female,DGE,DGE,ENSG00000061794,not_gwas +female,ENSG00000142453,CARM1,ENSG00000142453,OFC_female,OFC,female,DGE,DGE,ENSG00000142453,not_gwas +female,ENSG00000162613,FUBP1,ENSG00000162613,OFC_female,OFC,female,DGE,DGE,ENSG00000162613,not_gwas +female,ENSG00000183742,MACC1,ENSG00000183742,OFC_female,OFC,female,DGE,DGE,ENSG00000183742,not_gwas +female,ENSG00000164967,RPP25L,ENSG00000164967,OFC_female,OFC,female,DGE,DGE,ENSG00000164967,not_gwas +female,ENSG00000141905,NFIC,ENSG00000141905,OFC_female,OFC,female,DGE,DGE,ENSG00000141905,not_gwas +female,ENSG00000106733,NMRK1,ENSG00000106733,OFC_female,OFC,female,DGE,DGE,ENSG00000106733,not_gwas +female,ENSG00000127922,SEM1,ENSG00000127922,OFC_female,OFC,female,DGE,DGE,ENSG00000127922,not_gwas +female,ENSG00000119559,C19orf25,ENSG00000119559,OFC_female,OFC,female,DGE,DGE,ENSG00000119559,not_gwas +female,ENSG00000178597,PSAPL1,ENSG00000178597,OFC_female,OFC,female,DGE,DGE,ENSG00000178597,not_gwas +female,ENSG00000278505,C17orf78,ENSG00000278505,OFC_female,OFC,female,DGE,DGE,ENSG00000278505,not_gwas +female,ENSG00000110665,C11orf21,ENSG00000110665,OFC_female,OFC,female,DGE,DGE,ENSG00000110665,not_gwas +female,ENSG00000135778,NTPCR,ENSG00000135778,OFC_female,OFC,female,DGE,DGE,ENSG00000135778,not_gwas +female,ENSG00000188783,PRELP,ENSG00000188783,OFC_female,OFC,female,DGE,DGE,ENSG00000188783,not_gwas +female,ENSG00000164587,RPS14,ENSG00000164587,OFC_female,OFC,female,DGE,DGE,ENSG00000164587,not_gwas +female,ENSG00000164331,ANKRA2,ENSG00000164331,OFC_female,OFC,female,DGE,DGE,ENSG00000164331,not_gwas +female,ENSG00000123349,PFDN5,ENSG00000123349,OFC_female,OFC,female,DGE,DGE,ENSG00000123349,not_gwas +female,ENSG00000011638,LDAF1,ENSG00000011638,OFC_female,OFC,female,DGE,DGE,ENSG00000011638,not_gwas +female,ENSG00000037042,TUBG2,ENSG00000037042,OFC_female,OFC,female,DGE,DGE,ENSG00000037042,not_gwas +female,ENSG00000170296,GABARAP,ENSG00000170296,OFC_female,OFC,female,DGE,DGE,ENSG00000170296,not_gwas +female,ENSG00000225366,TDGF1P3,ENSG00000225366,OFC_female,OFC,female,DGE,DGE,ENSG00000225366,not_gwas +female,ENSG00000135211,TMEM60,ENSG00000135211,OFC_female,OFC,female,DGE,DGE,ENSG00000135211,not_gwas +female,ENSG00000235655,H3P6,ENSG00000235655,OFC_female,OFC,female,DGE,DGE,ENSG00000235655,not_gwas +female,ENSG00000077721,UBE2A,ENSG00000077721,OFC_female,OFC,female,DGE,DGE,ENSG00000077721,not_gwas +female,ENSG00000144063,MALL,ENSG00000144063,OFC_female,OFC,female,DGE,DGE,ENSG00000144063,not_gwas +female,ENSG00000186468,RPS23,ENSG00000186468,OFC_female,OFC,female,DGE,DGE,ENSG00000186468,not_gwas +female,ENSG00000232938,RPL23AP87,ENSG00000232938,OFC_female,OFC,female,DGE,DGE,ENSG00000232938,not_gwas +female,ENSG00000204576,PRR3,ENSG00000204576,OFC_female,OFC,female,DGE,DGE,ENSG00000204576,not_gwas +female,ENSG00000084731,KIF3C,ENSG00000084731,OFC_female,OFC,female,DGE,DGE,ENSG00000084731,not_gwas +female,ENSG00000129968,ABHD17A,ENSG00000129968,OFC_female,OFC,female,DGE,DGE,ENSG00000129968,not_gwas +female,ENSG00000181524,RPL24P4,ENSG00000181524,OFC_female,OFC,female,DGE,DGE,ENSG00000181524,not_gwas +female,ENSG00000181126,HLA-V,ENSG00000181126,OFC_female,OFC,female,DGE,DGE,ENSG00000181126,not_gwas +female,ENSG00000243147,MRPL33,ENSG00000243147,OFC_female,OFC,female,DGE,DGE,ENSG00000243147,not_gwas +female,ENSG00000183814,LIN9,ENSG00000183814,OFC_female,OFC,female,DGE,DGE,ENSG00000183814,not_gwas +female,ENSG00000151779,NBAS,ENSG00000151779,OFC_female,OFC,female,DGE,DGE,ENSG00000151779,gwas +female,ENSG00000100316,RPL3,ENSG00000100316,OFC_female,OFC,female,DGE,DGE,ENSG00000100316,not_gwas +female,ENSG00000188766,SPRED3,ENSG00000188766,OFC_female,OFC,female,DGE,DGE,ENSG00000188766,not_gwas +female,ENSG00000066827,ZFAT,ENSG00000066827,OFC_female,OFC,female,DGE,DGE,ENSG00000066827,not_gwas +female,ENSG00000008056,SYN1,ENSG00000008056,OFC_female,OFC,female,DGE,DGE,ENSG00000008056,not_gwas +female,ENSG00000165672,PRDX3,ENSG00000165672,OFC_female,OFC,female,DGE,DGE,ENSG00000165672,not_gwas +female,ENSG00000233503,HNRNPLP1,ENSG00000233503,OFC_female,OFC,female,DGE,DGE,ENSG00000233503,not_gwas +female,ENSG00000104808,DHDH,ENSG00000104808,OFC_female,OFC,female,DGE,DGE,ENSG00000104808,not_gwas +female,ENSG00000175595,ERCC4,ENSG00000175595,OFC_female,OFC,female,DGE,DGE,ENSG00000175595,not_gwas +female,ENSG00000170516,COX7B2,ENSG00000170516,OFC_female,OFC,female,DGE,DGE,ENSG00000170516,not_gwas +female,ENSG00000143742,SRP9,ENSG00000143742,OFC_female,OFC,female,DGE,DGE:DTE,ENSG00000143742,not_gwas +female,ENSG00000143742,SRP9,ENSG00000143742,OFC_female,OFC,female,DTE,DGE:DTE,ENSG00000143742,not_gwas +female,ENSG00000111653,ING4,ENSG00000111653,OFC_female,OFC,female,DGE,DGE,ENSG00000111653,not_gwas +female,ENSG00000111639,MRPL51,ENSG00000111639,OFC_female,OFC,female,DGE,DGE,ENSG00000111639,not_gwas +female,ENSG00000163214,DHX57,ENSG00000163214,OFC_female,OFC,female,DGE,DGE,ENSG00000163214,not_gwas +female,ENSG00000092978,GPATCH2,ENSG00000092978,OFC_female,OFC,female,DGE,DGE,ENSG00000092978,not_gwas +female,ENSG00000122565,CBX3,ENSG00000122565,OFC_female,OFC,female,DGE,DGE,ENSG00000122565,not_gwas +female,ENSG00000160633,SAFB,ENSG00000160633,OFC_female,OFC,female,DGE,DGE,ENSG00000160633,not_gwas +female,ENSG00000166797,CIAO2A,ENSG00000166797,OFC_female,OFC,female,DGE,DGE,ENSG00000166797,not_gwas +female,ENSG00000128274,A4GALT,ENSG00000128274,OFC_female,OFC,female,DGE,DGE,ENSG00000128274,not_gwas +female,ENSG00000203761,MSTO2P,ENSG00000203761,OFC_female,OFC,female,DGE,DGE,ENSG00000203761,not_gwas +female,ENSG00000143947,RPS27A,ENSG00000143947,OFC_female,OFC,female,DGE,DGE,ENSG00000143947,not_gwas +female,ENSG00000089280,FUS,ENSG00000089280,OFC_female,OFC,female,DGE,DGE,ENSG00000089280,not_gwas +female,ENSG00000106153,CHCHD2,ENSG00000106153,OFC_female,OFC,female,DGE,DGE,ENSG00000106153,not_gwas +female,ENSG00000081041,CXCL2,ENSG00000081041,OFC_female,OFC,female,DGE,DGE,ENSG00000081041,not_gwas +female,ENSG00000117280,RAB29,ENSG00000117280,OFC_female,OFC,female,DGE,DGE,ENSG00000117280,not_gwas +female,ENSG00000164096,C4orf3,ENSG00000164096,OFC_female,OFC,female,DGE,DGE,ENSG00000164096,not_gwas +female,ENSG00000134698,AGO4,ENSG00000134698,OFC_female,OFC,female,DGE,DGE,ENSG00000134698,not_gwas +female,ENSG00000145354,CISD2,ENSG00000145354,OFC_female,OFC,female,DGE,DGE,ENSG00000145354,not_gwas +female,ENSG00000145736,GTF2H2,ENSG00000145736,OFC_female,OFC,female,DGE,DGE,ENSG00000145736,not_gwas +female,ENSG00000130811,EIF3G,ENSG00000130811,OFC_female,OFC,female,DGE,DGE,ENSG00000130811,not_gwas +female,ENSG00000236474,GCNT1P1,ENSG00000236474,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000236474,not_gwas +female,ENSG00000254512,PHB1P2,ENSG00000254512,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000254512,not_gwas +female,ENSG00000183638,RP1L1,ENSG00000183638,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000183638,not_gwas +female,ENSG00000166435,XRRA1,ENSG00000166435,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000166435,not_gwas +female,ENSG00000259339,TGIF1P1,ENSG00000259339,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000259339,not_gwas +female,ENSG00000198064,NPIPB13,ENSG00000198064,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000198064,not_gwas +female,ENSG00000259318,HMGN1P1,ENSG00000259318,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000259318,not_gwas +female,ENSG00000212643,ZRSR2P1,ENSG00000212643,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000212643,not_gwas +female,ENSG00000104835,SARS2,ENSG00000104835,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000104835,not_gwas +female,ENSG00000114374,USP9Y,ENSG00000114374,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000114374,not_gwas +female,ENSG00000117500,TMED5,ENSG00000117500,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000117500,not_gwas +female,ENSG00000174501,ANKRD36C,ENSG00000174501,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000174501,not_gwas +female,ENSG00000215165,TCEA1P3,ENSG00000215165,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000215165,not_gwas +female,ENSG00000059588,TARBP1,ENSG00000059588,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000059588,not_gwas +female,ENSG00000234227,RPL7L1P1,ENSG00000234227,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000234227,not_gwas +female,ENSG00000204866,IGFL2,ENSG00000204866,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000204866,not_gwas +female,ENSG00000188624,IGFL3,ENSG00000188624,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000188624,not_gwas +female,ENSG00000088320,REM1,ENSG00000088320,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000088320,not_gwas +female,ENSG00000206538,VGLL3,ENSG00000206538,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000206538,not_gwas +female,ENSG00000235674,LDHAP2,ENSG00000235674,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000235674,not_gwas +female,ENSG00000258890,CEP95,ENSG00000258890,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000258890,not_gwas +female,ENSG00000177984,LCN15,ENSG00000177984,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000177984,not_gwas +female,ENSG00000241697,TMEFF1,ENSG00000241697,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000241697,not_gwas +female,ENSG00000237406,NDUFA9P1,ENSG00000237406,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000237406,not_gwas +female,ENSG00000105404,RABAC1,ENSG00000105404,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000105404,not_gwas +female,ENSG00000167202,TBC1D2B,ENSG00000167202,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000167202,not_gwas +female,ENSG00000218186,KRT8P43,ENSG00000218186,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000218186,not_gwas +female,ENSG00000168096,ANKS3,ENSG00000168096,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000168096,not_gwas +female,ENSG00000109084,TMEM97,ENSG00000109084,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000109084,not_gwas +female,ENSG00000143344,RGL1,ENSG00000143344,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000143344,not_gwas +female,ENSG00000035403,VCL,ENSG00000035403,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000035403,not_gwas +female,ENSG00000162241,SLC25A45,ENSG00000162241,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000162241,not_gwas +female,ENSG00000158683,PKD1L1,ENSG00000158683,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000158683,not_gwas +female,ENSG00000269343,ZNF587B,ENSG00000269343,dlPFC_female,dlPFC,female,DGE,DGE:DTE,ENSG00000269343,not_gwas +female,ENSG00000269343,ZNF587B,ENSG00000269343,dlPFC_female,dlPFC,female,DTE,DGE:DTE,ENSG00000269343,not_gwas +female,ENSG00000180708,OR10K2,ENSG00000180708,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000180708,not_gwas +female,ENSG00000214244,SETP21,ENSG00000214244,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000214244,not_gwas +female,ENSG00000187391,MAGI2,ENSG00000187391,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000187391,not_gwas +female,ENSG00000273762,VN1R76P,ENSG00000273762,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000273762,not_gwas +female,ENSG00000258932,MIR3171HG,ENSG00000258932,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000258932,not_gwas +female,ENSG00000183604,SMG1P5,ENSG00000183604,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000183604,not_gwas +female,ENSG00000138472,GUCA1C,ENSG00000138472,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000138472,not_gwas +female,ENSG00000105186,ANKRD27,ENSG00000105186,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000105186,not_gwas +female,ENSG00000160117,ANKLE1,ENSG00000160117,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000160117,not_gwas +female,ENSG00000257966,OLA1P3,ENSG00000257966,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000257966,not_gwas +female,ENSG00000161642,ZNF385A,ENSG00000161642,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000161642,not_gwas +female,ENSG00000136542,GALNT5,ENSG00000136542,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000136542,not_gwas +female,ENSG00000259378,DCAF13P3,ENSG00000259378,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000259378,not_gwas +female,ENSG00000185031,SLC2A3P2,ENSG00000185031,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000185031,not_gwas +female,ENSG00000251400,ALDH7A1P1,ENSG00000251400,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000251400,not_gwas +female,ENSG00000227331,RPL7AP22,ENSG00000227331,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000227331,not_gwas +female,ENSG00000088356,PDRG1,ENSG00000088356,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000088356,not_gwas +female,ENSG00000206159,GYG2P1,ENSG00000206159,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000206159,not_gwas +female,ENSG00000257195,HNRNPA1P50,ENSG00000257195,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000257195,not_gwas +female,ENSG00000214988,RPL7AP26,ENSG00000214988,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000214988,not_gwas +female,ENSG00000160049,DFFA,ENSG00000160049,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000160049,not_gwas +female,ENSG00000139547,RDH16,ENSG00000139547,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000139547,not_gwas +female,ENSG00000107882,SUFU,ENSG00000107882,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000107882,not_gwas +female,ENSG00000188001,TPRG1,ENSG00000188001,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000188001,not_gwas +female,ENSG00000140259,MFAP1,ENSG00000140259,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000140259,not_gwas +female,ENSG00000127589,TUBBP1,ENSG00000127589,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000127589,not_gwas +female,ENSG00000243716,NPIPB5,ENSG00000243716,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000243716,not_gwas +female,ENSG00000232230,TPM4P1,ENSG00000232230,dlPFC_female,dlPFC,female,DGE,DGE,ENSG00000232230,not_gwas +female,ENSG00000269955,FMC1-LUC7L2,ENSG00000269955,Cg25_female,Cg25,female,DGE,DGE,ENSG00000269955,not_gwas +female,ENSG00000141569,TRIM65,ENSG00000141569,Cg25_female,Cg25,female,DGE,DGE,ENSG00000141569,not_gwas +female,ENSG00000238118,SLC25A24P2,ENSG00000238118,Cg25_female,Cg25,female,DGE,DGE,ENSG00000238118,not_gwas +female,ENSG00000243746,EEF1A1P10,ENSG00000243746,Cg25_female,Cg25,female,DGE,DGE,ENSG00000243746,not_gwas +female,ENSG00000215812,ZNF847P,ENSG00000215812,Cg25_female,Cg25,female,DGE,DGE,ENSG00000215812,not_gwas +female,ENSG00000130300,PLVAP,ENSG00000130300,Cg25_female,Cg25,female,DGE,DGE:DTU,ENSG00000130300,not_gwas +female,ENSG00000130300,PLVAP,ENSG00000130300,Sub_female,Sub,female,DTU,DGE:DTU,ENSG00000130300,not_gwas +female,ENSG00000109917,ZPR1,ENSG00000109917,Cg25_female,Cg25,female,DGE,DGE,ENSG00000109917,not_gwas +female,ENSG00000242683,RPL12P21,ENSG00000242683,Cg25_female,Cg25,female,DGE,DGE,ENSG00000242683,not_gwas +female,ENSG00000163586,FABP1,ENSG00000163586,Cg25_female,Cg25,female,DGE,DGE,ENSG00000163586,not_gwas +female,ENSG00000127314,RAP1B,ENSG00000127314,aINS_female,aINS,female,DGE,DGE,ENSG00000127314,not_gwas +female,ENSG00000163872,YEATS2,ENSG00000163872,aINS_female,aINS,female,DGE,DGE,ENSG00000163872,not_gwas +female,ENSG00000258780,BMS1P15,ENSG00000258780,aINS_female,aINS,female,DGE,DGE,ENSG00000258780,not_gwas +female,ENSG00000196873,ZNG1C,ENSG00000196873,aINS_female,aINS,female,DGE,DGE,ENSG00000196873,not_gwas +female,ENSG00000249055,TBCAP3,ENSG00000249055,aINS_female,aINS,female,DGE,DGE,ENSG00000249055,not_gwas +female,ENSG00000284283,TAF11L4,ENSG00000284283,Sub_female,Sub,female,DGE,DGE,ENSG00000284283,not_gwas +female,ENSG00000243232,PCDHAC2,ENSG00000243232,Sub_female,Sub,female,DGE,DGE,ENSG00000243232,not_gwas +female,ENSG00000262583,TMEM231P1,ENSG00000262583,Sub_female,Sub,female,DGE,DGE,ENSG00000262583,not_gwas +female,ENSG00000152217,SETBP1,ENSG00000152217,Sub_female,Sub,female,DGE,DGE,ENSG00000152217,not_gwas +female,ENSG00000170956,CEACAM3,ENSG00000170956,Sub_female,Sub,female,DGE,DGE,ENSG00000170956,not_gwas +female,ENSG00000184349,EFNA5,ENSG00000184349,Sub_female,Sub,female,DGE,DGE,ENSG00000184349,not_gwas +female,ENSG00000254430,OR6M3P,ENSG00000254430,Sub_female,Sub,female,DGE,DGE,ENSG00000254430,not_gwas +female,ENSG00000268598,VN1R80P,ENSG00000268598,Sub_female,Sub,female,DGE,DGE,ENSG00000268598,not_gwas +female,ENSG00000169926,KLF13,ENSG00000169926,Sub_female,Sub,female,DGE,DGE,ENSG00000169926,not_gwas +female,ENSG00000138463,SLC49A4,ENSG00000138463,Sub_female,Sub,female,DGE,DGE,ENSG00000138463,not_gwas +female,ENSG00000120549,KIAA1217,ENSG00000120549,Sub_female,Sub,female,DGE,DGE,ENSG00000120549,not_gwas +female,ENSG00000233609,RPL10P19,ENSG00000233609,Sub_female,Sub,female,DGE,DGE,ENSG00000233609,not_gwas +female,ENSG00000161835,TAMALIN,ENSG00000161835,Sub_female,Sub,female,DGE,DGE,ENSG00000161835,not_gwas +female,ENSG00000169727,GPS1,ENSG00000169727,Sub_female,Sub,female,DGE,DGE,ENSG00000169727,not_gwas +female,ENSG00000055118,KCNH2,ENSG00000055118,Nac_female,Nac,female,DTE,DTE,ENSG00000055118,not_gwas +female,ENSG00000090238,YPEL3,ENSG00000090238,Nac_female,Nac,female,DTE,DTE,ENSG00000090238,not_gwas +female,ENSG00000198815,FOXJ3,ENSG00000198815,Nac_female,Nac,female,DTE,DTE,ENSG00000198815,not_gwas +female,ENSG00000129009,ISLR,ENSG00000129009,Nac_female,Nac,female,DTE,DTE,ENSG00000129009,not_gwas +female,ENSG00000166448,TMEM130,ENSG00000166448,Nac_female,Nac,female,DTE,DTE,ENSG00000166448,not_gwas +female,ENSG00000140488,CELF6,ENSG00000140488,Nac_female,Nac,female,DTE,DTE,ENSG00000140488,not_gwas +female,ENSG00000137343,ATAT1,ENSG00000137343,Nac_female,Nac,female,DTE,DTE,ENSG00000137343,not_gwas +female,ENSG00000137343,ATAT1,ENSG00000137343,OFC_female,OFC,female,DTE,DTE,ENSG00000137343,not_gwas +female,ENSG00000137343,ATAT1,ENSG00000137343,dlPFC_female,dlPFC,female,DTE,DTE,ENSG00000137343,not_gwas +female,ENSG00000151092,NGLY1,ENSG00000151092,Nac_female,Nac,female,DTE,DTE,ENSG00000151092,not_gwas +female,ENSG00000157103,SLC6A1,ENSG00000157103,Nac_female,Nac,female,DTE,DTE,ENSG00000157103,not_gwas +female,ENSG00000157103,SLC6A1,ENSG00000157103,OFC_female,OFC,female,DTE,DTE,ENSG00000157103,not_gwas +female,ENSG00000131323,TRAF3,ENSG00000131323,Nac_female,Nac,female,DTE,DTE,ENSG00000131323,gwas +female,ENSG00000101945,SUV39H1,ENSG00000101945,Nac_female,Nac,female,DTE,DTE,ENSG00000101945,not_gwas +female,ENSG00000118689,FOXO3,ENSG00000118689,Nac_female,Nac,female,DTE,DTE,ENSG00000118689,not_gwas +female,ENSG00000136156,ITM2B,ENSG00000136156,Nac_female,Nac,female,DTE,DTE,ENSG00000136156,not_gwas +female,ENSG00000150051,MKX,ENSG00000150051,Nac_female,Nac,female,DTE,DTE,ENSG00000150051,not_gwas +female,ENSG00000114354,TFG,ENSG00000114354,Nac_female,Nac,female,DTE,DTE,ENSG00000114354,not_gwas +female,ENSG00000138623,SEMA7A,ENSG00000138623,Nac_female,Nac,female,DTE,DTE,ENSG00000138623,not_gwas +female,ENSG00000105976,MET,ENSG00000105976,Nac_female,Nac,female,DTE,DTE,ENSG00000105976,not_gwas +female,ENSG00000157502,PWWP3B,ENSG00000157502,Nac_female,Nac,female,DTE,DTE,ENSG00000157502,not_gwas +female,ENSG00000122034,GTF3A,ENSG00000122034,Nac_female,Nac,female,DTE,DTE,ENSG00000122034,not_gwas +female,ENSG00000159840,ZYX,ENSG00000159840,Nac_female,Nac,female,DTE,DTE,ENSG00000159840,not_gwas +female,ENSG00000198133,TMEM229B,ENSG00000198133,Nac_female,Nac,female,DTE,DTE,ENSG00000198133,not_gwas +female,ENSG00000197826,CFAP299,ENSG00000197826,Nac_female,Nac,female,DTE,DTE,ENSG00000197826,not_gwas +female,ENSG00000257591,ZNF625,ENSG00000257591,Nac_female,Nac,female,DTE,DTE,ENSG00000257591,not_gwas +female,ENSG00000144191,CNGA3,ENSG00000144191,Nac_female,Nac,female,DTE,DTE,ENSG00000144191,not_gwas +female,ENSG00000107404,DVL1,ENSG00000107404,Nac_female,Nac,female,DTE,DTE,ENSG00000107404,not_gwas +female,ENSG00000166840,GLYATL1,ENSG00000166840,Nac_female,Nac,female,DTE,DTE,ENSG00000166840,not_gwas +female,ENSG00000165175,MID1IP1,ENSG00000165175,Nac_female,Nac,female,DTE,DTE,ENSG00000165175,not_gwas +female,ENSG00000170185,USP38,ENSG00000170185,Nac_female,Nac,female,DTE,DTE,ENSG00000170185,not_gwas +female,ENSG00000137166,FOXP4,ENSG00000137166,Nac_female,Nac,female,DTE,DTE,ENSG00000137166,not_gwas +female,ENSG00000188042,ARL4C,ENSG00000188042,Nac_female,Nac,female,DTE,DTE,ENSG00000188042,not_gwas +female,ENSG00000164087,POC1A,ENSG00000164087,Nac_female,Nac,female,DTE,DTE,ENSG00000164087,not_gwas +female,ENSG00000146469,VIP,ENSG00000146469,Nac_female,Nac,female,DTE,DTE,ENSG00000146469,not_gwas +female,ENSG00000133639,BTG1,ENSG00000133639,Nac_female,Nac,female,DTE,DTE,ENSG00000133639,not_gwas +female,ENSG00000163032,VSNL1,ENSG00000163032,Nac_female,Nac,female,DTE,DTE,ENSG00000163032,not_gwas +female,ENSG00000178602,OTOS,ENSG00000178602,Nac_female,Nac,female,DTE,DTE,ENSG00000178602,not_gwas +female,ENSG00000078098,FAP,ENSG00000078098,Nac_female,Nac,female,DTE,DTE,ENSG00000078098,not_gwas +female,ENSG00000110075,PPP6R3,ENSG00000110075,OFC_female,OFC,female,DTE,DTE,ENSG00000110075,not_gwas +female,ENSG00000100354,TNRC6B,ENSG00000100354,OFC_female,OFC,female,DTE,DTE,ENSG00000100354,not_gwas +female,ENSG00000127022,CANX,ENSG00000127022,OFC_female,OFC,female,DTE,DTE,ENSG00000127022,not_gwas +female,ENSG00000180008,SOCS4,ENSG00000180008,OFC_female,OFC,female,DTE,DTE,ENSG00000180008,not_gwas +female,ENSG00000100650,SRSF5,ENSG00000100650,OFC_female,OFC,female,DTE,DTE,ENSG00000100650,not_gwas +female,ENSG00000136379,ABHD17C,ENSG00000136379,OFC_female,OFC,female,DTE,DTE,ENSG00000136379,not_gwas +female,ENSG00000102245,CD40LG,ENSG00000102245,OFC_female,OFC,female,DTE,DTE,ENSG00000102245,not_gwas +female,ENSG00000104687,GSR,ENSG00000104687,OFC_female,OFC,female,DTE,DTE,ENSG00000104687,not_gwas +female,ENSG00000148303,RPL7A,ENSG00000148303,OFC_female,OFC,female,DTE,DTE,ENSG00000148303,not_gwas +female,ENSG00000231584,FAHD2CP,ENSG00000231584,OFC_female,OFC,female,DTE,DTE,ENSG00000231584,not_gwas +female,ENSG00000178385,PLEKHM3,ENSG00000178385,OFC_female,OFC,female,DTE,DTE,ENSG00000178385,not_gwas +female,ENSG00000108561,C1QBP,ENSG00000108561,OFC_female,OFC,female,DTE,DTE,ENSG00000108561,not_gwas +female,ENSG00000184182,UBE2F,ENSG00000184182,OFC_female,OFC,female,DTE,DTE,ENSG00000184182,not_gwas +female,ENSG00000277149,TYW1B,ENSG00000277149,OFC_female,OFC,female,DTE,DTE,ENSG00000277149,not_gwas +female,ENSG00000154582,ELOC,ENSG00000154582,OFC_female,OFC,female,DTE,DTE,ENSG00000154582,not_gwas +female,ENSG00000101473,ACOT8,ENSG00000101473,OFC_female,OFC,female,DTE,DTE,ENSG00000101473,not_gwas +female,ENSG00000142541,RPL13A,ENSG00000142541,OFC_female,OFC,female,DTE,DTE,ENSG00000142541,not_gwas +female,ENSG00000118096,IFT46,ENSG00000118096,OFC_female,OFC,female,DTE,DTE,ENSG00000118096,not_gwas +female,ENSG00000158296,SLC13A3,ENSG00000158296,OFC_female,OFC,female,DTE,DTE,ENSG00000158296,not_gwas +female,ENSG00000122642,FKBP9,ENSG00000122642,OFC_female,OFC,female,DTE,DTE,ENSG00000122642,not_gwas +female,ENSG00000158201,ABHD3,ENSG00000158201,OFC_female,OFC,female,DTE,DTE,ENSG00000158201,not_gwas +female,ENSG00000066027,PPP2R5A,ENSG00000066027,OFC_female,OFC,female,DTE,DTE,ENSG00000066027,not_gwas +female,ENSG00000179632,MAF1,ENSG00000179632,OFC_female,OFC,female,DTE,DTE,ENSG00000179632,not_gwas +female,ENSG00000243943,ZNF512,ENSG00000243943,OFC_female,OFC,female,DTE,DTE,ENSG00000243943,not_gwas +female,ENSG00000172456,FGGY,ENSG00000172456,OFC_female,OFC,female,DTE,DTE,ENSG00000172456,not_gwas +female,ENSG00000136270,TBRG4,ENSG00000136270,OFC_female,OFC,female,DTE,DTE,ENSG00000136270,not_gwas +female,ENSG00000136270,TBRG4,ENSG00000136270,Cg25_female,Cg25,female,DTE,DTE,ENSG00000136270,not_gwas +female,ENSG00000180776,ZDHHC20,ENSG00000180776,OFC_female,OFC,female,DTE,DTE,ENSG00000180776,not_gwas +female,ENSG00000106615,RHEB,ENSG00000106615,OFC_female,OFC,female,DTE,DTE,ENSG00000106615,not_gwas +female,ENSG00000100941,PNN,ENSG00000100941,OFC_female,OFC,female,DTE,DTE,ENSG00000100941,not_gwas +female,ENSG00000155980,KIF5A,ENSG00000155980,OFC_female,OFC,female,DTE,DTE,ENSG00000155980,not_gwas +female,ENSG00000104904,OAZ1,ENSG00000104904,OFC_female,OFC,female,DTE,DTE,ENSG00000104904,not_gwas +female,ENSG00000116288,PARK7,ENSG00000116288,OFC_female,OFC,female,DTE,DTE,ENSG00000116288,not_gwas +female,ENSG00000277053,GTF2IP1,ENSG00000277053,OFC_female,OFC,female,DTE,DTE,ENSG00000277053,not_gwas +female,ENSG00000072501,SMC1A,ENSG00000072501,OFC_female,OFC,female,DTE,DTE,ENSG00000072501,not_gwas +female,ENSG00000168291,PDHB,ENSG00000168291,OFC_female,OFC,female,DTE,DTE,ENSG00000168291,not_gwas +female,ENSG00000159147,DONSON,ENSG00000159147,OFC_female,OFC,female,DTE,DTE,ENSG00000159147,not_gwas +female,ENSG00000198855,FICD,ENSG00000198855,OFC_female,OFC,female,DTE,DTE,ENSG00000198855,not_gwas +female,ENSG00000049540,ELN,ENSG00000049540,OFC_female,OFC,female,DTE,DTE,ENSG00000049540,not_gwas +female,ENSG00000099203,TMED1,ENSG00000099203,OFC_female,OFC,female,DTE,DTE,ENSG00000099203,not_gwas +female,ENSG00000111011,RSRC2,ENSG00000111011,OFC_female,OFC,female,DTE,DTE,ENSG00000111011,not_gwas +female,ENSG00000153253,SCN3A,ENSG00000153253,OFC_female,OFC,female,DTE,DTE,ENSG00000153253,not_gwas +female,ENSG00000149972,CNTN5,ENSG00000149972,OFC_female,OFC,female,DTE,DTE,ENSG00000149972,not_gwas +female,ENSG00000117118,SDHB,ENSG00000117118,OFC_female,OFC,female,DTE,DTE,ENSG00000117118,not_gwas +female,ENSG00000109846,CRYAB,ENSG00000109846,OFC_female,OFC,female,DTE,DTE,ENSG00000109846,not_gwas +female,ENSG00000173812,EIF1,ENSG00000173812,OFC_female,OFC,female,DTE,DTE,ENSG00000173812,not_gwas +female,ENSG00000111057,KRT18,ENSG00000111057,OFC_female,OFC,female,DTE,DTE,ENSG00000111057,not_gwas +female,ENSG00000136943,CTSV,ENSG00000136943,OFC_female,OFC,female,DTE,DTE,ENSG00000136943,not_gwas +female,ENSG00000073921,PICALM,ENSG00000073921,OFC_female,OFC,female,DTE,DTE,ENSG00000073921,not_gwas +female,ENSG00000100280,AP1B1,ENSG00000100280,OFC_female,OFC,female,DTE,DTE,ENSG00000100280,not_gwas +female,ENSG00000164535,DAGLB,ENSG00000164535,OFC_female,OFC,female,DTE,DTE,ENSG00000164535,not_gwas +female,ENSG00000102316,MAGED2,ENSG00000102316,OFC_female,OFC,female,DTE,DTE,ENSG00000102316,not_gwas +female,ENSG00000182552,RWDD4,ENSG00000182552,OFC_female,OFC,female,DTE,DTE,ENSG00000182552,not_gwas +female,ENSG00000135404,CD63,ENSG00000135404,OFC_female,OFC,female,DTE,DTE,ENSG00000135404,not_gwas +female,ENSG00000139291,TMEM19,ENSG00000139291,OFC_female,OFC,female,DTE,DTE,ENSG00000139291,not_gwas +female,ENSG00000112701,SENP6,ENSG00000112701,OFC_female,OFC,female,DTE,DTE,ENSG00000112701,not_gwas +female,ENSG00000284024,MSANTD7,ENSG00000284024,OFC_female,OFC,female,DTE,DTE,ENSG00000284024,not_gwas +female,ENSG00000140990,NDUFB10,ENSG00000140990,OFC_female,OFC,female,DTE,DTE,ENSG00000140990,not_gwas +female,ENSG00000275111,ZNF2,ENSG00000275111,OFC_female,OFC,female,DTE,DTE,ENSG00000275111,not_gwas +female,ENSG00000163001,CFAP36,ENSG00000163001,OFC_female,OFC,female,DTE,DTE,ENSG00000163001,not_gwas +female,ENSG00000170142,UBE2E1,ENSG00000170142,OFC_female,OFC,female,DTE,DTE,ENSG00000170142,not_gwas +female,ENSG00000106028,SSBP1,ENSG00000106028,OFC_female,OFC,female,DTE,DTE,ENSG00000106028,not_gwas +female,ENSG00000136938,ANP32B,ENSG00000136938,OFC_female,OFC,female,DTE,DTE,ENSG00000136938,not_gwas +female,ENSG00000154114,TBCEL,ENSG00000154114,OFC_female,OFC,female,DTE,DTE,ENSG00000154114,not_gwas +female,ENSG00000225663,MCRIP1,ENSG00000225663,OFC_female,OFC,female,DTE,DTE:DTU,ENSG00000225663,not_gwas +female,ENSG00000225663,MCRIP1,ENSG00000225663,OFC_female,OFC,female,DTU,DTE:DTU,ENSG00000225663,not_gwas +female,ENSG00000239713,APOBEC3G,ENSG00000239713,OFC_female,OFC,female,DTE,DTE,ENSG00000239713,not_gwas +female,ENSG00000197894,ADH5,ENSG00000197894,OFC_female,OFC,female,DTE,DTE,ENSG00000197894,not_gwas +female,ENSG00000197043,ANXA6,ENSG00000197043,OFC_female,OFC,female,DTE,DTE,ENSG00000197043,not_gwas +female,ENSG00000149084,HSD17B12,ENSG00000149084,OFC_female,OFC,female,DTE,DTE,ENSG00000149084,not_gwas +female,ENSG00000243989,ACY1,ENSG00000243989,OFC_female,OFC,female,DTE,DTE,ENSG00000243989,not_gwas +female,ENSG00000139168,ZCRB1,ENSG00000139168,OFC_female,OFC,female,DTE,DTE,ENSG00000139168,not_gwas +female,ENSG00000269858,EGLN2,ENSG00000269858,OFC_female,OFC,female,DTE,DTE,ENSG00000269858,not_gwas +female,ENSG00000147724,FAM135B,ENSG00000147724,OFC_female,OFC,female,DTE,DTE,ENSG00000147724,not_gwas +female,ENSG00000091138,SLC26A3,ENSG00000091138,OFC_female,OFC,female,DTE,DTE,ENSG00000091138,not_gwas +female,ENSG00000127445,PIN1,ENSG00000127445,OFC_female,OFC,female,DTE,DTE,ENSG00000127445,not_gwas +female,ENSG00000148110,MFSD14B,ENSG00000148110,OFC_female,OFC,female,DTE,DTE,ENSG00000148110,not_gwas +female,ENSG00000167302,TEPSIN,ENSG00000167302,OFC_female,OFC,female,DTE,DTE,ENSG00000167302,not_gwas +female,ENSG00000161970,RPL26,ENSG00000161970,OFC_female,OFC,female,DTE,DTE,ENSG00000161970,not_gwas +female,ENSG00000180198,RCC1,ENSG00000180198,OFC_female,OFC,female,DTE,DTE,ENSG00000180198,not_gwas +female,ENSG00000128591,FLNC,ENSG00000128591,OFC_female,OFC,female,DTE,DTE,ENSG00000128591,not_gwas +female,ENSG00000180747,SMG1P3,ENSG00000180747,OFC_female,OFC,female,DTE,DTE,ENSG00000180747,not_gwas +female,ENSG00000197579,TOPORS,ENSG00000197579,OFC_female,OFC,female,DTE,DTE,ENSG00000197579,not_gwas +female,ENSG00000197265,GTF2E2,ENSG00000197265,OFC_female,OFC,female,DTE,DTE,ENSG00000197265,not_gwas +female,ENSG00000184343,SRPK3,ENSG00000184343,OFC_female,OFC,female,DTE,DTE,ENSG00000184343,not_gwas +female,ENSG00000138459,SLC35A5,ENSG00000138459,OFC_female,OFC,female,DTE,DTE,ENSG00000138459,not_gwas +female,ENSG00000168806,LCMT2,ENSG00000168806,OFC_female,OFC,female,DTE,DTE,ENSG00000168806,not_gwas +female,ENSG00000158428,CATIP,ENSG00000158428,OFC_female,OFC,female,DTE,DTE,ENSG00000158428,not_gwas +female,ENSG00000106302,HYAL4,ENSG00000106302,OFC_female,OFC,female,DTE,DTE,ENSG00000106302,not_gwas +female,ENSG00000230359,TPI1P2,ENSG00000230359,OFC_female,OFC,female,DTE,DTE,ENSG00000230359,not_gwas +female,ENSG00000118473,SGIP1,ENSG00000118473,OFC_female,OFC,female,DTE,DTE,ENSG00000118473,gwas +female,ENSG00000119547,ONECUT2,ENSG00000119547,OFC_female,OFC,female,DTE,DTE,ENSG00000119547,not_gwas +female,ENSG00000165376,CLDN2,ENSG00000165376,OFC_female,OFC,female,DTE,DTE,ENSG00000165376,not_gwas +female,ENSG00000253251,SHLD3,ENSG00000253251,OFC_female,OFC,female,DTE,DTE,ENSG00000253251,not_gwas +female,ENSG00000105248,YJU2,ENSG00000105248,OFC_female,OFC,female,DTE,DTE,ENSG00000105248,not_gwas +female,ENSG00000145506,NKD2,ENSG00000145506,OFC_female,OFC,female,DTE,DTE,ENSG00000145506,not_gwas +female,ENSG00000104154,SLC30A4,ENSG00000104154,OFC_female,OFC,female,DTE,DTE,ENSG00000104154,not_gwas +female,ENSG00000151952,TMEM132D,ENSG00000151952,OFC_female,OFC,female,DTE,DTE,ENSG00000151952,not_gwas +female,ENSG00000196839,ADA,ENSG00000196839,dlPFC_female,dlPFC,female,DTE,DTE,ENSG00000196839,not_gwas +female,ENSG00000134759,ELP2,ENSG00000134759,dlPFC_female,dlPFC,female,DTE,DTE,ENSG00000134759,not_gwas +female,ENSG00000187094,CCK,ENSG00000187094,dlPFC_female,dlPFC,female,DTE,DTE:DTU,ENSG00000187094,not_gwas +female,ENSG00000187094,CCK,ENSG00000187094,OFC_female,OFC,female,DTU,DTE:DTU,ENSG00000187094,not_gwas +female,ENSG00000161981,SNRNP25,ENSG00000161981,dlPFC_female,dlPFC,female,DTE,DTE,ENSG00000161981,not_gwas +female,ENSG00000123473,STIL,ENSG00000123473,dlPFC_female,dlPFC,female,DTE,DTE,ENSG00000123473,not_gwas +female,ENSG00000272636,DOC2B,ENSG00000272636,dlPFC_female,dlPFC,female,DTE,DTE,ENSG00000272636,not_gwas +female,ENSG00000167779,IGFBP6,ENSG00000167779,dlPFC_female,dlPFC,female,DTE,DTE,ENSG00000167779,not_gwas +female,ENSG00000073282,TP63,ENSG00000073282,dlPFC_female,dlPFC,female,DTE,DTE,ENSG00000073282,not_gwas +female,ENSG00000165685,TMEM52B,ENSG00000165685,dlPFC_female,dlPFC,female,DTE,DTE,ENSG00000165685,not_gwas +female,ENSG00000138435,CHRNA1,ENSG00000138435,dlPFC_female,dlPFC,female,DTE,DTE,ENSG00000138435,not_gwas +female,ENSG00000141744,PNMT,ENSG00000141744,dlPFC_female,dlPFC,female,DTE,DTE,ENSG00000141744,not_gwas +female,ENSG00000250486,FAM218A,ENSG00000250486,Cg25_female,Cg25,female,DTE,DTE:DTU,ENSG00000250486,not_gwas +female,ENSG00000250486,FAM218A,ENSG00000250486,Cg25_female,Cg25,female,DTU,DTE:DTU,ENSG00000250486,not_gwas +female,ENSG00000139793,MBNL2,ENSG00000139793,Cg25_female,Cg25,female,DTE,DTE,ENSG00000139793,not_gwas +female,ENSG00000165219,GAPVD1,ENSG00000165219,Cg25_female,Cg25,female,DTE,DTE,ENSG00000165219,not_gwas +female,ENSG00000106013,ANKRD7,ENSG00000106013,Cg25_female,Cg25,female,DTE,DTE,ENSG00000106013,not_gwas +female,ENSG00000100884,CPNE6,ENSG00000100884,Cg25_female,Cg25,female,DTE,DTE,ENSG00000100884,not_gwas +female,ENSG00000154864,PIEZO2,ENSG00000154864,Cg25_female,Cg25,female,DTE,DTE,ENSG00000154864,not_gwas +female,ENSG00000091656,ZFHX4,ENSG00000091656,Cg25_female,Cg25,female,DTE,DTE,ENSG00000091656,not_gwas +female,ENSG00000107679,PLEKHA1,ENSG00000107679,Cg25_female,Cg25,female,DTE,DTE,ENSG00000107679,not_gwas +female,ENSG00000107798,LIPA,ENSG00000107798,Cg25_female,Cg25,female,DTE,DTE,ENSG00000107798,not_gwas +female,ENSG00000255154,HTD2,ENSG00000255154,Cg25_female,Cg25,female,DTE,DTE,ENSG00000255154,not_gwas +female,ENSG00000099840,IZUMO4,ENSG00000099840,Cg25_female,Cg25,female,DTE,DTE:DTU,ENSG00000099840,not_gwas +female,ENSG00000099840,IZUMO4,ENSG00000099840,Cg25_female,Cg25,female,DTU,DTE:DTU,ENSG00000099840,not_gwas +female,ENSG00000198569,SLC34A3,ENSG00000198569,Cg25_female,Cg25,female,DTE,DTE,ENSG00000198569,not_gwas +female,ENSG00000180815,MAP3K15,ENSG00000180815,Cg25_female,Cg25,female,DTE,DTE,ENSG00000180815,not_gwas +female,ENSG00000180901,KCTD2,ENSG00000180901,aINS_female,aINS,female,DTE,DTE,ENSG00000180901,not_gwas +female,ENSG00000205129,C4orf47,ENSG00000205129,aINS_female,aINS,female,DTE,DTE,ENSG00000205129,not_gwas +female,ENSG00000100350,FOXRED2,ENSG00000100350,aINS_female,aINS,female,DTE,DTE,ENSG00000100350,not_gwas +female,ENSG00000165675,ENOX2,ENSG00000165675,aINS_female,aINS,female,DTE,DTE,ENSG00000165675,not_gwas +female,ENSG00000077684,JADE1,ENSG00000077684,aINS_female,aINS,female,DTE,DTE,ENSG00000077684,not_gwas +female,ENSG00000140939,NOL3,ENSG00000140939,aINS_female,aINS,female,DTE,DTE,ENSG00000140939,not_gwas +female,ENSG00000165458,INPPL1,ENSG00000165458,aINS_female,aINS,female,DTE,DTE,ENSG00000165458,not_gwas +female,ENSG00000079432,CIC,ENSG00000079432,aINS_female,aINS,female,DTE,DTE,ENSG00000079432,not_gwas +female,ENSG00000027075,PRKCH,ENSG00000027075,aINS_female,aINS,female,DTE,DTE,ENSG00000027075,not_gwas +female,ENSG00000020181,ADGRA2,ENSG00000020181,aINS_female,aINS,female,DTE,DTE,ENSG00000020181,not_gwas +female,ENSG00000184110,EIF3C,ENSG00000184110,aINS_female,aINS,female,DTE,DTE,ENSG00000184110,not_gwas +female,ENSG00000180537,RNF182,ENSG00000180537,aINS_female,aINS,female,DTE,DTE,ENSG00000180537,not_gwas +female,ENSG00000100351,GRAP2,ENSG00000100351,aINS_female,aINS,female,DTE,DTE,ENSG00000100351,not_gwas +female,ENSG00000253304,TMEM200B,ENSG00000253304,aINS_female,aINS,female,DTE,DTE,ENSG00000253304,not_gwas +female,ENSG00000139517,LNX2,ENSG00000139517,aINS_female,aINS,female,DTE,DTE,ENSG00000139517,not_gwas +female,ENSG00000286140,DERPC,ENSG00000286140,aINS_female,aINS,female,DTE,DTE,ENSG00000286140,not_gwas +female,ENSG00000224916,APOC4-APOC2,ENSG00000224916,aINS_female,aINS,female,DTE,DTE,ENSG00000224916,not_gwas +female,ENSG00000196072,BLOC1S2,ENSG00000196072,Sub_female,Sub,female,DTE,DTE,ENSG00000196072,not_gwas +female,ENSG00000130522,JUND,ENSG00000130522,Sub_female,Sub,female,DTE,DTE,ENSG00000130522,not_gwas +female,ENSG00000103569,AQP9,ENSG00000103569,Sub_female,Sub,female,DTE,DTE,ENSG00000103569,not_gwas +female,ENSG00000280670,CCDC163,ENSG00000280670,aINS_female,aINS,female,DTU,DTU,ENSG00000280670,not_gwas +female,ENSG00000104894,CD37,ENSG00000104894,aINS_female,aINS,female,DTU,DTU,ENSG00000104894,not_gwas +female,ENSG00000163793,DNAJC5G,ENSG00000163793,aINS_female,aINS,female,DTU,DTU,ENSG00000163793,not_gwas +female,ENSG00000051620,HEBP2,ENSG00000051620,aINS_female,aINS,female,DTU,DTU,ENSG00000051620,not_gwas +female,ENSG00000206053,JPT2,ENSG00000206053,aINS_female,aINS,female,DTU,DTU,ENSG00000206053,not_gwas +female,ENSG00000243678,NME2,ENSG00000243678,aINS_female,aINS,female,DTU,DTU,ENSG00000243678,not_gwas +female,ENSG00000007062,PROM1,ENSG00000007062,aINS_female,aINS,female,DTU,DTU,ENSG00000007062,not_gwas +female,ENSG00000068354,TBC1D25,ENSG00000068354,aINS_female,aINS,female,DTU,DTU,ENSG00000068354,not_gwas +female,ENSG00000167619,TMEM145,ENSG00000167619,aINS_female,aINS,female,DTU,DTU,ENSG00000167619,not_gwas +female,ENSG00000185262,UBALD2,ENSG00000185262,aINS_female,aINS,female,DTU,DTU,ENSG00000185262,not_gwas +female,ENSG00000092470,WDR76,ENSG00000092470,aINS_female,aINS,female,DTU,DTU,ENSG00000092470,not_gwas +female,ENSG00000125864,BFSP1,ENSG00000125864,Cg25_female,Cg25,female,DTU,DTU,ENSG00000125864,not_gwas +female,ENSG00000186470,BTN3A2,ENSG00000186470,Cg25_female,Cg25,female,DTU,DTU,ENSG00000186470,not_gwas +female,ENSG00000196476,C20orf96,ENSG00000196476,Cg25_female,Cg25,female,DTU,DTU,ENSG00000196476,not_gwas +female,ENSG00000196118,CCDC189,ENSG00000196118,Cg25_female,Cg25,female,DTU,DTU,ENSG00000196118,not_gwas +female,ENSG00000151725,CENPU,ENSG00000151725,Cg25_female,Cg25,female,DTU,DTU,ENSG00000151725,not_gwas +female,ENSG00000176108,CHMP6,ENSG00000176108,Cg25_female,Cg25,female,DTU,DTU,ENSG00000176108,not_gwas +female,ENSG00000172409,CLP1,ENSG00000172409,Cg25_female,Cg25,female,DTU,DTU,ENSG00000172409,not_gwas +female,ENSG00000068438,FTSJ1,ENSG00000068438,Cg25_female,Cg25,female,DTU,DTU,ENSG00000068438,not_gwas +female,ENSG00000111087,GLI1,ENSG00000111087,Cg25_female,Cg25,female,DTU,DTU,ENSG00000111087,not_gwas +female,ENSG00000180573,HIST1H2AC,ENSG00000180573,Cg25_female,Cg25,female,DTU,DTU,ENSG00000180573,not_gwas +female,ENSG00000004776,HSPB6,ENSG00000004776,Cg25_female,Cg25,female,DTU,DTU,ENSG00000004776,not_gwas +female,ENSG00000034152,MAP2K3,ENSG00000034152,Cg25_female,Cg25,female,DTU,DTU,ENSG00000034152,not_gwas +female,ENSG00000101608,MYL12A,ENSG00000101608,Cg25_female,Cg25,female,DTU,DTU,ENSG00000101608,not_gwas +female,ENSG00000173376,NDNF,ENSG00000173376,Cg25_female,Cg25,female,DTU,DTU,ENSG00000173376,not_gwas +female,ENSG00000184207,PGP,ENSG00000184207,Cg25_female,Cg25,female,DTU,DTU,ENSG00000184207,not_gwas +female,ENSG00000132207,SLX1A,ENSG00000132207,Cg25_female,Cg25,female,DTU,DTU,ENSG00000132207,not_gwas +female,ENSG00000132207,SLX1A,ENSG00000132207,OFC_female,OFC,female,DTU,DTU,ENSG00000132207,not_gwas +female,ENSG00000149809,TM7SF2,ENSG00000149809,Cg25_female,Cg25,female,DTU,DTU,ENSG00000149809,not_gwas +female,ENSG00000124191,TOX2,ENSG00000124191,Cg25_female,Cg25,female,DTU,DTU,ENSG00000124191,not_gwas +female,ENSG00000124191,TOX2,ENSG00000124191,Sub_female,Sub,female,DTU,DTU,ENSG00000124191,not_gwas +female,ENSG00000115282,TTC31,ENSG00000115282,Cg25_female,Cg25,female,DTU,DTU,ENSG00000115282,not_gwas +female,ENSG00000134007,ADAM20,ENSG00000134007,dlPFC_female,dlPFC,female,DTU,DTU,ENSG00000134007,not_gwas +female,ENSG00000189292,ALKAL2,ENSG00000189292,dlPFC_female,dlPFC,female,DTU,DTU,ENSG00000189292,not_gwas +female,ENSG00000135678,CPM,ENSG00000135678,dlPFC_female,dlPFC,female,DTU,DTU,ENSG00000135678,not_gwas +female,ENSG00000177663,IL17RA,ENSG00000177663,dlPFC_female,dlPFC,female,DTU,DTU,ENSG00000177663,not_gwas +female,ENSG00000124733,MEA1,ENSG00000124733,dlPFC_female,dlPFC,female,DTU,DTU,ENSG00000124733,not_gwas +female,ENSG00000116205,TCEANC2,ENSG00000116205,dlPFC_female,dlPFC,female,DTU,DTU,ENSG00000116205,not_gwas +female,ENSG00000123610,TNFAIP6,ENSG00000123610,dlPFC_female,dlPFC,female,DTU,DTU,ENSG00000123610,not_gwas +female,ENSG00000171970,ZNF57,ENSG00000171970,dlPFC_female,dlPFC,female,DTU,DTU,ENSG00000171970,not_gwas +female,ENSG00000196843,ARID5A,ENSG00000196843,Nac_female,Nac,female,DTU,DTU,ENSG00000196843,not_gwas +female,ENSG00000079101,CLUL1,ENSG00000079101,Nac_female,Nac,female,DTU,DTU,ENSG00000079101,not_gwas +female,ENSG00000169203,NPIPB12,ENSG00000169203,Nac_female,Nac,female,DTU,DTU,ENSG00000169203,not_gwas +female,ENSG00000155087,ODF1,ENSG00000155087,Nac_female,Nac,female,DTU,DTU,ENSG00000155087,not_gwas +female,ENSG00000197208,SLC22A4,ENSG00000197208,Nac_female,Nac,female,DTU,DTU,ENSG00000197208,not_gwas +female,ENSG00000121900,TMEM54,ENSG00000121900,Nac_female,Nac,female,DTU,DTU,ENSG00000121900,not_gwas +female,ENSG00000105048,TNNT1,ENSG00000105048,Nac_female,Nac,female,DTU,DTU,ENSG00000105048,not_gwas +female,ENSG00000030110,BAK1,ENSG00000030110,OFC_female,OFC,female,DTU,DTU,ENSG00000030110,not_gwas +female,ENSG00000166845,C18orf54,ENSG00000166845,OFC_female,OFC,female,DTU,DTU,ENSG00000166845,not_gwas +female,ENSG00000119147,C2orf40,ENSG00000119147,OFC_female,OFC,female,DTU,DTU,ENSG00000119147,not_gwas +female,ENSG00000227835,CARM1P1,ENSG00000227835,OFC_female,OFC,female,DTU,DTU,ENSG00000227835,not_gwas +female,ENSG00000091972,CD200,ENSG00000091972,OFC_female,OFC,female,DTU,DTU,ENSG00000091972,not_gwas +female,ENSG00000164919,COX6C,ENSG00000164919,OFC_female,OFC,female,DTU,DTU,ENSG00000164919,not_gwas +female,ENSG00000144655,CSRNP1,ENSG00000144655,OFC_female,OFC,female,DTU,DTU,ENSG00000144655,not_gwas +female,ENSG00000137133,HINT2,ENSG00000137133,OFC_female,OFC,female,DTU,DTU,ENSG00000137133,not_gwas +female,ENSG00000100209,HSCB,ENSG00000100209,OFC_female,OFC,female,DTU,DTU,ENSG00000100209,not_gwas +female,ENSG00000269335,IKBKG,ENSG00000269335,OFC_female,OFC,female,DTU,DTU,ENSG00000269335,not_gwas +female,ENSG00000161677,JOSD2,ENSG00000161677,OFC_female,OFC,female,DTU,DTU,ENSG00000161677,not_gwas +female,ENSG00000128052,KDR,ENSG00000128052,OFC_female,OFC,female,DTU,DTU,ENSG00000128052,not_gwas +female,ENSG00000171444,MCC,ENSG00000171444,OFC_female,OFC,female,DTU,DTU,ENSG00000171444,not_gwas +female,ENSG00000119227,PIGZ,ENSG00000119227,OFC_female,OFC,female,DTU,DTU,ENSG00000119227,not_gwas +female,ENSG00000104886,PLEKHJ1,ENSG00000104886,OFC_female,OFC,female,DTU,DTU,ENSG00000104886,not_gwas +female,ENSG00000182872,RBM10,ENSG00000182872,OFC_female,OFC,female,DTU,DTU,ENSG00000182872,not_gwas +female,ENSG00000107819,SFXN3,ENSG00000107819,OFC_female,OFC,female,DTU,DTU,ENSG00000107819,not_gwas +female,ENSG00000215347,SLC25A5P1,ENSG00000215347,OFC_female,OFC,female,DTU,DTU,ENSG00000215347,not_gwas +female,ENSG00000139656,SMIM2,ENSG00000139656,OFC_female,OFC,female,DTU,DTU,ENSG00000139656,not_gwas +female,ENSG00000118707,TGIF2,ENSG00000118707,OFC_female,OFC,female,DTU,DTU,ENSG00000118707,not_gwas +female,ENSG00000153802,TMPRSS11D,ENSG00000153802,OFC_female,OFC,female,DTU,DTU,ENSG00000153802,not_gwas +female,ENSG00000162191,UBXN1,ENSG00000162191,OFC_female,OFC,female,DTU,DTU,ENSG00000162191,not_gwas +female,ENSG00000095397,WHRN,ENSG00000095397,OFC_female,OFC,female,DTU,DTU,ENSG00000095397,not_gwas +female,ENSG00000126215,XRCC3,ENSG00000126215,OFC_female,OFC,female,DTU,DTU,ENSG00000126215,not_gwas +female,ENSG00000205189,ZBTB10,ENSG00000205189,OFC_female,OFC,female,DTU,DTU,ENSG00000205189,not_gwas +female,ENSG00000101974,ATP11C,ENSG00000101974,Sub_female,Sub,female,DTU,DTU,ENSG00000101974,not_gwas +female,ENSG00000103126,AXIN1,ENSG00000103126,Sub_female,Sub,female,DTU,DTU,ENSG00000103126,not_gwas +female,ENSG00000146540,C7orf50,ENSG00000146540,Sub_female,Sub,female,DTU,DTU,ENSG00000146540,not_gwas +female,ENSG00000167130,DOLPP1,ENSG00000167130,Sub_female,Sub,female,DTU,DTU,ENSG00000167130,not_gwas +female,ENSG00000124205,EDN3,ENSG00000124205,Sub_female,Sub,female,DTU,DTU,ENSG00000124205,not_gwas +female,ENSG00000164404,GDF9,ENSG00000164404,Sub_female,Sub,female,DTU,DTU,ENSG00000164404,not_gwas +female,ENSG00000176476,SGF29,ENSG00000176476,Sub_female,Sub,female,DTU,DTU,ENSG00000176476,not_gwas +female,ENSG00000172716,SLFN11,ENSG00000172716,Sub_female,Sub,female,DTU,DTU,ENSG00000172716,not_gwas diff --git a/results/tables/intersect_by_type_and_gwas.xlsx b/results/tables/intersect_by_type_and_gwas.xlsx new file mode 100644 index 0000000000000000000000000000000000000000..d679e9fa125466e7f66cd04c9962b40660cc2d3f GIT binary patch literal 61458 zcmaI71yCGK*EWp16Cgm4gaim4G`IzKch|)hcUWA4h2ZY)wge9$NO0HS?#^Pn`*GjT zTlKy5|MfjnHB-~OJ#$W9SNG|e>2s+nAfvoOz`(#j0H$YZBmA!o`{mrk)ylz*o$a4v z&G#|oJ`S9qb0Mjnrz0m>jDnI5+Tv9LCVW#Oh>YVlBj#k6@Me&1iQ}@_;P1QriPY8( zABs7$$i)%+S*^%>EJp^s0BhIZNRo-b!F0S~g-u7PeI0G`*E}GIO zqKyQmkbRU-SXNT-+eC^*@QduQSQ&7&N9|$pvTJ1IxVkyq%Z5PrK*Q|Mi6vib-(Ohe zt;Z@z92?ZyW?TZf67E^e?g_|YhR!Z1bNH$X=oqFaD=kMa04N|KAgKO7AtHXMVIT=~ za<_7FH_`NQwsJFK^LBKoNgi?f#X%qi`fvr7$1&2>k~%0%u!=!}A`q)Ygl_42v4*FuZBXmHkO#OvyLWKe59VK#KX@RbTI%mW)#D zQs9juFCxdLab#P0)UTLiT}@TyQGbL%u9Ae7cY(27s zLHw{_v#-^@fJPxn;ZC7T^p5VKn(;DstnpoOX{(AkaM%-Q)Lo^mEW zVZZPcvDrh^XkQr`RZJqjih}Ne|3?e?)MzMY8s`+)GihY6N0{m{p>7?e-)J(e0*W@OSnaLS`b zHr*6d0hdGpfT|97t>{NGKr0J>WJ+b0wM8NLKzCLgYZ zT>@26QcMo0EF}^tO*iM|Z7EyHzc{*N2j58P6t6TER zsbbTmtj+DXG|98eZ6VuY)=cRp5&Jee{NTVl&uKUak;wZJb;q+5X-ZyVeA0lNC#5H2 zWp9Z7R%A6^pP;T@Qh)Cu#PhY71cJb%y5Qze#$XuKtN0c1G_|21QgQyGd8B~1z9lO3 z4$VCW?q;eOk?cRt_>e+b&VS; zy~$H2_9&J2Kk(7~11wdjcNWD9s4V|=xKq3U>+Qh)pP=XkbhS4J0`30+_kRMUxINM* zf^fKex*uN$I9WZ`SiaZZ9wa7f%@@-lH>5ZRg`i0piU01){pDx2_GD_^{TGt6XkN(c zjjE*fO zSXsF+{{`&m7T1rR*;W?_{9ZJQ zG$#LWQPW_=$oJB5lV1k?|2rbQ`VSXwwq~wYmKyFal-Ria8vp~05_Sg?PfR}Dh*UkY zP1koZl8SoB<`VtM2EpwnO3It>tRSyrxM#Vn& zfnXC8qR_J*(dWCvK@$dbr%i2R$DhQmk{EK+k6O&qZLn9eIHd z_nQeO(CxmmI@q-e=>F#L`h15$H1Kg-2lVv(u&@q--j1lRLkHP=0`D2&dv!g} zch_EdyCB$I-$Gs>^t8_l^l;OPPa^_`EtxVW8Ihu&YlScZ?Riw45Bbp}u%bLTMF zdY$6YKc@2VI5kIdkqJy4x&wC{Do=^MmucY%60w05* zT6yqG=DTFL{xXO_0Xy&x9tgpF+%U1?gWhaHZfPd>Bca)v&;+MWPu3eQKObK7yFcgM z@ar@N2~p+e#7UVaK#&OJGHn7BLH6+c1cH(WB0X^2wCQwmt~O7JiE=3yHB2&`TMWQ? zA2=RK1J_NEpAmjzkBh#Z2&DG2zVLzH3RHU{3X03g4Q|lYm8A<;VtM6}5o+ zJh{PU5x~`P3g3n&t37b3WGe1gF4WL1OaJP4WdQvo@eyXWg75sn~RH(zi9|!R%1F-sM%v^DnIwl0tXPAhgt74k({Vq>;McU#x5wcnzIkWisXVx<~ zHbXe8p@9_~Ww9KqhPfVI7v(0cObHeNmJ!B1^^}=Z+=&NQai-9j+8Z~O>99m!Pgx|m zrn*mE)&MkTLK^rp{@|XRX^ER1yW!$5IIq_(gK@ENVW0Tl30&97=MLzf09SL*H?-7} zG~Q*y?Kg9#D4zUU?O7a>!HzRQ9}{4^tv&J|Mx>EySkeP-xzZ`22D4naKaL{-hI9|7 z%jDc2$m1JNV$AxIG+4p;3(uq7%L4-V*7k#q8MXEHG%16*fD>x3L8t6|1NZHd!#7UA z#`u>=ssMaT)?g#3zW>wjdVQ-=e0$G-`Pw`Q%LkK?IompklRVX9EQ^OCHNbo%1&m4U zS3En`6(5ZUykh>jp=U3e_0_`Siv=a>zL7wB{4;hkmuXP$!cD2@A`~F(+x2&*tubc% zop<7V{}fYGhY9I=P)ARZSC3&A)>8)OOwUzIaH&?PKR7(S(^O30`zfEOoNLIkH6_>LCMfp_T; z!8Ue#>Dq?=^$24>UN!@KbJrQ3ptOzxnwT?Wz=A@=*L$$GKvVPMnk_%%18GTBt2cl<@u~ z2_(aEdSlqohBu;ns&M8YI)|w1LrSDq=d8WMEwc~_nESXlGL!)MHT}NvhFqWY=6uoZ z6pwwof8y3q5&97~x6``=2GXd7eQ3dhDT2t;WJ&b?_fWLpV0B{KtNu#He0q$XgU!iKrlr$*bSBl;_)icH0oWIDxU|mR)4MAp2ePg3Mio z>gfg?{V7D8fn1=F$F%L6pQObO(V@8X{X8&LiLg03zp<>tGs!k+o@Zl$X4M+NGJwL- z(7DFCFGa&#_cP^uysPY3j9mxQ(+&ayD0W|n>7wNISP#S-2DDkzd1nl<2HHLTjzBYf zzTIM8s>G3QNNF>JbO{BbFz^1IA;-WW@U$u2lwqhNF@Sumc`9M0VzI#1e&BcPZ(12Z zs~<|s@_a~D&JRJmZt}PIBY*m8s6?kxZpLp-pQL`oCMRBuhOtb%lqIJ`j+fHUHd$+1+XmEsp3@E99nu zrv^1+{>oiiKZH<7mp6N*k(?AOu?ouysWL2bAm1Gu=?K!7wX-Bl^Xj!z{ANK%F8)33 zTE+C7jOhF~W)Saz5Dnw^g2Pe#snd%(uIhDFcB$?q8w79h;_U(v3YB z@}AN@{_Tqp!c*n8y3W~N{e;tPR}*}}1``^j^c<~%&$xu)q=pm~i?%m)673sQ%m~Q^ zY2A)*yhn1IPD?}CmK-jEKVms<7IhT^OgA~49P0VL_lD?>T+5fOO@&6@8G-7XyERAf zPLM^1E4Q<%vrGb?s!BH5l%5I4XR1^F?kz6tw*e0)O@C5wU`O|{)2gCWg@|UO=P)oPV?2Fln7mRy7fw%B9{hDJ z#~XzBAOKcqB1kK?HEn4=KP=3na+LnlMtSgFrq)$cTkUV}mW}!edb6Q*uP7!O#i&cM z-9>wW+d?MeM%LOzjqdQ~bkEPNb~dK^LgBo+l$x|S2~?-!#{FexB?hcG^bF`FY$F=6 zPOK`-ZERqwaq37mwCk@`=3)C7I_{NLh02P@w8}ZFY*DGdQf7o#&QFDW+8#l5Ys5uU zs-cVXzPMT%CbTHlagSnk&Nwh*8&0o@>J(|ewOZqIxjJx^+w^TQS`;`tEq~oo74Mb} z-D|I{@h$)B@W7|}3E`)UQh?aa{SlUdUPk4o-?`<({SJx(jnI7w-2C`ggN>I~TJE;1 zT!!x5lSAEuY-;@Ah;dWY_x-tDhPyvzC};F;me%pmJGh6LIOf`>MW(zHwMd^Ix0hEX zW_*k#@MO&<)IZH6u=8`?aY3D{{X5-FN84(+SVyB>Q-TJ(M583+{@}q_fvO=llGW`fx0h7C&Xm)u$bj^nKY(&q>2F4@CbKcgbo^oyy+8 zy)1VY;Z?M)5G2&f6)ASVFICIeSX$?)oJum_a+jsM?8i8zZvoEv-!6~vDa>A3qoFRA zfUly-0?TV)a7m(Tf4o>L4-CPS4L#i!6`imog?SrDJzWb3^{lOi)vP3xlht&a}2&QT+bmx~9i5Ipm16ho!*;HPlTE z|DxPm(SWtvroWeH!aj@tntMj;mw|9oRI>KQk%D1UchQV)!R=)HH$^&QEYh|0;aqQ5 zWT|^Qcy@^#b2NYvYYn?XMz9PkU~95wTVcWv$)~x(Q{idINfA@f6q=+xU#NvSj{!c< z+9uSMeJjfp)wOhVdxL8P4#Drlm@x$RcI`b=X0KXUp-+p5#xgeZ>&l^zOUsUr8*S>B1>D!#TWJN z3zztv4U~oAPIC|`HPq7p3MF>7xLk=`T_+)v!K+9k&2P|+#(fEHbI*?Zw?K28q}%~X ze!r)NapzEG`3kI*G&R4a46aqphBO!HRsC%Kc-q>%P%R)Hq;t{SJroa6@~lV1x!%7v zUNi#4A-7O!c%YhEDA|&D4wZG)e|btNJ_w_q^*oyGXQ)ia;D|OS6%(@EzDseu7IVe{4pYT})#g$i*#`c5 zNwVU>TjrUrhs&9V{z6k!!u^^SgI!2F%* zXrgv?Lm{l1nQDhIj+H5Ah z6aYsUzXopjr;OU8+yUS8-FLq;lZq5!spCle_8U#>cz#bq$+*50ucD6{e){WZJ=`6$ z{91wB8z>lgm7(D?$yX&4xpXrzsMJ%)u-qrq;YcJL+lx+6K5AbevxI_e{5B`&F6LZF ztoPa@@B&On_#yY&%GM>Kg*K~6p3wF38(wRGx_FzkG4prI_tcw(=c3qqGrcbW++~eq*%vWwuga!k{1}4C%=N z+hiIlUh8*J&KRJd=R0PTjB7`o8ELNHQ+Lx59<8`^>+tE_ZY!b`pUDZG@zfOV+6R+m zVm+4TN>%ZJT0?x1oqXA2mIK5rx^mJ{!@4JB{H#jNj{?abyiSy+xpB+s-UyO5Rp8#x zQt+KUvwmpB(EZu1G$>bgtzB@fIDfjs<1Jwp6204%gp?gvLs~3*JzWxNW6D$MroW$} z9m^a^G-Ty%OYuPPnv5IJ?yW$)UMT%*L1Td=H`nP^b;5OoG(5+SWqD6L!6R9=RD84d z^7R9=Aua2-T7!o}j+US3!kgnhrw`<8Q@-^oo$X;W{rb0Y2r~%`%YyR&ZokaCFJ$)g zLEmFL@s=8#^S*h|E_|j=DllV3eY!X7pA=xl^-AeVf10_Ev@@7QwMmsv{UTb~^MO&D zI(4d1c$i6GHstCrR|jW{ABs@zL*NA#7x${j%)rdMQZ>e|?nbt7CN$*sEYSvwX3g!% z`S`<~vB55JnIh#n+w?2afIIH}7;D)YiNwj{ZpV05gc<^fH-1S8rI^8NLIn%JCQ)^t zQgyst`*UI~i4fDDp@hXQd*w5`IWagO84_yVBFQE&w&MSNj z$yxL|*HtWu_e3t?Fj&$fGolebq6=)8tNOc4YUw_3*3f8~Y`19^@!>jtW8CkeelM`J zD=kMF-BkI|l9+-nh3~HREOIx7t4dAliMRg1(YaDe%YI*O;pY2s@TD+SHG$@l$PbIF zfmV_>1iR29|H0Jw_=B39yco(ukGg=NeBni7EaCTRs%{)f{w|-krZ8@f`~Y`5af_^# zf0d!`u@1RL=i2BXVPTaHur1%kLS5a4mv~FX+hOK`8CQ*~cj!a=wd4Yh zfY95rU*<6Bd!1%<{+w{gYuE1qLHd*N+LpRys^34&!~yib`o3Bkf8smw!NnCQD}glo zGUY43^XcHt6y?G_I`9`gbI1SsZH*RtZX)CERjP1k`>#8Qf6+sjKpaX$#=)ba1nwPp z;AvY~At{9~Kl0qWaiKMl5v{xGau}){b7pDvQ&`lokQU=vXIad=Nlu=YV}(Ea*uusxu``IIEeF{ZEHmMu(N}l>#^pdgGhIMq+ZD(aMBbx-3J?=>e5= z!$Y)1=FPOPRkL0nN(+PzH;f;P>)6oeEA~6b`WwV+mlKW4sf#`B$U39r>a&9b`aV)R zm!$#^6$H^Prt;bcl~pL_4pfu8o}}B?`b)%fGRe5cVV zI#3iWJZqT=oJ7MCXwHA=>z;gVUQgJWCEs0_aZ9Hb5)^WVZ$*vEni!=VT5y%l+YWzU zXw)$%}wbotW>V~sy zyEX)L$X_8lA161@K=}uXB3P|5+64uzx&;b@-zl{zQc&=#+77zw16LKR8aoj+dQLtp z3ob+F3eOBfM9wn@h=hfxY6TD*cU!-pxxX7v>!trnJqPedekb|lawe1;H4uKx(u~_B z(GU$;os+tg02m^pjV%KwN`pS35j+en4~;`k<|}4?HAF7wc5pW7I-NG6TI{uXJnIrC zP`Kyt%~NZ(5GD2+`QT8p*T&~xJh#uMmG?P>5Zj(ArVQ7^B z1b8PBy%8d^+%o2ac_eh^q_I(6ja^3F3{2(wEsa=h85TnD1j?^>c@rm<80?g=zniGo zG&EoJNbsA^3Mmw7ArW2mDl**?`{mdYn`L=ZsABXMh8vKl#cSVrCyYa%%nMbDu;MN< zX_Etw9|%o6_P38nmS0cG7b4%u3C{=kTCY3V|Lo5gZa8UH6+@l;c5X<`l1=A~ePG2J z%Lx=PL$Y&jXYiD+R4ugynv%fLmklSp>(!n{EUnx3rRHp76WCR`1K+4|ooOwKx8J!0 zUu*@ABzW42C%bp7SuO*r!6rf1c8X)?R5=)E$lWW~6^6MU#0yua8*!YI8On4YKOYU7 z-QQs^a14IMOLNW2uO$a;0reBU5;AR$Ym5BaCbZ|8=~&Ab?z$bt<7TG&%?{oN9{;tW zV7VgAT?m|ZNPmS-+u*{o;<)Qk=$LaKBGv4^lTnHtCzHc`d;?D9&2mJkL8iN+E#VS| zRgaG&7u5P)S_+X8ErzNzrzw$jS1Iz8UjWzHx-Vp~ue%+ZPi35Gi!P>p?Y)0Bq0X)H zs8~$Ybn0jxwcmAqkhkqMeqc=rjZbeWM12yj4IPZh3>t5o5YT>=RD*qtfvk$kGt(Cw zhfVv=WLwzBbhlF7RBUnn*1S*YmJn^T%4}ASYz!80^ee2Z_JJjIuOIZbP`Y2{Hn)Q~EM@wFVMIL^a}cio@P!>33`pG6F+jO7xc>pr?1dKgx}NPx$B-&V~|XtP{a z{kZL*wg49^SGBa=7lD3KaeBtdEvuEUE|4VQ9uF~W-HrKH1wVw>_F|2uCVB>?SgC~? zDVDdyHJpvC2YV^!H}`FJtN7Cd77wXL8KhPNk1@HJ>)hp)PK-G-onPstokwQ*JN(b% z#4_@)e+?WTRnLOU4F==JXH?xF>`f(l8kW(&O}`qd>v*n}DEXmE2nZf47uoml=w{>4 zt%jAo^N#ME@GKQq49!$aOB(nZB4tE&cauNHND&IgUu%t95cNiv&g7zU=cnAM4{6WX z9&)cSLG>`*(?==WFnTf)1ND-XhijWN%|7r^8I*E8p?N9|587K}32?ahKJwC>Kq*4d zs08nxlQp06{fqqmQc*F*p)wF@xu@N7aD2aRiRaf!G|Hoe_mBI2 zRA7ovkgZsZnW_4*pJjU=3? zuC7DS@9&aROf?t~dKU-5_qCa)*L45Pfr~WnGp&o(lJIt#ARjQbgd?M}l8HeRq5Su= ztpS0Bfhyh7Z3bRijpP$_Ag0zVCp<1BestgyJNH{#&fHvG@lGG|H({$GkineuurC^A z$Fe1p?~B2>jFmq~|8yKW7Wvz&&9-FUP?-maA&Sby0Ajqh#RayPWuh(J%^h-P%GdWR z0t#D8rS<`LTuU>oABCA*lb+?S|Ii#+u1(;NXydRImW~ib@?_n2&1#sM)9-X_H$9SS zRpB4kudh!X#35U85DViM>3ao@p#pkP_~^V!B72MrKdI#LmR~jgUFfTi&r^2gtXHt` zQDL4eMBb(60h(vQ-sgCgBeCuV6mE-Om>L+gt}SvL3a8tF$fqPiRp$LzhR>ttH)Tn} zGsl#qyxa}cL+|4203Bxz)0Lf)9xQyu^#+2BlWeQCMNppNcJ!59Ra!~P2-bc5Q+vkb9`Sy9c2DxC%ZD~JST0h7l8@-?yG~B7CMfSkLW{V%Pj6FCce4i>Px}nW~(rf zC_pV-&zdP@#C&>Vn*D8Vk=2j1k4Zs4-FNA!tii9pSd-vYdak#^57G~pb!^ARGo1Y5 zW2(BgW8e}4ZHX^)t5&4}5k(R{iR{7YxHsxUA^XmTww==vQ6UEvwxsh!ofDxH%Qaik zW6T@!&W`a;GwxZbQZf;mv!hM?A@=?;yy~n5?Gbz{Gd@$NHNAyOPfY=md^Pt3;+EDu z)2*GM9|a_R6#eM;+c4Li#3nW`({B{>Q4WSIoN5eu$v2y3_e4Mo$27tSWM;NMT{l;t z2K*l1JUV6@^86V`RydHMngz!bm=d}ulEOseK%wUzsb zU3XZhR4aaQ34xkJ6hoP+?vm$cXY7kY5G5rJ58HMIwBBK^C8tskGTP%iJ?>I4JQ8Wz zl0l_=bTzn899F{@vzrULs6x;rU6z3|D#r#!TG8fwb8=pPq+g4dOTMjO*VnzMt; zAe|&Ah}8TAN(I|-uFn1Scq}ujM(W}prDW(Z8u0!~rO{tCpe3glLjx&D4JvA)%I6ax z6jRH=Qm)-(+7QhwO|kIfmF9-de7j`~dGO0p&jB7$oV60k3@32haXQ?Qy^5G-3XyLm zhmE(2`3+d2^(NQhZ{Vl5zl@i#DaG`6kL8n12amwT#hunoJ-pnejeerdr3Sn$GBT^9 z3%&ADN33{6VQmxRuey6MJyeM8@G)KGJE?~RWb?qAdyVijkiFS96; z!-*E6#k~8%Ov*fkEa77?{PG(A{q0Y$luLK7A5OiVlL3Z{OnL~U_00C`@suW;t+b`y zcsHq2tW2(B?KMg62Rn+KZzkWV4{3l&xvy@&UZ!qQj=XX*E;&Y;s;^4ekUZ7-gYIWb zc~izd1fvAMJuC$K$|vkRuU3hwn>J^%trP7P^gv4 z>ThBWv>nT`*%G?Mm4Vkl@r;Q%6*}OKV>kdoj(W2U$>6I2jcRzSRa4opdC=Qp@Wjk> zvZO&axVh2Gf!I)tic}@_H^+Rw_9)!p8MtU?$lnav`$BU^Wo_>{D&+N7(u5^$}NBW5mt^Fq5z6d-C5qy3)w^iOfuPXkjj^)zK( z7m`xp{JIpHYeF?X#6QBmnX@>qM|3KNl6Hprl$2WJ z6nn8b4N*vSk$W>*2LRD$t=~@g?BR;=$Xo5n82bpC zxtqn$k}pTC7Wi(RRDxa^=nFLad{**W4*F$KKlh29VHK5W4%b#o$f&5G$dXDp$lh8m z0o5W@(!lE~aB94GKoFm4(C!-hRC;j{fvm36%!!~Frz4*lUAT4B+YG5e!&_-&DC-wE z4ygsvPfvdEyT|QAFItLEmbZpM(dMQ3dBQbE-JjMea^+56jh^>4uh-mD?=s?V52}^K zw+_x04?2G#ZmmU(cI$s66Z_*zO@yn-RN?Ux?SPr8b1=$d;HR;Q%WiA8gHru(lhQ=x zSDExd`5I79if_bNG>Ve8`eTe0bM<6Tp87iNzsV2~QL-QTFC8CnD}zQQ0X{9-*jT9x ziWB;LweqP`L0s`S(O;D}afd5*L%Y24HBG*6|86>&%3rH*kz1N9$}(FoSaIR$pPJ+R z%gRUyFSY@-RQ5h)+5!yDosVncrf#sp;_0Qxm z*E&+{p-x(_v=|@=qHfFPZOj+3h>JFD6SsWDU2O6fiBoZhR*QM>Fx?C!yV?JYYm1Af zp(GRjjQ-$z%QW7>5IhjXCZ@AwxOu%q`YJ!pU>-PM_6Bg#511|LT7E?F z4G&{MFt{|9$J#!qDnZKH@Oj?9&=6>RknURwE%srN1f-y{4>opNX{D>5f=&1Cy5HO& za@k7hblBpWw4fYs@^7y)|4NXGgvmP;0en`1KEkiR)g}#|t9oTS30kc*ktk5A;%`Bo zev`5cv|!;lA*p>>CTw;=`$A#GsGG&mXkT z$e`vzyI%K)m?uJ`#?PAbqOpF3%xwEVv!H=tV~w`bwnB{T<+gG~2N7|kEh#^0=vGNT zs-l&%r75ho+z1)d9eiF}sK8w*b*dHrGzb%= zPGz5_dTEQQcbSL}pS0mLzt)piy~w3JPXI0g`D&0LW3IIh*g6<^Z+_i#vVY5~EK(&q z6RM^&*j$b>KR=Ye;g(?6V>z(ks+qWHm8seACbhN4G_bJ>`Ji36+GRBnDm40VGY{rk z*Ow z$@a+NYL!+Rhns$Fg?OYmq8yjT zhkX?}cOT_MTi0|a_UTGwikL;~%PlE%MdyHX%8@Qjqy7FIB49q!#@c0UtX2t_B!nHZ zq@GsS5wJvU{H5`iF$?vSEwk9QVG%?Hr=|MMyQevc;fAcUahKXoDd(MKdaEi2Zw#)u zm9_dgAbE%XtrJ{QFQ~-l2Zzc~0Oqc4H!Q=|e~AxrpxV57N<c*BP3dMZQRxCKZ^6%PSK96~WlubXdS?ybeQtgkM6ke4Cv>X*aW#Sbf%TUC)-MX`U zgEdML@%rrm(TSz{`pOeZ0vD0J;J73tzR=#%6PCygVS%!je32U`onPnXbw{}eW=jIE z35MAYe>9w^#$uhc*Wxz2x78GiuPlwnu`@}Aj=L~H71vi-kLqXEA=l$ha%Mo)-kI-y zu1iM8YUkT2eC<+WYxZ!uu2mj^cSoP`wE_8EQZh$5K4sVB3*dY-`g5}5?lO)F;hh*!4_VLHfy4Ea_bfJr370XBmet$5B&~Do zm{zd_hROm@uN=2M?c};n)6HxvK!<@9QC%iOGPLct@Ut;71Xf6I>^W6>koj z%=w(WFjCyFwl7(t-(~KsURGtC2)+H;1-?}>VxOiRQsAx$uP{D+r&c5{lu{y$aJ|YL z^|ezoO?L{kxATY%5EM=BD!^PBBD6*evsVEoJ;hK(Um&Yd)1u zk0KezNGErnx@@#vI-b{z?e={mV8prwGHCnZlIj}@)#+s4cIb-KMJFEfITksIF4KffSAgehcWt`!7N8aw?VE7s&|>xc7AzSSH%rr9*j7@yEM{&trCIp8X(EP9vf zz#g8m?2|x`el7JB+v;r4e+2^+oi?L3V0x!)+fEj#*{W>PW8B1@H32oTCH}T5vUjT) zhwdG*OCQE3U>u}RUBW(lYga0(iR;|J^7qRJ5eAxo>MDKkU!6hZ$AKmfuX=-JcN@uk zw+g@hx(xX(EGVl%B&y2@`g=7R=$FHVI*&;#s#5R5sL0=G{!6Dw=ySruqKqcObB_u$ zn75I$b0n*UcJOI>yYy8K7)ezmp%j5VChzkArvUXgS!+LII6SCm_n3{q|+51u4S!7?tzTG(KI|}QipMoDyznS(B za-($jK1DCmD!6gM=infpmISk${i)PYXy)}~MLQ+-_yYM(ewicxS+!Ru5%);nP5T*O zhyFJLX(qe(8^^uB-pIA%8fn_ywj6ju4d;(^jVYy z1z1vohzsFs*TbP=mz~*Zxk~0$XuFfj@eeFi*!%hgGLv`N=C(}W4T17wG)^y@)Oay(igG{o?kH!)$P37QY zHp^vcFDafHMBJ=tUj^#K31uUH7K+$coPR#fSro9^B1K1Sc8`| z1A|Z5I0##&M-LZmDGlGEZlblUG2T(*ggge%{et$6v(ApA)|+tV4UR*|zRWf{7~jQ2 z7UHI7joDbECx_36bXd1}@M%BMRDw}Lo6nvROc0rS<#*<3ZcvZK%mz}qs4yo#C0k{z zT_Z3vK6;xi94`O(RIc+h<(SEf8HM{AZTzyK$#{R+K+_D$Y1w<7m@kz=ybpHh%;X7a zk!@-mcaRCTD1To;%HHI8b8~M& z*Dnpx#tpZyscSb1T<9rU&S&@9ZPf-)S zrmnk>gVnz&x+TdOMW|RwH`nCCs<>Ct{p)avzN6 z!h7YxZuK6+xuD?b^&qQ-_({pG*|yB#WTB8QwF@RPHl6HR&r1yK%;m&v8fvQXq!kD*VH~Dmu$ImY-kgvi?M`+d^v_ zWiAQ#H#sBrGdDDpm4&^j@Hdt6Xo6sh$hF(hCJ68(fLjC?bK-(AK+X*XsPYbT%lbZE zpHjH77l%Z5hH#laSUIwGUW%C>P_(a*jHFo(){Hu>w@pzUyk~N1$!IeCU{>LO+eAT` z_$76QMY2+Y(yg|zP|w!>#435i^9SwmvmeiX09w)u^dUE?i z&l)Iod0Cd^6T(fsip33`!ocgx#g+C2|BLvnFd?aG;@?<+QF~vko>^Q!_4hQ-3VDxW z(`PCgEVen;ipK9@JgiMUu^*D!ck`wc3Mn7;K2)sZLKAay+Gu6HCh6@U2_cC~Do00q zAC7lvreOanR;c#laVKArwrx=UThjJF;-VL|fxE4hqt$|&KGidETmDP{>QO1U ze9C#S(3t+1fr+x5#p_7F={qynk6{q~l4_Zl3e&o2SlAT%PXNR*pl~;^4KH6Y!&2&zEOJ z#9bgqxpYe5yhIDILY8_oCe(eItj_T{1|*Ox~FEFiw< z2~KBBZZHG~3$z|{*>B0o@#UGd-xOc;$(i>;@j1UZ>a)Tb1f@}_7E&2ejRK#>qIu`9 zYb6yojPX}`i-d_NfEL%{2eE5Jy4|37Q`mu$ybb}aFVdw1r&y_Zj)X-+F0ST^gS3(+ ztzM9#6^k&45 z8e2Y1rlNJ{I2}N`w)twRC!VjkCn*H}EX89Tb>x7V4i6&zns3MSH)tEZ=D$&h=E9U0 zK9=G%G3I`m<#@=HEPPvxIrrXx7?KQDfSHd*K}fKRRn1HOuuBj8bP&&M3U^9-`epvN z5m(o(H)?)Pg_HEJgsU8lB8RDMo7AUWX$R3heMyHVYV$P|5Hgh>PWS52&qa)qPb3n< zs2OY(>ZA=ct`_Mql6u<3tF5mAr4ZPy;unrfPf%_etgRM{O>2hA7yMerJ$pveDHr z=_xigE!Z0*nMR(3`#f}pdAKTl!d$P~_q+A4%azfZK%U#Eu`5-hTeZ&8Ka9a|sbL;? zs9AGV1+eEnYEyYcWF6j((PtvG{o+jKbvMTTJb7~!Y)3VzsSonMWaVzno z3Sqmo<>gO8p^9?nNoJg%mPpEJOUknVjnlam$DFUGawA>G;P&}b8k&*KnF0rb+*=iT zA?xeR*xc|bP|NDEuIGfK@Nc1|EZPLyvh`~!A~6A1?M3BHtL#FjlsSfZa-E4aT0)MCvv%x>9qVp30{+$wZ!-PEp)=`BO%vzxy@oqk=AYmn}}0BWZD2(?v?*5?VbT``+;VLtQbxbOsCeTnbO@4K8-H zrLM8Z`;T4oC2#?+p~}V;`?XtUsg~A=Tc&=6XQN5<;e9>8Ys)DYSv2YxrX_>eGzFHm2O3V&*?~IXYh*~5okv6xd9UV z{kB{%#9-^}JR+dgXaubza?w$!V7I8Nr|0(;-XZ%Xrt?_KFjYSY{9dsV#GsncK_dL0 z$vHM1A64x|KUhTh-y$;peqn;+s zEti7A2o!CtPL9SlR|lPZhB+|Yxv!;vJ?TY1b&&3l(m>K~Gh9)U?nwpWPb7yiII9wGVogfJ2b#As+R_<>9qvHFw@bA3(KN`M?e?-oaFDl8L;w8kl%?@dp0G-$P1VpWI zwmFQS!n=gUqeOGSfJmyGysL+%-Q7ovH^0N$!er5!9mHtc4v;<2a=q~RylAlut~{f{ z(C&0iyYxl2OxprK2FOZjqLCmAyS3|7{-BmIuvC=g0a#G8E^vA==|SuSHDgNKv>rr} z_Y@m$(XQt02|5CPDJ(WPhW07B1L=rp00sWwbC24u&25srw7U~4z;dhp5CNyAAEipe z!LP50IYF4C)p(74`Xgy#W$(+5KvH90SF%@DOlo&;x&(MS;^+R=kb24JUaY^MVfkOx zd$0e0c>Q0bilIgczzG*)%s`S5$ZBQR_3F1-TLn2Pt?_MhB%R=r(`R-YrJ;&It{)8f}V=PPkNpoA)x!QbJ%WOAndu0MijnO z2jA7{d5TegS9@TOCV}#>ORpaI zDLedr1_XtIo?ogQpM#(ypnITF4|KoBTU6x8^N^uS+lnrKxjhG^91~P z5I%SgI~}Y8UDLo16GU^=VK+Ua@QV@A=SN^5WCEV|V&&x@6_Zny{b$Je{0lW{pnn`( z?SY;^K#yPlDLl@A?$_ZrE%2j#&_5og^}t?i-m{Aa%$YzFPS($tESh?jnii}<9X5Zg z-6k5x0vl}ltwF6ebJn7F)k`Pmkm{8aw~2_c)Q1xjQ`i0AU@V-rkY4GE5vcC-f0}y}fF`ePZP>BYQl%|bs;HdS3a3Shih_!ePU^8%>8Y)N z3IP$QWfD;Vfkd>HT8q|NjDSd6TRpAFD4+s~BPyfAkx>!_0hLG?6Ci~AYw!I|!RYC| z-~GSu-s|OJvfnlDwb!%Oe(m8CvW=hh+2s7O=$7aem!x8Etk0|!3Ir(`pI5--a}_q zYd`-L#r2D-#kum3e_2ImF5WxmkE|8f?B1;VTAnvX8hrD2_!j*wK-##fLj0-Ym!Dg% zsL7tUu_NG*u*A=$!T&s|DD8~iyMFg0tMY=Q$}@Mmrn{Kb#xIKxd_Q+|&4dBT%--m= z?V1VGjc+?2iExy6q_!+SJ$3HPgU27&B%Y4Q{kOx4KjnGjfm7bp*VByRjQu<+!j81| z{g`HSs^qug+&AmK3AkA>_49P2`quaRw%?F!YVL`;Dm}^@9(m*ZCw~SwWIeeyVW#5! zv5_|}O?^GnXvNEjz&b_WkC{e+rN8|VnQJ-a=**s#2j8uW3AlMZ;9ZgB%L849d|^?6 zLfe^TR#^Jm#meJHXR1~v^}G9iR^wyWBeE=b=yO=uP}-{9CoU9tsD2eE%oT;_T1GEg z`#9M$Ub!}@_@p>i5-jMR^9etsxkq@lMD}F&1nJG~2e|g-3FV!8X9}}>-l|iE*Ca`* z5uK9O4-OVrkfp4ncuZt+UTPciwht6SbmW^vBr0U|7Q{A{-1g6MFM#B z@3Bo+J9wys5jA@~d_VJ9`vX|G=+uDxuH>N)Pomj=vt*X`azd463NKPxpjgba{Uhtt zwcNMX9$Z~f`CC~wyl`S*Mc}pEH`jJ;)jGd^_;cZJ_ZIWAt&G9q=2;xgOS(=iYwA0+ zy#)&b;@OSQol!du=enQ>o}^|goZiOsr`y2}YJ{rkkf^LWd#<|bLuKRo$RBuo5U^tG{E zT$7%(2!-%9m4nA2Nx_U?#0jT+rRI5m=<-7p$z$Z==~041?a{ylvwXCcA9`3)-RV5V zazoM&fgj`!9E=?}7CVp~J8&s>;CAeo8gSMvv3Pp-oP!f|Y7j~!+FN-0x2%#+-p!wJ zzv4|x;?sCZqtBy~lGnB;P@()QJOUygx`EBik$C3d#M0w~6JL%zp*=UKG=&J0fuBE@ zId~$Mbx+|f7oevgR?V{luT3BV-za%aLJ7>M^?A*<4Rr^e9IZ5|sO&wU(~LU!?%F89 zH)vzsVh!2Dcky1O3!PW(@T4kUSr;R+ya%S_U;gsM$46(D;gzBYww(@<(Hx?0jH7W;q+R_mhtSLvc)+3`W;8&5vJI05zp>}SNZ6PQw@ zvZ7I7-z=H49VnOdhJKHB2O_h%e?3Iwt=dIv4{obCwB4^rjX3#$OFCMBT&LfNvVzV$ zAum94W!7L>#`giXS!LJk8dJth)O~VKZc@_Q61W6n9ehFwRC&LqZKI|gXP2;vgMYdf zrFhT%LnxmxU>oD>(Fewo7R)#Xy40-Ru=c>r!O7mRpcM2gd>JK}CS|zWU}x6%Ad_W< zr)9j~EVR-1rjrH}c6b~j8^C37pSX#~E5Xq=1&qE|Su#fgYDs`F-e&_-cqQPpn`~!7LNy0+cD9W4IbO6EO}|W+xsL2njAb1Gk~%8Z4lF3z z>EXM|E9t3@rnZlt`Vi~VFoaC*TXo+BblC0RSrzd*Xz^Gb zxHxw_au}u7wul#O|5&u^pUSy^6ntp^M;1;zzoXsH)e1%SsfcNoBFinCV?mV9eCiGa zF3n}dErj%X3KDhsPX1Nb_Let{x4T_Ho^P9z7!eOng;f0=Jm%%Us$xQ<-<1^a)Lu#I zui`Jj01#;*&0j$B>?tXE7xrsDWQL@EsrglzTZe4_cWUA1-C5sBpI%4KLU8E265dG& z2FS-|$o$}p+h%J)*KNvimQ!R?GQw6DsE;)iT8szt7azI>VRna=$S3IlgmAcW>6J+S zyW8EU%+~`%qy?!zHV#A{9H$&-*VDEGc4DXO0{q`_zrlZk%(Ed|yJ#!5-_?!YJHDpv zQ9GR>SNs`(RkDcZt+_1cU4m8n#CLeSlVf4k4}P-_7TdnjQ~n*6`%;4F^8qbBg(wSr zwKO+!;e!Rh=*WA(vN(4d@;>N~6UpPSf>dFI+mvhDoMRPp8sD+VD*abP;^+4pOy)G) z;J^DFj_g0>uV$;J`^E|X-Y!q-?rX0ry&_BwQP0i1ms7TRy!GG=?@RL8m%0zedOUI1 zTq${w>UgcnL*8bexL5meV_Qvo%S7|RMbq|akNuM3)qnlNbk&si{RKNKJsxQ0$i;n< zQZwbSjp0Tw!h-wCL~6w{|3`a+Kaeb0?liD!*Iupn$S`NqR(0@2rJ(!tH_D1x+6TY5 zX!iXphxbqaiG7pi^|d>Xvr+9Ich}K;Fu?m#O5o*8(cFP#TNtc9yd#z9W2trfq&+-Q>%(Bn z=%@jE8OT4KYFL2& zx)VIf!{GYCI(MP;Y_-z9?dTMF_SUEh5dGo9U@W@ms=Qw;-P&z`&}lHbT7HJCQoj5s z+z&bMm=qgfaEho^Fj#q0{z-p9mi&_=8>C)pMRhKdgws`(2C_pP~_uL9pm8-uka@`e3L%Pjh;R;-&*VN&hrFt}*L)s$Fp@s@6T z>|tq-$b^))&+Xl}5 zW3p!HRk=%RZ~8ACH%@|nMPlh#te<>OpShW)#kTF}NTtjoT-{rPuw#nITrg;N z0~G8Pg*FDSQ>0X!i5xf3cP)l*vBz8Y1~Hd^6h$u2OIP!yZot!9eh)q(i&Hl`8Jk}{3#7L)C8-hB%mOD zHX*TRmONmFW^8`Tdm?ijeps&Xhw~&oCa%G{o%8zZ-Y5;5CBG1LQ~rW(RprCrUAo!+ zgH@?UU0NCc%R=4W$}czB2?x?G2jVKUwjbT#2d3#JJv91ivWf0ebcila;TM{(uss}o zcHpH*ja3?d>Nna^87ae5rstbQkNbD&PPLj0UQOe-+r7q5x+ok`E$_EV=jV#L`WtuH9pn7{+on$yR|Q5NPB`kMZb;Rw!T_*bxMS}(Va7USL zlFCRIT5YjM_s0A8jh6^)q*=1Te=7Eurasy4R4kqTcynLXM`uN~1Lqgoww9*$$*&IH z6a6h|DOq?xvHxP~lhGQBi?z-BGl~W`c8vs8v-rI!C9sUA*`>P>FcmZ@-mY1i&3`vL z*X-K@Sh~#BTX(uIW~)zSyjzzvC9cD7R{!R{_#V~%FGX{G0~h_H?K9Qc0ps?&Afjje z;d#2yT8lV0d*8TYJh8wnSobg0Qol;o&R6T>?5gU&)!uG4s!VnZ^Q}+V>Q_0Rq7)!{ z**B2)u&Vyc(E2!}tEc1P9?!}FWuT~?f2Is5$zAzL3!PH;?a$%W#My}JuK}Urey^=j zu2U>lFa4gs>!!FQJ=H!ms(P}8=GG_Mj+OY>Z$@&@OKQB-+`Fi>-;3gAxzA*8qqpGa z>p@%2DwedR*zq%bL!w+Kr-23>xdN|!lB<$uEx+@C#u8a?mVM{L zk|vkRjoxLl-da(?dmJ}W3naZJZ;v98gVrbZUS4RF8hSpF5<^fRzI~+_K9V-YDVu@p zu{|koR=jB=Zh3`x5;4c}93W9&0OFtSh;@psUYGJ=2HF}7Db*5)b`^4^K()kN^f2_> zvYrK_p4Q19cG-V{Owj4GZA%n5thmCYX^R#H$_`hX2M)ZMf3qpe9QNrtH!D@qW%QwG z

gb(;8|=D0nDH?QcK*EG_5eefrWxJCV&pSV;e*;}fXn3ZsX7k#&k;}zb?_Q9o!I6EPuu61jv>~M{_ZRD{hD(NSazL(s6gly&u9=34h z4{x>dEF<50H_JDjt}pH%<0>jK?`n=qD7;y;?C6KK*h-0lRDo*u3-@jINm}tGSfAad! z=y4YywOmrqqom1Q>o$ariK}`C{jF+~R?=2_4)31`B5!I%lwFmd6BV&UUK5nP!}{a4 z))ZuB*w?zc<*#!M)tx?@Wuu7OU3hb@v`@TAE zHyci_5cfx#`f8gxqsl0?cNYTb3G^mBoe4^Z9P)D#m)KfRVLL%pbWsLRLdLCy+#Wmw zJYC*7xnXm}xcgK(#orsVn+Jp|S{!z)Y^(ix%0*u2F-j8AUDselFmT-#``UG3(^P1C zbZHQm-e@E-+G15o$Oy)f$Kv+tC2qn=N<{7%?xcEZ& zm~41Z34$s$tmrJe<5y!kIBkRJZWkqjUAFrjVGhMeZy!R130)ARab)Y{jPl|Bn&n?# ztUX;4nE;~Hm|L^fjYm}YDJ4w{zDACgS5b1TroC7OtB=L?2%W^Op)X?VX4~tFVvpF` zRciXyrB%F%PkOKlVgdq@jYccn5_;At)|2w00cpJpQ!1L6^aR$xjIiy!>+OOAC^qDn zir?yuK8Y*Lq|;=utQrC#Ro%t0nw_es2z^WkoIVY7)R{+mV?rbsqjL=02Xf$aj?NaK zkEt**;EiISqJ z^kw{8L`lk8%%G&)Xa!4PeX(CM+mh_JAxV=%=<@4aHhfZ4E~}>F%syD5h^rs`?q{lS zdbHW641Mbm>FvjQH`_jO{v(=7Q!&^K(OFVAlP`iwFRVX)Yb~5v=;R-ry6XJ)3T@H#8LYqpnOY(H<80d0AN?$LU|w7z*tkG3l1y==%?sk? zN#FWc#hZ3jEw3n2p0VcGo`cAbDBnIuFWQfcUSJ<47W{(ehTKA-pZ}`nL`gg(Wj|!G zWO9HMZ4Z#muQp$Cq#O1RsyiQT_HwK?H;QcZ44%v$|Kn6kh|VbH&aHFHwjZY|x`3Xf z!xk1>u0;D3mB3rhX8EGWcNK=TYp94q$(BfhcLzu!#Y^P&*Ma8^sB>w1GL?)U zg~Cw?x?-!)2?J4V-FnVE5F55)_dI=3FZOGDJB#>QKhMC%x7COH?kbCZ7WLoF+;%&n z5<<${*nc0w4{*o}?J7;Ob3Lkd=aj_)LIP&mS*@{dd6`EV+u3^4`5B_*am8;+zE-C{dyuBTf z5WiBc0U=C$F)G`Ig+PGJ-U&t8X8FMi5@{L2Y6OcgQlfnWplNQ%kD8-Vbf`r(UXt}@ zphxL~b_f-SSAbcV4#{2%10nOSID%|WwgqGrLcxTMG!uXV2k)vMgd*(Xo(4}Cl;ls= zA`m48CHaD?AMno6mjp_@ScvF99!zTKX$oD~0$`GWM^qx7 zN^P^c(izo?y)>z4XD5P^#F19@TP!XT9MqvUhtPL`sKiE&TAw@uvTO2Th+#l&gTiC2 zt4X$vvd6gY$b+DnDRhbE=L?R2>Lkbqmx~C!AVlVzy8QgPQK`n+HloBN|+4?@pj7bHqB4v$1k+}7FxKs1T-uP28% ziT#`aJi1hFTj-UHpqMv6Av!hzY?)e}wJmR<>vfZC-{4OMB(po{WLgGKpwOGxfz?9P5lr1P(ad2}3p=ONgEZLL{m}_pxBszjI_9oKm1Gg1N z_?-H72>iPmM=<8)z7O^4WPq5gR;}u1E<#cpq_$bZwZCZ zO#Qg7dKM?}6pJ7zxX3_bz=4YAg{=VC&>O-VrQt)Gz9<&ox^lq?0?88~*8R?=RJ5?wEFd(Y9KaDV4=KzD zCniYsaU6zD;LQroZlD-pL<5-yoOu!A#bfphGR~+fF`G^BZCOi!*Ez7r?{aV6ye*mOm+{lG#4XI&o zQau&xRtg#EgOhRWAGkgg?yLq`kax`?-_V4J)D+nPlZC&?N zTX9L~i_omHZl!P!U?w_m113p4^AH@wwx$UR%V4ZOAHW`m3hLDAV;|hNxx838JCr?* z2pAj!!hTgB=Cm>NiP$4(XKAxN?@$TT9WYEJ%%31RoHG6giO|Of)D#F0E>=cvX1iv{ zC@k*uN_LVIbU5oKy4Ib!1{JG1fA+%^JG085g%ydhy8GkQsqT4U-Jab|D=Dxh9D&N* zF|Nw9x`{2&CeSUB%RAcn0W(Av4d>!}Of!U%EB*DZ($d;%2k)M0>UujB^|RZfwVi4N z+y*5}f}xg1s4Ng58lbW;e}c+jEVQzeLT*JE9G08IOf7EF_4+kV!3g?6{bie7UW!L; zA-F{e??ue=pXR(d?@$GTkEpu6h|6I37>Zk%HJr;#14&lhVh3G@f!oKNBF{WKsPx?I z)}mCxL{oIm7MLt!t2Zcr33emUuBY171fbnJG)MtWrj~A>)p{Y-C>v{%DYQcfYsESm zQEd$M(PBgfc&aGn0*0}{2x28-Cy;5I5kO-=W>bB&v@&Q0w#3xztnxZrF${q^q|+*Ez4O0dNv4n>7(MG^V1|cabU}s@%3II_U?Bm9C-C`SUXpAF zXNRQ?4ZzW~lOCh7=o%ryzp{jez0aYtf{nRnG5Y^|iGAh9E*NHg*}$64x|JHC0X(9! zF9K6~u}gy~_OwT+Z7?-Br3%#~)M4!c&;uGX<4z$DA*wQJZ4RxP_a#7C! zX^;A5 zHWr3PNokvn4p2>|ta8*>jEj*bCWU)?jR9VhqsbJB8g~n=Zo+dY}vm;q~29b0Mg03?^B&B zn^YQX;E5XX5R9MpoRsZt#3dCLgC`30?$SAn6I!&UxMn z3WoiuZa9Ne5bocy^R&AGG$eE>G`oriEx6gtK~FdgV2GD^=5gVCQkLPiHyY~^=t*n> zL%GXeD6fRzLmxMRIhYX#?FjnER(Y23Y)8XA#78KHvE6T1X;;MvI%F+Bol`lcuNijD$O?>=t@p2rP!4hx;Y zIbeE((Xi>6);T+DBc=!7XsT~|gyIlngoXz(J%G3&rf1P2F+EJ|hM1lM^RVetpE5ms zLQfaVwo#)r;vK5X8>9zVFqHsBT-o+ydhCOG^c>VfGzL7DT18*FaWd0KJya^lbW1-- zT|bGofmFd6x8bM6;}j(8B~oW`_VHvjG8*xuxHxcJZ@_5bvN{Ib@W>!aQ2m zq26K9B=HWw#v$IpVt{~*chC`}zcIM7#%+}s0Ei+>s2;EWK#llVe+fM;BU2^fV}#J~ z_CoVvyuCQMh%)T+SKzrF*Tv9+S5R{@W&;A6?AWt)jH`G@&r!|NB0=?hH1MIOe?DCf zaIiSwz4QJ9YDlJ)7$y^P$KhKt{>7;cPX~b=o!Ss6UDq@2Ez+`4H)UtoWzqt{W+!(J zuvw;jWP>MmZ6$!fAYAAG;Xsm+;t6)c+c_DVc0_rpa>CCg9U9jIzYy40uMJU{S_3O z+Z;9vZRuHAL^m;=5tuGX2Bt&!w_Xe_JUrNgZofqy>h@!;5vJ_DeC`Ff1#)f0fl;3BBP->dMVUmS+nS@qzKBp9Jt2fGk|c+ta6TLzce^E4w0$89a_}I-=***N zXU4p=xOlV|AoNb=GcfHsf@u|RzOUONkY#Vn^h0gV%#3DKk<<*7_t&_>^lY{u<0bzj zdo&JNu#mmK^oq6dSg! z<*5$YxC8_HPBn*UjaxLGUeG*v?q7m4kG`Q{8q&qO)sM`YR)E5E6$S$e2B*;xd3WiWd@^iIgwyQLt}UT)8q6@+c~g>HnojC4mKOrQTsmlX4<&+w zn4a~4Z2|V6$fAdm1pQJ#jo!C-8d$=qb*&MmMAJT)20*yL$%qDQGh5kPbU_9M$)ks( zaH9|KFgtW)1c_SjIHGczXW#?>7yWJPW1*Ep^ErDnI8}~s{ee-gmQtgg{%EZpO2c~v zT|qo^-O-ootix4N?wvloSKxx-+>nEjrJT+>nZw~x6QmiOA=0BQ{;qd14Bt~+Vp>vh zcr>*y(NhaNlSfuAfX*->VRvmRFM4YdZgZGAxjQVT^#fG742FWZ~QRI^*RPXr6*^FF}2eZYt6s3JZJ~ zMa=`4=HcFLsJ3RAX=}wwyac|Y6C?sHN!%eD|3o65vSGXiUZ+EtW<^36F~cJR1FWDu zQwpaB%-~@3MMo$+ka&if-a>a4CE};$Jx5;-3ypU1JaI5=G^H0BYTZOb%uk@M3UX%w zGoEA8*EHj(8SwA3eC zE-vJtl71T6tZ17}If0)cM2HVxUW7yU7~Imv_~`C~skX!kU>Px}%|ILaP7c`$)aVBx zHO>kOL2=n2q=pd^W0g{56)rkO=PkYf3Fj@b3WAI}8p{z}&W^;$a0sqhHViUwc%6Lw z2B91Qyi|Vn4s<=81UbTUS`II`jk0DnhJk2Y4B)aEu40g3 zl?{_&ty?dmG1IX<@$+!23>OI#Aisuj@@t}KWez&4&*NL?L>z>I+?iw!tWs9Z#Nr4O zpl?U#3ClLrsHN|&!%z%x4nUH^C z4Qw)~6431rT>0R6U=^wp&|M_x%k{N<4)F00IO_m-lT3`JbZKfwPE#1;I#+g6KE;TO zLUAUZ0V=j_mmg$%&t$SjT_4R#OM-iQV7x-*b^SY#)Wt(0EK0FR*r7u&R5TK^AfV&U zF^ezvk|g+ujNq|0%(ZA1PZ6^r=!eb5%%K5nVf2Tx89LxnpVo%Ok2s>xVC_sRs+_2I z9k^paVpatG^v(KAL6~94e^HPuYOWSW7p}EK=4!;O-pH(US&DnJEZ`z$g?oiyR;q?Z zZ%S|{Z>(9vUg3-%SRh2qipFaBbTb2Q=xP>kVY3Ecvr_OMpIGFUWgG(c#H=VQx6)mP zAu}^#R=D5@W`$-3GxdC?AdFf6i-Kg4JCG2q&=H|-@P|;K2jwvIahVIDKJb!JXGc?T_iw5D$wo|2){%OqQP7#h0-UWIuB8mo%B;Nn`hXbjw3goFUdjog1E zrv{#)t!y^-^$P5IixA=7euSXIQ?%^9onN@t6;Lz`V6@itlAq}cOMi+6<~tXZY7L{h z?#C=hcs@qk7^<@km1cAtOC_^3sd?!gYCasreE?8QRp zUXn(`)Xlto0UM;{O+Ju~H9Xf=F6(}|9V zmOza=f561d-fIPZmGcQ6sddMsu2}TIV=}p6D=ElWIUsozChqIK$P1tN&9mdNaHsf3 z))&Qza{GpM{<>7i9OT|HjC{5y4X>zF>8W(6Pd6V|3x(N*z@FbABFIlvZ zpe#KrKjStelPXXH&+s+I=PtoxckZr%BtU?esYY(j-X2ES(HUN^gcm9)j5Rk?=hY+4 zqk9h2DDXoxphK^{ZGrYCh57(+(Jvg7qCN3p%7+2?Cf+k;j^jIZzkhlB!-FrT%yN%u z@ZDOPx-a3*?CgavWb<4$H5H!q_6$7>})6B%B!BL zrkBzR>_w%D{dR-BH>N*&Y0L7?F}KJ6J$UuC(w7q4-n6yeFiW#}w7twH^xDO78yii| z{_u~NHmrKV>XWtiM7BLw^uU2%%uM@6)QB&PxjkWWxU@8BYgWd}36<9gq1#1C z(YJ~$wl6rq`yqPbky(KkV#3zTQh(YVpVfYnW_DtR;wL+&j`CNPlRNCbs@iSukyqRW zA=KGib%0{!;Z|*pSbfkpBEo6R%EP($+O=iU5pJ$CjZgY`<-F`GNV``Y8Cr5N2(&AF zz1Zww*O(N<&0aTYgID21d?7c>Jdub{Vb81(OzUVODt9C?_dkxQ8^ZTBj^uj0iFFMd- z!ABt0XEuVrRag;gW(!uUN{WSUH7vs{%&@t0bZ69S*qrtnA0I>?-d`MS#$v5B4^}NV zPYFNqZP<6=6p4)umr|?-iWw6SUUTLGuU&*!SI@$DZB~|GwJ>mEsbt-Scy+TlUVE#^ zN;bX0{Vmy&zg=mu9y~a8kI>NFoyrbd7Fs_zzlXyGHj9ltEB#x>tsjwnnN^uI&OlAlLR*fNSlEYbnj+DHOAF%OE0(*|xDHDG1i_JhLqwW*jCZ5O)XA%M=Os178kdr}Qqt$+ zCxw^DJ+3`8e$e+e4(|FIo`VKHR&Z=tgKasdpWeL4PT7KOs*-Y+T{5=7>|?wiS`Lzo zLla^wa2jIlbjKbD>l5FCESN{KT(C_jVuU7CCLVv9%2094*8c@@-Z@TdKQb6eTT{bZ zp|DUp9itOKHbnR3{KW-pFEc8+NNQap^1fB)4P*tQ2TI2i`Gv~KAtHsHb z_H?cRQ=we*k7y>>P{x6$ajNN?x&dQ!kbE2+ z)3zK%5whb2A;@5)fo;?YhZ0R^G0Ff$xOO(znLx;fBgPyGIExfbO{fuFBMocm*KNp8&n`@4jjAO z=FU$$-zp%7grHeFM=6eg!_p6(TMmH*rihA}|Hto}QdIUtST!dfhO=@JPBjsY$q9M$ zW}IEO>ZNbmn{gbKmpa%gOABnfNY=M8hpfC}AnKuH3u7STE}PQ)S@3xTt`J&_^5-bO zlK$GZ+=Wgc@Ii5bbytyG`aM2E^8*XayMkU-PUwIiMdOBz+pvtZ9^_*>w>HErT& zf78r?9E4*mmRd%OBX6f^f zWYhan634PR*a9EYdEbWZg&1{uhUP7IT1;J-GUdOss8Jgv>_cbp0nOCknbg74G?k!_ zC2U%t7PbFIEt=mBLf7yFsuD3Pv;c(WZ?-tfwW1GRHlQu}5=R-7e4xFR?45?>w`2-2 z;nbiMoVyeciCa{{la~QeL`L`X>({!L(MKXJ5>@i{fq*DHEPmn~8l8j}$MYz?zReBB zGD@vCL`z8RObA&$>e^#X9b_m4iM5@9rTMdik5V-umdH*0yESwEQgnDIO`+312^q^y zn8n#W5QonreI+)a;_dKFn*H z+T`PyMJc1G;wqt<2kX|e#nt7fZH=Waxy+s|NHgb~(SRpys z?wn+g7XUZfieL(J{$f2#V{v|WTsP=sM;F7UQ0h1rEWI50Q9%unb#CUMHf&NUd?0NS zM|72x>Wlndgr5pNOQ_-5N?E;zEJE31PPV{TC`#y~tGFbAFB8;kG$v5%NMR9H3wsm} zdWXdYtKgtVB!HRn8LXz#wIH>QHDLlB9GvRiS6ZqN13OxCThKh^c!gEkdnwMn7*l{s z8XvrjE>1zqz=65?VUILN%a|mDbU*Qka~#lgn0l%Vo5*3n0j!cAAj|;0IDCdC2 z=y$4sEzZYC>1iaySz`pTX$VpY9}K?#4h;pNhVw!|Yd5X^kOGhTGK)P95VGo+rgr28 zvs*PFI{1Q7{34EwNN(Z)5)%-1W9r1+D447CldC~_yCq9mocIi#@EW!xH^ghdO#P5k zlVD*$aJ+Fk(vkq^!LHaYhw2x@?MG{Z~er#+$4u%BNrt7MTVsH0BwC_|j#u zEfjRbWgCWAfFEfyZ)40n6cy4@cp}c8)}1Zw45CZSYl8sw1yF~fhQgOj-YCb4`E@b% zGYvp#R z*kej`lwkyRQoWlS^aNe9L5~sG9nHxoPMM(3ieN(Nc2PV>_XU(xrL z&QxnddcsgkEK)X^syDR(0Q~^(wHY6z@ZJMW-Ic}R{8Ehk=lYO8_hq+z8d(o`|)Ve$-t2&GW@zjGUF10Vl33b)c)(f{yaix=DxbnpuwC{~SUfdi;>hl}?RB#a0f9BdnC8G{gCyt+Ev1asmP;>rsJ zMqN`&BWK|{++69`1waaNI8up}NHLwlcJ1^En37!7aE|yPtI#n=aHA8uR{=%V_Qr$# zI6fqf9+9}xFhVbM3>)L?NIPGf*h5xu!G+Dy}bwFYm zMA3Bz{OvUSvp6+ew;9BS-TELL166pK$qr&L)1y0jctu|x=x`&&ZVv(K2=gxgp6c)b z;79Uo-zqrA9Ge4!Na8+iQ;Cv6K2NWrp>Gz|oldqx=*@2BW_}Wdp5KeGqVUrYcw}{! z_sL7_L6u+#t-TGogHtmA1&j_!Wk$}#gJ>HO7>Y7AaK}iK&eQ~ihV2V)`Bv?5FMUhj z?!EC)#Bj(2BWwr%D5KDhL6~wmMFpTA-QvS)ElY7;$7x?0LWc8wh9DM0di}&rBD6Rl zHw}*vFkDrs=T$vk9pwbj;g}{i{JDU}PeWi94r$gvr3i=Jnrg#0d6k}kAi!oN3%;z0 z0|1CHpK#-PZJ%l6nNHy}nY^>)2*%(maYtk*cw`L(gu(BqYeKI92u9Ik_84NdtnJc4 zPP@b4nm-Hw5iJO7b>nPUjlt=z6xQxSPMrwam*zd?tR+3|*P-~R7l?7z;8NNUG_)$@m2z781Ygn!igY>VKZ^F^)`^Bt=*sPa!(8BlCy+xh-$9vK zGY9eN0WmZ>g`Ol~#q|6QLdU;CrWHy2d@|Y3k%oqaeuYp25)AQPggu`1Jq7tVYv^g; zQ$sU1C6uIWS_#m@VWj3LN0lw74Ppq+Wy=Ij#_TCjgJq#GR&it(jOsQvrm9`IQHtSQ z?WLxcC(M>W`0{f8k^+A;ph6?Q<)*Dl`?-VaWjpB^7A%>MO~^K!0O(?o==cKWfkzNH z;Pj#ic4V_0=xJAu0)x|L<)UVLS#%eS(2&r84#*h)y@)VstoG!7XG<8JG!XDf3Fp76 zv}&Mm+V6X|3bqYunKMU$nZY*Zv_1hga>kD249u2QH2)`j=~oC~jY-WIs$~ljt99F( z{N_@vUm}qB+ps-w4s1grZ(Oe{IU`c8Z-U`C90X(%8d8anJQ+RH5K}5ua2jq19A+cT z+uipyJ;F6K33Y>7mBJd+ev%ded2+beKnL*7>Vs-&u#>?utV6WUVt$j4DsklgAb@k zV;X9}1rHwC-V_3mBxIRgZxGcD+4Y8S=>I91_BIQF5dJ%ZFBiBUK|rEiGiM>(@woqF zeMM3W+!CuuYOElGk(4+X3!d`29_{s6JB{dKBc6#1>3QO_apBK2m1pC^72#cY3hLLK zoDk+KONi*gS9ip500S#C{^Z~cJSRj0Lo$=h4}!5EK)NlQx;H+;rP)0p%!h*t^X8>; zyT?H=Qo&)ESRTMp2o8~u+d2_7N+Kj%t`nOoP;);Q-0)(Wc5dPq^yH~^W|f1yc!zI znVofB#;Ma24B@lR$DB?PHJSqv==2TG1g`s0&(QkP0O&@8#Od4}|36FSbgavL+(TSLu0wc z%2nL%F_D^$W?&t-4zZ%|%RmkN|Ax%n@G3G&;~3|j?z=v8ch?X?)3YR=bY-}5$P#k1G-^v`JqaLbZ;$>4 zH!v3@oY;XDJz*qmNgTgdhGZK9qq@J$h(Q|Ez0;?~8~2r!f=-Qn(84n2N_{X02K$x`9(1N!<`#z*foto*<^w9h{ib8+Vawl)y>Z z$jQP$08bS;but8urk7I%VtBQ2eIaiK-K+(`x7VZ~^s>WJ*z@@Dx$vL-@NF0gH~j|> z3HFu2hm@D@*H&P-VC1ViN8Z zILxL-fYiOwV7UDW|9zA=G2jr4LxAy`hH1RVF z;~0h>_yKvkAOz{oozXAk^dTukHw^r)3;{U$IuU`Nha@RZ*vfdm>e_MO;%7@T9lOQa_I28V77sSOb4z}cO=8!So6R!3!x~6~`eb(Zu zqAKq6H4V;nG^AtSoWTP+%?-}r$R5grr?0@Capdlna>!dS4TOJd>gvGvG+aP~MJw5~ z2FJH#k?*gPHOsB~UXdxpmMVUM2L9_3@C{60KS@HDKF#gVNg&v8-jUHxbs(J@TY~z zb77Lt&l2zTJ;?-_axQVA%c+O-@igcS@AF)y5ePN&!^Wm(ek)R$u^*!tfUmm`2H$1o zOt>({fQOkHqg#`fY8N^WjYAhQ@U2qXgmiFomY9Mw0B8=GE+*X-OlQv6a^zEtzG$B! zWE#Z1ag5^n>1&?wuSRjN>(c{2CVJpr>KPxdue`xm`1UHjJAmftkP=Q*(=cZjPH1q#D{4k?35K*ngVFnZ zfp-~@m-Zey`h**yMk%J=n;^(F2-T9fesh7h%E06Bug}0m81jAwLBLpZ3@zaO%w!M+ z{+$~*8|gdd#sE;LJI!(L+1(FZ-$eLafP2oIx9OPo1hv}J#ZnQB{~(lS4>IWoy$E+4 zk5JG>W005M+p^3Di38zGj%0$&g7B2C<-)zMAHDPw#FqY)j$BV9FH?nGfRP4H+T^$01HqDYXKC7ur)%cf-MaXj65=RkpuX$l(P)cFdnKfez!$thF%_2dfH=4`kGc#fwSuErvdT+ye z!~C3%tmnu}=Lx+Vq-JQl09XsWizlgQzJ+%J2gLEtbU@BRIh~nlKdtqBYPQE!yL~D> z+rtA{Y&}4A9P0(f3=aGp2RD3}tD#t)1t|M*uYJOcY1BJ&uwlScRQnjqLxb&su1pSg zGQt-3)4$b8oW>HZ^Ob zqN2t$i!{9V?zXt6y?py6sqH1(<0oHv?4+*V<=kqaS3c4$pAL?cuKV-9`3u14yhvG)wF|2XZn+utp%>6&=^izC(2 z;qaO61%-TvqiE;!@h+;3ekmhVmDvy0%s%yx;-eLZ(;6;2jaIBWkAEEHU-$~If4`J1WqZCWe;~!WxbB&+6)~bC?lKRj5N|%ReW6MGR^MhjwRP-Oa-cifnO;d!W zM~_I)iAX=^AHBP+_8!)5B>If}8S8}YRPUd1-ak;5)V4Xx+WQ3R!HV#=gCl`NNPKi^#Qx?n}SXa)dEIsEYqE=9eS$=j)pv zJ|lnh%x^Ko{Dw)zK9>}j-yX#dL?9dUG$D{oU#zP`%s;k3h5xV-hD>3>jaH{{f#wAd z^2a<1Z`b@PNlaC3RMg~cr%ujStZ|}ZjH_hSm1J#OPVl`PI}3ek`gRqB_@r!0UxBGT zOzRnc&VLu$YZ=ZlRmac!uez7>4tA3u#7`O-_!5}E@x!oF={MZXkKk>KzkfX(z5xYF zT<+E=J(6IH^!46wZ?)c1^#V>w7Wn(o=o>Ib=lC#4Hx>{;SC6sV?J|T9p)=Y8lx(tY zgWZP3TBPqI_>2e!u_$RM2kXC%NQLTK|Np|O$iKw#xvPquz+B+(zVNM8{V&z$T!7>} zxw_@Nf9SoO1?{zy!vovL97;cvEibe)^6>BKc+5H|)1&}CgNMsvs$NL(?EB6^Q;#0A zvq;yE)*+;v9UvD4I{on|}eP&G6A&!oC)um*2$p>M9oA3#Pzh8b2o@b>;d9HDjpP0Kd;QQCY z1IN&Eok)f>YG)DakRQc4JP0?S#+d6h6wdd{ZMcUA;Re*`c*q?E@epz*yTpY#L9sya z@OACXxhePQ&4H-xSNLC(d;{kVVYZ@8C+<_*@H5lj)F>kYYYHi1yfT-`M?-t5Q|(!T zN#+Vd!praD1KFei9wjDYVh}_HB{jFAxEUYY0oLN3ou+7Q%bACae<^yS#R9ZF$%DSoab-#SwI>tD*fbWe9aydCVkk~@eNgo}Mnc(}n5$W&^6&0tmO$_W0!p)fV zBRqrrSkuJyBj&cZ&##xtgh2c0$bSwgy5<8vK1X(rA2CA^g$f*wwU|QmX$|X<`7A|z zWK^;&eSXG}WnxoeL(pghmi5Deg zWJDX;>P(hJe$~G7{;~7Uaniey%FabKt-bcu@Fy>_3d8T)TnRC1Nx~FdWJaV}cYZ`^)@w-GXlm%j717ycO?ms9FLU^%sS^jiPVWz^1cV zEd#a#5bc}%bP7PWh4U7oRX=96*d9-RSS)++AwXb_m1l*Ac{FlrwkS*$d>(9#eSjgZ z);z-x63ZT~d6r0e6}G~v^Rh|FvM;R0FGg?}V)Dd}=$EQb+ygg=n%jvhG1&FrvfU;5 z^SKD@LWJvq-M%qxijr~wwx@1Ba^L#d?4KM{W}|Q%Q!UMwTQyHj-J$_tL1=ehfv~= zP)+m1Kk%Y7MGA(f7NDLW@pGKqB_Gt(t*hb3R5{^4*f(toohUB(=02aCR~L(>H;f#S zyFa>o&zwc~zx_VmO5*w2q%U{hIClKtKcb@BUiszBw)nzMJ4e~S|5!8PahfE$KD)}Y zy>>%fxm?`*ny~7FxU@Yx9K!=gq^|(TFkGV@^`V1nc1odLOqHeomO;r}aeMxRuePih zrMTd48Xj1Dermx4%QtE-Bt|FH?5aAxQ(>INyEe4|EpJ~FIyK7q!jYx$nNC+=SLTs) z-v8jdg(8>a<-Ju4K0W6DmZu5&4CstV-#zA=Z5h7&NW{7F;eh*AoBM*6_qfuGp*U$3 zIZ&&)9rM4?I(gZs^ib8jb8mO&PZ!EdaHM3Wq(vH1bzbHfno$+o`vAy630goc?O2 zG=?_QtP3~B9a3~DawZnotv%KicIWKZ@|;hPEq}{1xWZBMvPaSdf7@_|n{9Yt?vfVe zpP^%<{=X~{e{|Vtcw~DmUgfp(mno?=73hI%%1-Xapxs-liPgKReA{b}#AtywcTLu8ayzTr~h5wO!xf!2%gBE&$C*E#FzoF8A@_C$i@k&G}XkKP(E4;JWU4`b7p zpLmuDRY-$VH|sB?#ebCHuf{^(L;TUQHMA8$g@CxWaU3ferI%65F4B<(Pxx;M%kZE6 zs-iYJ&SuZIpy~@`8CLAa=!C-D9aR$`9Mcw(a9lP@VH_SfJbmW9oY8EQj4sG^<+@|N ziO1UW{&*o1ZNt;&wJhk%f4uIZa?QVxTa5@2U_b=o*+xPj4~G9K&q>6gzwF3hwDsEi z#uZZwkQA(P@T=asj}#^lYM3MAeB0fZaTuPoy7;3$=b-cCrt{U^A=jcCEv%#`k+ zf~f*=*Jt^b3R$ue_HMAJGzIp+a@AEujuDprj&jY4UL2PrR7T-XhI{yzk5tvMayb%W z!m6)Wo1)JmAkvw9q8gU&n0iy+@UY0FH|mLMz;PwsnR8$}4_Oqe_BUy-9Vr|a5ji;3 z3gsP$auC9c&0i>B3IvfmsuH`t)ecvv>G&L3pvqVx-sNt+$Fr&pXM+3M+L2gC>kPRw zl?#CSrAhAk5sKsjrfgtghH0bdgpt@TuUK%e3&}Cu0~phhOmvL*torz^>Kx4^chljK zpdMZ_^{r9cW2e=_S%=&J@}Hx+EX|CG`C1J&wDi^wt}o!%Wio1_2j&B_at+P6D>!m+WUY8 zd~8i8DP(xyw$mYhF5&iK^`#d08VSJ)4!_=+m#=6B*6I9%?_{-rOHp+!jIXNiQfG#CIBxt9Y%>}0%xjOM@PLb7`z zPI$=P=xf%H*Ck~hb?5z)z)0mbl#v!eR}Vfj4-Xv4o>U{#1NDuxtIDpu7B8gt@=!V> zU|#|LjDdwzQuOgP@u+(V4o%75G+JePe5lAM5(uMZOd5wL+^`Y97A23Icg}LBNO^(C z0_*5Ff?vxhceGCa*G;TDCIj5)h=gBrzfqWH1z!`c9K|0QWZj!G96FC!BF-8+uut^H z#1}ohVWZ%q9xMJdGeM%|&Z@%@+OJ(uI&9R)yRuUn{1@zp!^#jf>HrRgtcY!iv*L73 zsH)bqKy?}dKzw|RZlTdvTOge~_d4>e!k>)sh-5vd8kO#N>gH(m?;GjF;tak+pR&;n z%a4LnG`C3P!ddPI?9ivQrAkWS8HyWq0^_3-WEjQx7BNO~yZknFl#`S58EcpmZ#-xY zjI8L5RO9d5UV9t7f((V~hMc`S3Ky9Cg;m-yP+-Bsrfd{|IX1@GoZ+o7#brwE;`4(j zoUoOcQ<$+N*-B5|@)V7PMj~FJ#Z5p{o|3$CV0R zMxUQgMtek}(4_3-Z#G=>G6>FVuQjFw$8{l>TVlJi%A;L~o&+&yulOO(WfA2l?&t~= z9iLCH;U0~UPLRogiWzHi9zKV^q6-M9XQM}goy@|4C1WRJNc{Yxljy?}N>LFidxk3K zUvA+%mM&LdOG%+NCX&+u4mN`d!U%$rPVyRaJ&~qsB2~5KnBC*BQ&g@zTIi@&1h>QI zsu$Rx8w*FNg>z5-YE!BZk46r*4}UV26?`ZqVsK1~Q-~*aU0tP3yMu!lm)ViKs$_^1 zQ;EP6btEw9>`h5i$k|Nr5Q!69ieY2`vJhHy-huVORK7q3B+jRx6#AIXaoLD>9yxSy zt@58lVzW0U17>1!Ay^}jvkMYm1Y={(Xd_)2?5J??E>ExPk$jd)Z3A%HCN zRh!$Yl_z@Flsjs)eUV3SWxvrELsgL=arx&JLIJ`gDLcUIW2&u4;p4B0@J)#UG>euT zIjY4PI*o)dx6PyrdLT2!Tgu95vAhwL}kBjjlHH6wpPMg{@{}HJ}6a?`J>i zR6v0Yv1^pU-vK3x3C(G%uK+lmo5raHBqKC0DXcTnX-;*elHtHWwv85tRkAXqI*@3 zdTzVy*Of{lBO)|U_EzZDs*_ISiG&07S4}KZJfsnWO^@pR_PYpp=@riW!szfwVIO>8 zA@GoU@E1uPKXx1(6pOE3*e{5V5~|($x>vM|91A6my1>DtD*hsorY*aQFG}J&Hgt)k z1%ukEe@X^SK3#6~;u3k(8wb;d4NJcD!mv-54;KPZlJr#91kB1E# zwtU2}VaD+P>Hj$$gMJfi_6Z2(*`S|89~^G^f%jL#hYj04de|^i`YHJTr(>qUr)xh9 z4%*@qv_lc-l!GiAg1tZ89K0!%=e22*p{J+p z3Qw8@PtJg~uj)O0b|mL%@8Hcoh91AY^q1G0;IT9C_$0l@Uju!@19(L9u;9)9>w|;+ z5eb7EPj}HF@OlQ;PjbMn)t9-U>*%;&(${X_c**5Dp1`V~$3BRh9 zUs?|vmh)Gbjz1Mfj&I^bG9Mg@05RUE(G4W;0F^u-mf`e0$igG zRXuE}Yr7mC+5mo;ruT5!BIe=HFMWKrgiJ+NBQbCS${o$8#C&-9C8BI8m#yOASo2%AmN_ ztya9P^UP)PimY)RyphI8NU2o~AU6^1Van=*P}Q`vig;#9kXT&VezYlRzCi*9I+g4T zuI{}#j4dv=#Y^yR7WnceMAf6F_$ts(`C;&m)7d6x>$*8>F4}-^0n$ei!~jf3=@j}U zgi>OQz(@_yoVNQ+klw<<1!(7Stm`|u2kQUiNiO|vO>u2eupK8ScCJ@voqglPp7_jY z@{Ef6sqgFpwTz-H2McEm0=Az013(S}3{3fdgb3r`3O#WrM|TTHcO!KlXA3t2CT|D( z+O#Rh-z=ySL6o;`vPcH%8WJbPi59U?A7B_tKO)TZ@^>Ge^1`FOYrw&AxuDN&xYb{n zUw73xG=={d?bg3<&X*p*GQ{Ve8ksv_55R^`an;qiBEi8Ix#1&_=K^QhHH_-4`0+b7 zOwjJ-6ml`Jrh9ao)Ii#;i^cPo{lhuk?$wS+V>%!_9Ex9V-<(TX0i+Wz<3 zwpu&oPGwSUHJUw}PWM+7iU$iDg!w-0KN~3~KMFZC!PJ2a--l#fkiHWjM!aX@4(@r( z8&t*d1MzC)2Vj|aM6E3qAw2`OdvF)5r6uVWGpjmfUF%ft!6{d)jy1YgVDQB8-0`&0 z$#8kRg{GMN!_Rl$IBmO_De7v6WhLg#VrBw2e?C8R5ZHLV6vjt%<6BGckJA$$t6d#? zq0E_S((m&<4{x*C*MH;+wy@zqIc^r&M}6j{65sRtpHyhhOssBiT$)k098W%O^S(p> zhbnL?F*93mFfd=}|BWite^i+}nJK$EIlD2NI6MD`r@T2<#D6?R?)IZM*;R%8_=P39 z2?gtcGNA!^VKAPz_~}O;%EwQ{EU;m>1{%l9y@B# zBV73$O}if7Z#s=c4oVYRr0zk1qBhPXC~WJd#hjtEbc3JPst?Z=cw!>=xdj=Mt+o7n zfFv0FH${NR2euZ<3l8AG=Ihm{?H^hP&@g+Oqm)n9bF1{WznNI+xh`G%) zv59S;nq=;Ix036jOZeI`cJT9Ub4bv%?`j=H7%>0$&o72=6Z6v5Eo*-cY+A?brLoDr zLDzC>r$WN8Ifb_n5%+kUl#C`({($FP8$IDE6?JS3Q>Iv>uy6=~WflC0BM(A7~WqrAgDa};m*H}3`R-YwptV&k|7}z)Poj)^GWzEZJ`sz*Zm>D z=stBY6FvRj!sm-8e6E$3NR`YcJVoC(+&Z9SFbu)-2|V=k6?^dpTTH)1<#6@x;ZZt!Pe+M(R(6JKHw8dfr^uQNzTkxg&hhIXOom@c$so zW@S)={|{A$|8>9P{X^EWjD&&c@KFA5Ka;IDW6Qpcr@U3uVlHoJ4V6$4r%;E0k{zdy zk6Z9iZNKX79hJdgsHu^6SpFHGaD9B410*E`0=M_Hl(->7H8irqDBWVZ@MKvQU}#O<@X zgd(&Lu_YHJ(y>lYD8b=`|M)c@CFITgVSpit;;YIB@YjPPbxZ%x+s1g>(MMd#E&YwX ze`yB`wi-7I+12KsKDw$|xVzgpTDdX*f8VT3rZ$cjS`LmwBuF3q zYR*tX(^3gb^DbZHNcl2F!1WYPRcfr$(+QV23?NGKD$OrUY{JNlQYPiJPvwENmGA11AJdW8o-)nXKG;E)P-o8idRKsG0Q&-QRKAQOjZQ zzVb015>sAvyp0)Fx;k8SwjeT{T@d%BA?dwNnrDhc5(TN)pA?BKphu~Q@cfVv6~Wpy zX*eLP4fL3>)s}t+ijEd{wj&p@!F;sP+vh)B`aDAN>VDO&FgZqSj49>E*()tTX$1Mr zL)PA|;1y)OLr1(L6X6ulTnmeQ>_q?95EebXwX<1r;q@YxCpP*I7qyKBG~E9ZH|^i9 z|DPoR^S`-pvo>+HFjsT`M~Ri&f2l%%UFy1a(}j`BeH8wtOKfAyLq0n@b+~tzNGTd! zH;9>Ay$~WE+7z`z;p;V5j|5d?)llXs8e_?^{nt9>MP6b$z1HV`P(P#FpYiKh3GF?sU`gdqKazXm7?{tg2(`GQ&iy#_OEXqs`0I*XKF0MW@Eetj5cn5jODR z_3COXeMzEAezG6y++E`9uymCnmGR@;^0Q9gY0+GhY0p6kN zp&By2{W7$6;Pvbk#-TcX)ggNHp9P4r9qNA$_`RAxO?UQe1G+-EFHPq@IUI%K3gwoZ zmi)CWjT$xF!(@!ozsfrkY)mH8+)yPHm?c2ifYU1|uKT@1k&qeuhi|4tgR_X+Q;0JzW`1U>tU>v6q5rJ#&^F zoBa$+k>72AP7RKP46$GCOcQOusePIKqD|KpHa_$la>;xw(iVDzV>X1}@|crMto~yA zpEQr`OUq>~EhMaFja_ZTLAyC-6}Nemw-iCAm}3D_FSc#WekYtsIkxnAly`vNN4~Km zzsXtTzA?V_Hzfc16@MqbCid5PS=EdY4!O2ddER`Z z6P4YQFdSDLTX=lElfhdR4iU7GYNz*~ju?C_cLw=8)KrdA0b$*`r0V!@&Lz|eI+#;r z%ttX^Qblu?+?$tNHr4v&OQ47ZpROFjxL+-YlsYdOZ4m_*tXfP+Gb24B@7KQ=nqI_o zu;+C09iDD2uKvc{Coxa3O+8Jr83>i*&wDT4t+p*WL$%SStdXUol`qzN*~XdWaev~tyaZ46rUE4FP-*nU>h}Ic^CSB<#!S-{Z*gVOq1vXmQ8Z3*|WW7 zj4|6SZ)-w&6+8KC?1-&)MfNt2Bep&o^#0nDi0+A2Rn}C|nIB5Ifo09KIYmD46Y}Ww zE}llnj#Z{>TBo{2oWmO33_bTH01hfj`w4VjujIgQV~4JAg*r|(HeMVHw+I{hSnSMP zBofv&bLlT1eDWonRjpnc;^?{NtT|T7<4oA5A5C&mMzzXwuMuM|Cx>)-_-(woM0NA4 zt6?x%r_&HIO`6Jt{3K&{l(1ZN^i$47222Rd=p?R=}d^>41y$M|+KE zWxu-0(bNv)Luiq)NdL36x>nVH%5sD%FL^2R^5bv)wx4%Q*Tz-7PML+7pJ3^8C05c{ zfyE(H(1fLpUH5p5eo;#<*Db;0?Pl=Bkp{4h0Oa>hoxS{M2oFnmNLif`nK$!fSU&Zj z5_xvE3eWdTl9#gAqbgRXY{%qRvv9SE>5F6=-K4!-fs4Vx8(+J8`m2(w)X^Farsy{q z6Q0Em;uTJJdvW^mpG??xex`F;4b`BAYA+c`u`snZ8xkziI)8?>iV1=#I@p z#EIEI4XMQto;jlgH;*~L^H z)c}xhJcNHZPSd`kffj43L4eh1!N14HqAF%&_ojnClG%~sq^{Crn``b!JuXRR#J1hv zaT(Dc!f1ZqIOyG`i_EsC@#9uaTCftZeI&Ad-ldCPF-_ zK&!6T+TeFm%UD_oZlw23Fs_rd;qZhiM&eD^0m{gvhUz^yVP_9N!@)*7!)-IS1dHi( zdch9gC5Lvv>1Fj1`DMD+hD*?Rc&151>sw*<+iLPeT+8|x^g6b;k+~aT!(kW6>@xnF zuHF3!kX)rmNbh&3=NlSk89iUSpF&x~PC!7>E5AqRopbO5z`)L8;e zF@?O+HwAxM>7b zoP}a3?RtEV`k2pOv6LdElDIgzt>S+4lcd~Z`?z8s8qJNon zx%*e&0|#)P*`4yc)Jpcr5>`sH?#`ah=)AKko-ose|J%*3DR?CK2T$5A{#rbUel2O# zDpTex%6X4SkN_|KvG-a$s#}S+Wkm#L`D`j*4i;W2E1Tf z(Fe;38zlJ5ucc5%i@eex%t_CFDydxA)qa{KtlhD-74_u6VkR4f*uyUEi8GkCq2DG? zcaZ#5Da(i_`H>-+GP=6bkr0pgL6?C1)pQbIQ=^&~9Oz!IGadgbOW?Bpdzta30D;F9 zEC`Q(SyP`Oa)NfenEYasHYG}vXw_x0Vd^7T)MRLWKgU%KlD%Xku#L9wBK1_Lo=(k% zR_#HD?(0)|yyB7Z2l?axn9K z?+LEh%yot&i^qniDxB-S2vn=V$)-S8izwZKET@6v$G+g1@6;eG>P`sjT!6t9?Us~8 zg}BeqZS)akc1+PiVgWibs8_6Lo`oV}(bfJrWX4obF25g4rQ`CONcG7%p1^V}FAiBK z*uE3HUza2(UL#@QEXDZF%(eLwtxU?^WRt|-oGG@D8OuL9)||b3rFG+wje@RHn{n!6 zZp1!Fm-@LEc0cK@(ZQsGBr_^T%;=PU#izICqagZO4}OFw-pasi1Svrn;bpwM$c(wY zopGC9Wrud}i{iZaz2L97UA7}mI|twW-h^Krd?^H%_0QK5lMBAwkn+f_X|BsEc-2#w z-)iQGNYIi^`pM})2t|ey!-7t7jpYVW{+ACi4ZRnQrrA5SN(B8&3VXNAYK*-fFAN+| zgF=WAM0@$$6Q&`WHl55AJl`!qBbt`hiwTGf$izW-MVVZnq`EMpfb>hQlp#afzxViwCkGiTK}(O+xKUgU*Bx8K$ucN4|NEj>TJv z7cz;lFbg)|KJ-{4>5KZIY>OU;Mocc)g!Vi?0`g*^&oHZ9fO+ym=4P`Ajv)yQ2%N~} z2~5O|H#$@EjnZe8tul|3kz$LGi%MUlsWa_Mv6EbncLl}cX5y`Nb#D9L`G|}cJ@)!B zF==I$>6H3u*J9oaS~dX6x6YP|04N7kPNd%^KMehD_`_6uN|4AH8gTC2IHHFoLSXvi z^R&_DksUc+qo6F!!L%;5fD*c*Y@voesa3(?NQN9HKsp`du*)?;tFKM8Uoxjon?W8d zx~{!-x0MpvH<|7*g6A&iT?HbDI*!e^8@C>19b0*U6bKf>F7MIt=GJYMRopyzoLHQv zPKMSCMmf|7bx&R$^sN94P-_SB**UhPQ?+rx{hsBZ>OOXg#uDe?=lp7Hni1>}3gbmP z9d1``g{0E1*0Q@eTpHlbe>m#gA|6ySwU1v$L$F33->a(wFQ=iSuX zJaPOgwBOQRR8GQvD8nkkU6+6+lcn{$<4IF3LwZDmQRJD}2uHFv>xsK$;DCqH?|Fum zz7avfZFP;^tG{D1m%xjwh+EZzP9(2(jX?k6h$2p#Tf<%=VBC6S3~t%LInrk!oRlVd zh0ijrrkPv*6nB;AapQ64yYn1}h-y%pfSSwosxCwhRQ<(GHcgxIAm-EC^aR(xbH(@( z7j9-jglQ6IQuaX7o#{I}3%NV-h@y1^a2U>N;O`?{O3JZR@sDf@5v{Za$g9i0Tm}fO zRQ6!g8hOG?#t=Ce6Ve`?2gu?pq8bD`U%6K)>E_-XJ5M^E@_iPHinI1UzaE{P!-Tpq zl*;$x10w68?B!}nr!!y4FGn%WuNzx#Z6|cI%DecEtdSYyxNfql`blb)GPHk{iBrb7 zJ;!)OQ81@2@2KHy}OD6GAnmi`Dl7wn=AoIiaE&vftPt5 zYC?fE3?8d5{_NWUpogdpqfM%J;_l<>nqBM`?e(kmm)teYA!t)7s(CV?DZ~Y)f4A}R zjU%O9cT4*(dC1=Lg)k??F_@RTo@!5~)Qeb17dmG~q@is=1C=wAp<NyiJhD@mUe<&<4;mJWnf49l>SnFji9W7j<~1tFj-pvzR;kt;m2`+U zP4UoU^=PtTP{AMMT^g3rlRRJ7FXLb$+AoZ-Cg_=iSjDH&GfqrnBW%0gEv4`?6Uj0{ zRVTL=RpihlDS|ILioCSS(jpxXFB@@v`X#?qm7Mr@1Z8-sS(J+=C?9_9Q6kS?u!PMp z57wyRP}~9E9;akd-C~gL{W`tjhMova|JBjW=cuZ7sHJ~J5z$>8+vsZ6wE^JQi*1ac zZ#QWkWGp5xl9HD8NtxP_ZMDRX*EU(Ej;Srv`DFGaCbuxUZ z76d(0N|-rui*G2DQ3JJ~<*=@SwQT=5dce_c&Kk>}R}JH@{)`)Xjz*}}QP{L~@(Ff3 z{4}ZJhSaxUma0sl0}is4;hGz1|9Gj5Z;Z!D$d+qzKooet&X5rm{q(ZAAswa!kPH1&T{ao$OUs7K!b0FV$l#j$uiYie2jI7 zmRN%j;EGFqv`kvL7e&$ES%>y!zNiqSh0i2P&wJ_^E!=_^n74v2isG-2l3T zu%;S=!EdT;7XMc#2kKH)SCH+%$I@C^5CrAUZzVF*K4}Cz(c$i2G5&&1<;bm3cj6@Z zQUpg)efzr@j1?Huc*71$OyX&f!aSINMRlC3W zHNL2heK)4=ByKoIbuEOqWd6N1->p)mu{DKlw=Ay~Z1;xCF5i&$whFCHsIlY3HuRjv z@>$3-fnufvpE`G#ax0)^NIA6=6C)L|wOtz4`la$|e$^8ob*G zadKU5k|<1t;JEwqLMvT$tKF1xtcqy%jV)cU>$EY97!w?&hqN7foI_yDh=JQS0WReb`MxYijU9 zf1~AHr|NYA;!(wEhNM;(6GCF+^XGwpfN)S~kHBgCF}hzMe=`gseB@1*fjGw@7@+1| znIUDn|7S6C4aoUx7`b;o8d||6I8&ify(_tiG0i7=u9^J`fgih9=&70y+uKntrsZ#} z7&ji~5ZbBvd}HQa%ijRlu60vF((xe#7Ts=6-1+N-^WlMZoqq%j z1#T>L8Ue#O&AwKHAd@TS3OcNG{tCO_GZ^77Q|gaaFx~G_J?{kT>(*?M>g$i7_qNHX za1Bz`*>Uo443?4o967Say|#8*YY^{rEg^qUu=P5^Eot@+6Vk)dZe57H)A{FO*56Oq zq+95+mXy{VlFA+|DDx9LqHc(x+`0(q$+e~FvmxR3_F}sFu?8iV!6Y;ipzyD2JXXSN z3z@U~IOs6GBgztM(@|9u>MLtC`3!cV&s1;@d$LH>l6IT@Q5p24s>jg8TyQNg0y9)N z#fHR`jFE(Cr=DX|e)*FWW2NA0-TNT$>{y4x#Q=#Z{gsm@u{@NeSuP&>*raoy+!C38 zZ8EMAhM53gwHa{o1cy>4+_x90>Fn}|q)7Rz+&MAAF$C$C=SF>1V6Cm`p&X_6!hqp| z)%DnNg>k{vN==PqFRT4clnl$>J~8$;9yNcXx@Lt?TSkFl6bvd?TYfqoaIr@(%sC%b zN2M?WWHo4%FoT_Z@|fxl(!xK{qj72*RbUgTPbm=1QNxh-*bl`fQ9!M#^*R{OTLS1T zpWJC;!Q0JVdJ)bb8`wwH9nKW54o)j9W#WH^#~_sZY?F-)^Ct-@Izg{(Cd z&4vL^r{-Ud$LM`0Y|g6dy+I;sed(~6z{!kCpg=ou1JdDj)x_y&Gc}L~5~yYOOvi4g z-^%64NpcGXQz3_DZ4Q+dEz)SMOL-tR|4@<6Y@(g`-J0K3mo#TUWaKylD69OOMF4!8KQ;uc2Yk<$tSWmYa?O~NKQ zFJH!>*r$p+p&ndZl{VB7q!!83Uv!jN6AbER?fZC}D&4Xwmz<0l%2{h_seMHzh@y=g zjqGIf>qCSLE=qsPeW0o1FJ;GltV>$pz2Huj^4$wYtXpyw_3-8UyWJGF;4@o=VQ6X5 ztIV={*2G(Y$r?)DTpM*SUvAaes$KS>=*}+pllD*eP_e0d|A(8352^ zb>VmTvNexWJ)ukE&Ef4+6 z%3@Vm9;mArFoMIhy9{A#4L9V(WQ?j?>=($#cNCMepoJ`hndLPGCe8z)RUho&Rf%0uH`gkRU^`af;DUJV%!!}2VF(?9!e=#Y5 z)i^9jW1~W6SfqjzDRxF#fMOIbdn?zusMW=*iUjh2#BU>)a>)fsQNm?_;otZ2vU`Z;5pwAK%4@kuKNOrC|9V0-W~F zWnbg}J``-8DVqjRCPoTJy}>YIVBUzan@^7uvY9hElQCdnir^-Sn<)1*G0CpYYE5qP z4qY8!e?;tNksxs-=(#rEy-kcY_9QZ&R3IuRl&Hp4LQtF&9y5V89tg#wgcZSVE=M&3Ria@$`; zxw^6>^LgfNkW$h}zr-XCnw=cO4#7{dGArS=P^x!VA|ATx#Li%5qs;W^D_ zhYO{pAda7(LuIIwf2~<4J`|hNO-+&C0ts?K;B;kxNU8c`>76C&)jt|}bZl8`Yqfne z04^|WaOfv{>0t=kjneS%n#Kxdi-3KT0SB@|X%#awlrmekXG3UNTBOzeTqHX4;0pUk zG2j=8lPD9#2i2FFjtl`!Zvru$VxC~Ih*jdusip%9$N^o|zdwNtAMBeagwWe-FhAuY zs#x%=5~fB?%CdV<+2|Bzd#Of1FSJ^*#iCUv3jj9FT$=07-s3c#lEz5KNtu}9ERpC% z-br`T?||Vp zmyn%?*IuOSI;8O3g7=g4$Hl@g0Rg*odb%^Sqd&2$5@fOd088vTX*>=i_8)xl#pB0+ zSHoE}Vg)Vd#jZ>+jZF^4{%OUJ)hcN8o79;UfTS!A9USLVcZzxJ61Mx;aZFqFcHzEq*8TJzVGJ&R# z4J(1ZEUReg^P;?I1unI(Jc${CM?V?}pZ>=q>_+@x%IG&H@xbPK5UXn1P z3-1kblRy_onJD#2{$qlII8=nw)Y+!$b~DG3YG-U`Lb*KTB<^mYPN+ynqwdtCtJyha zgdkK-iA)W09zm@rd`g7Y5KW~&R9}NkZ~#JC(B(k;9P5e_A;J026ovN89#yEkSA9|% z-d$D!{eSnCjXr*FgINsI?8Xh5v2umceupRGXYE!r&qA)iUO4s5n>=SwokXhg2w`ZN z#Q~C70Y_FBPLWjMLIsIZu5FwhADRVvog5G!A%QAmCRaX? zAkWW`KAPuX7E`Zk_{|Za%3n`u6Y2;uau0FGaX%+)yDPfb9m^D3`GxqWT>wc8T9;h6 zA{6S`w&qtm(&dKJOvm54z#tpC{M9IRr|k6_?aN}_Uo8w!XN`KLyAHhb8?|s>Hs%L0 zA?_(4uUv{Lx?h?uZvq7Q<->@Fh_-AhjN?J7T7c%Cs#@_5nGPI>P6!csmXehCud6RW ztsl_RE(Z~$-6bN(_NH-+6S0%+Xl3cOn&yLt$azdL%l4_95_^t<4>w85{EwYlhkuM2 z=;62Myop_kXHNetQ*vBK?}iiJpOuZ6kLss;Rv{B)arzd0Ya|SYzqKqyHdo_$_)%x` z%I?cAL0})OkcqCuZP|)3^F25HR5j5d+db(;^Ri5B!p~RG@U<2G#JH}K{p31B_8TRg zXCO2l*pz2Dw6(vn1pC7H8*qp17DmE>Ka9HXopJdnTldIGoNFdBj4K|oP@RW2M#emS zD%l+tf!&a4(yy>LA<`@ig|7=)*MD|t86M{2M_$Nf1-^j4dA>Fq6~tc-y(KR3g{#1E zqMp(-h_s9(H;YoBt@H|K?|s2y*F)%YK7UD)?d{1Tvlv?gR)iQ^;8ILjf^<@2$h3I^ zjVa{QK)Ci$lnO;hPA$wXB8mHQCkn@vSmlu}9Y7X@Bz$*hgw*hGZyR~Fr<%y5cb1%j z<=$f^^wAd?)RZdDmNN5se~7ZrHo$~8hw^IAZI!)4vHN)P84q=7&Rz?wa6}s{m1-h) z!1#XJSCWsA5kr5Y?s;BTo4a#;K55*S?=s5J?(>dzTICoLG7lYM@my0wxy+^1ZgnKY zSK3Kz>%bK?yFk!$8XlwFEN=dsATY}+DQ_7a=W&_Vh(jdVo3I~Mk)ayqQk_ig#NOdJ z&N3)Vnui@)X&4(2vafjg5~gzC&W}nHzwYE&=BGtnMg5HLug-q}0jVAdnSRSxeIN+E z4eu~3!TNElD{`?S+R622`^@V+3X;A(ye^iGNs8@KiQ0WbbD@gcoR`rYs4o_G96Cc%DvEbsx}e_x`V#s*6v+ zc~8gzZ~LHUh2#o9Dok;MIwlZ6IWs2$Zggs-H~hPAVMx7YvGn%zmS_+4G;0)Omd{!d?{@bz{7?* zuHrkk6qg44SwM=&mLfYwXMYmB+`0 zaszgtJ)%+Rwz)optrUzB-cx#ISEXrD1r(s-NRWRv=sm?TR=g@uhhkTR@G~F^NMV7f zUUW%P=e{#MY2Fbr6_(grIQ92>1&XHUmh@-V>jW^h^2$#|8z=Lc+IhvQP`5XEg{xO> z-|0Xh4R3=l-|n5(o@NyK?pmR16H^L2Le=+|dEk#sLXef@&A3T5A%5gQ-!;luSn!

ez{7 zITDWyD2N&SNLkGC%9Ics8O%DgL%?n=C_IqY6<{q5W3x$RF2C0O3U3oC4~zds>`_~% zC}j$4nU2|TmD4gRETFCNmnRQ*lH!2U#sMDT*?BoPd`kMdSv;d=Ezme(S86$kr7LMU zC^fh6TLOH-ao+GyBaWBe{+JAbwSr0ozT+_-mI1U60P@4>)uyWkc587@NvXxYfeEh# zxq>J!y7?3K<0_8zi0AQh2Ik%!pzeO*GX|%=hXOlMZo62q2C&y7yFc&gBC2tvqKl1355Xi zs?gkDjRwFWL^CfAv&w`{D2hPaUX3k6gX9Z>h=1!+gB9w}@tHmQAxRru*outcPE$qx znw(S(w`|ebaS8+nPla(&oadzk=cz+ES3M@btwsmF)yVgR-<1{9 z=|iR>jXg}+j~tn>Cve+Lu>yIrxW=#n!B_FwSw$@4JwvaKqGKINUXT${W?jtYa}Q1W zE3fSSxXxRpzox!zw60avxkx1y$He(hDBvKqD>lwV-+AkRI2$$zy~0+F_Z_=-irH#2 z$qE)|v(VVwl5PSvUjf*mexR*D@f8R4Hrl$Ih+~jNd$y*J5#dsx*07v7@s>^Vk_J8_ zrUAwQB^Wv|SYw#-XK-`J?WX#_8< z`UdJ6)I$l3OHYoc}Aqa%_9R);dI{=mz zs-zXYmP%Q0)vMmNuN~or^icSfA)yZxDbjUq>V~gt^SeVy`+ZM%um&eh-6ixk~&=z_EnToMLZiMU`PetvHiCYEyc034xxT ziTuyxITzHHHQCNG=LnCxge4K@yfy+~8}8S__Ljf9$Xvz&F5JQ)5W)*|x!9_>mKf!C8cC(SOKWW7EefJ?{-#w#i{*y>%TK@QZ-1=j z6OZ-^@yDtz_*j@-$>@{9^D|Od6>h6H}A2Zviw-)CruK<-4e1qQ8@= zUvrETNn1ErSmZU09&clbg>PA(VZ}L_I}-Wq2`R;GAx%Vuv-5pqRL*s3_oZJ)M$V}* z9&2#$nZykpx}bJl*4$5>=^t}0LkX9r%$ag)Xl#Y%!mRrQ8>R|}+G6<9DVzZBR5=~v z`ST&o?ndK}TU8;yhi@w0sy@xOdRh6PxY?-4mdHEh6?4J7S`uBfR1V6aaEavRy^l?E z?d)l!x<0~&jIv%lO5M2DHoesShb(xJ4;*~kce`CM^HX|TL#UXG1{DlBX29%pKE-(` zG7VlXvtL__iw zk7ZcGI8AJ7c&r0Xe5xv4L{U~; zMSfL|qiCdlblSVRFXa6F=Dd6y-xctKBVI6BjNOCf`I|kr;imi+Nu1f!C|diM&Jk_d z_?9AoY@Sc->h2xvrW6O=@K-j_fOtw5bDJglY+g(Q2q|K9_^9` zN7}C>szoKDl5*KIHC=Gp`w8DMb@LtB>8gW75x`7=YWN^;dkSgIHi;x8dN?f=U!@5L zS>jSnmLC0OA5Q$5zn1G0iCZ4Shoiw{ZG-wEWb~aReEJr-o|pvsPtmfe4t%2!voqFk zvpHB?tmpI@Nv)OFyWMUUmk6nt-H3^NgVN5OtoZe@l~)V|O+o};aYx+f7+~SSBXo*E zp6d&&=C&eB!sSak4~{vwLYJ8W+TZUsEH1q4W``g8QU}H8(h9Y{PrC9*ZHccra-xmK z|E{Pp%&5Z+4YS8p8tIWIi4}X2Vs8+2(W|p7io3#)pIva zaE&2(x@p`zR?C52ZCZL-&sUvkxmVQjJ9n7C4%9qgRjNTPL#Ap+2P+PzT1(O>3Ipb- z{QXS->n*d^qkK9rtt}s68;_`kU{cbOeg#Qh91=VHfHnqN5vMTiE6m<;hv*#)6deuy zwX3(mm*c2Q)jc-ZCaUz_Txq5qA%RS2mio`Oh|2L_AiM~za{0wd{xmP;{tn?x#PKM( z!7$#4)bR8ia}}=Bhru+Zb@F@J$zbKY(g9g_v#P9(cLP1swvfDu=_oh2*G^@asq!1w zH&1;Wu;s>@hrrdP&X-ze1Lt6c3+S*R?k4>xU0NxxcR&g;202@^K!WYC{p{kwgiL{X%pC}&fC#lTiUo+eQl?1_OnaO zialBkkrs*hEAlfie!oK7xNQ(a>P;rOl}=a1zT z74p$l{3}$oCUp6j?V0uuFpOY^S_aze>2%Z<98zavoLF?o;`o$6g+C^L1UV%8x)0v{ zp6;#DPF!t8Ty_?*3D?o={M6Ar$jtGY-^>%W8kqSB&jr(*H2#!+59FwR?S`+FX^J=9 z(CG3i7aL7W>Mn_+hrG&2JdyVMV&jh+{T#~1=dgv;32DU`u9Fn)ZoN~c`j%kI5L z*HvBTEc&f)yLk0k04hh*DxqPM01kqm&NiJ!jqdW+hDcD*mTxijg)*RUJWU{xhW2DpLem4_>@zOn8) z(jCzQ)1A`{16V>YpJ-Q{~4*J!`VF?3;ubka?%OX)b z%D5fcl&arI@D$%8T}I*xR)UOCd^tRv+d{Wbm0;2_loJ$py!8hNd44uTS)vlvm>FqZ zwgPm9s=Ho>c6Ts~!)~NDFd%13>mjrYT`VI7<65gaX8jMbI;Lk>SKp6*iH2bpc5%0vbfnOyTG}het zXle}n*EHjgoj@I|fT4yFfiLsL5 zzT&~b^6#hQepTrR9XPd*`Sny-K2xagIOZzT+<(G1uN9MF4H-^nR20@i*Ijlo z<(1uq7gLiL7?Q5M!kdI(C2R%orx9~)AInm?z1nVfUiUJ6eN>WwzeI^<1$yz0qa+MG zr`u`_#G^T-OV?TGU3`(hQGdcZk^dT&`%V?~Jp_SlN%-3tEZ;)lw?4V9AZ4`+IP&hh=RZpCML5lPR~rD?`(@ zuCN=a_auKxpv?h`f&2r?diI%vBpL#xlYwLzo9bJ#vZUPVh$55j`nW?^O1v}Hi6>oj zT1=!v@5Jg#NA4fj`9|LJ56dSF-G?doJcD>)NPZB~DsEP+sttb#=qVX>2Td}wIN*>g z*?dQsDd}NWoW*AV33-1pvhT-!Z~$>{k&)lTdL?zUd+QvtKH6&qvRgM^9sDF%sj4(l z%i$)PQ69{4g8%XmIg-zTkzvy*PTzM?fy<`S;YwqO3?Ieumhj5NA0E)E+!m#cSqwSf zg}8m$J>2z8bf$j=Zm*DSt3CpAh+7)|s|#N$TG7zPY7Z9lebd<>DNYwURh1q7`_l)> z(W8}Wyus4E??f5`vQxa-jH?s2r4lXvBlb&~st2L^hkrBmP}VUunkGot*nKy1larb*o_+3yRO6_`vOA&zU}BqbF@_=Gq4N1Ad~LpXy$jKk z^6!rbg00kvi8UaZu-w@aw}JX%Kc`xJIt5aI(=ZlB2@m=-##xT@=7h3e>MMiMDE|)A zy;!^;=@^THGk(Uodo#tKVr*O6@MDrvo_o_or7Kp^(_cDNjn>)Jzry=yr9w=3^g-Sq zXh1lGmI6!AgArn#CzL;RF4sOB2Bp(r%qXZ>3tRUeLiHH?{4l&p@q z1)%5@#F_{b@wqb$=DaAtQ(1z?IhS`vYOe-a@?~eu7`NO+jdn)YL0etPy-Zy%XRu<4 z8w?WaKaSvQKeCu|C3T;hlU+7&?jpjf=mt45(ftXA2V2{p@%LMoJ4Lf)lk}~y?CS=Wi;+5DJ2BE<(0>I+f~e9^+GX{0sXe`v!K<{n z#;0$K<$ezdfFH^dHBER>jq3uh!zVRxEt-*^>=*`&y z^LkxqHIC@A@gp4+LZ6$1Mp(lRx^aYR!;SV{ib%{g`2~<>`n-Oh3X2V~JYUY{5jKv+ z<`Vczs+{XHTkJqOvEUa5FsTc#Vq@VR)Mtc)S}N!8xIzFF>sSH^zoBvKVP>3XtuC@s zT3o9=N`VJy=K^3VgbB}Ta|M(rqkPY)mNYcX09ZXI)p z1bH@^ebuTJ?0UzF@R4Tq%kGASRL4n-BE~#9k&4+bN~O$HLn{svi!@&0{sh~%Sel$X zPhK13=Og)O_G?`TXB!?v6D-PsFbue|Y%v4b+k$*iZTeF4IUQe zYe;%psZ~qXBqacm(&k$*EVEqJy(wYDF{p)ToF+}VEVOleXrZ_CHDep~gqKUQX8@yNt<%w@by-vq@gUGzWNNg|xt7aSoF&7zlgqFZhc>Kk*>F zOaMI|-?y+yq0A)}A-0xz{vp4<(4@2X%2SUa6ocuz@m&we%uaz#RuR^V^STd$U~l8h zh4B@I#9R~YdpuS-U3!caj$(Rpn1));+cDPebY)QKTo1)!l zRFJ*GUC&Lbiq^Uzh#uxpWaa@}Ok@&wqQtZ+ho_G8of$TiVi2>p@LiweZv)z8$mp8z ze^+O&120vgax>s%u)t;PVi{^Fnv9hE#Jzr33|;oJMTF>NC|wbcU@uiLJu<9rFOg&AcNjT%(iS{t9=d%fpPriP?kDn4|iOQ$B#)9?rO z-j^fBL26-r&Bx|quS3u?0$VmxqU8EDyjgg8oN>lBslz5PRXng1egQwFrCnXvGTpZ> zx|wzI%PU?S{6Ic*8HeBAb+BibSp$tDblnaJgxjESr`axERSM7_H~rfyrE}F0whP${ ztNl7h;DEccm1G+T7E3RLMO7OyLYu!gVIvVU)`KbztW0p5{+T>3ZZ<pXJVwv9tzoIiKPxKexKYRtQOG=zn~1dNJKiXjPf z%Y?j*v}aFUQRwmylL6$BUv%FdnP3mosw{BO!xbJ{ZTeCvu@Dl zfg8NHrd|y#aiwU?C^&q&{Z0C7>zZ@1J@Pur4>z+<oU{i|1lR)uWnDJQ?^ZYUlltuQ4j!=1Ng( zZg!bYw7s(L$Dvqw*afN4xxb=gO@{Bgt6ujExe#i0r2pkfam6h!s@4`4eEaPCJ+8JW zv8C8{@?M8&*6>rA!zPo&1MPkL#~1Ck+Kr^$HrmQjApcgfs^p(5D4Wew&Ts^eXTk?I z_7nLW=OiSKmAb0)+Mvg7taD3$f*ijZW^Xa%LnLw)tm;3|S0|WIm9lHSy^X)D%;DuN z*-Ek9T&^8_u(l(7cNPB;kkRd zAqL+nYMl8f$lAU7Y@f}^WVhm5`gpd4D}$}4=9l)vk~98B^B>r*-95&WSt;YPDy~0r ze^hU>paJ`1*x!faV!YQW_oq%PK0kZE8u@0pV82$sSC)QS)8eXx&-VgaISRRF#ht+$ zQgp5@k4qGF-Nd>Uf6K(V+wb`LFrV8U>8F>l{%flKkwSTO#cfSjC+1Hmrrs>pBb7>q zw3|mg|NGSFz2a@C$g`0`TBbvnB(HzWiQA>h=DfB)uGcGq828j*W^LvqOg_(G3-U&i z$p@lm!tSjz4<~94CcbH{6_87qQg(}f&*tH%?+jDVJMX9QYWqgLv43KQwK(7C<&!jU z;A3>D+wV*Fx^^k7?|5g_tj_e(YS|?sg=vT&3p-^oq^dDg7LK=XIO6JINY^1RS}34Kr>R-ZU~)sQkibZ;@9b zT0S<%;udp6U<+PDGVj!;Wa74W8gpKu@`< zwl20&C4c78rD1ln$+)R2ETh%qX%i+z#wzhjfg9-v(fuzM(jEjtL8R6H<#m2#F<(@D)fD1Il^mUEmVX%X)?I0 zpq;%Y!W{jk)}}kZVejCfBQ|fNvJ7~yBzewe?b`kDOn8%^;_K799a7`sbg$hQwRrs1 zIdA{SqV>Lv;4LDCm4aT&xP7-U7PB|m)0rc4r|WxpOS`wZWhu*WK914b1wCK*YTmZA7V9!hrjcV^m8{Xk-r{f@4$VQdhh{x z_}V{xKpy%g7x2vvj@K-#Ehyu0==1Soy2cJ|(p$YtHDhtam<2PfMuDhJYulnFt@*yW zH=!#w>IYi69eViK)_bH>$7I{~NB+^9SWV8Cc6N_ne`^%2Ir+D;ctW2`E!*riC5@L( zga)U}x0;?WZ5L3#Y0YcSyvtwIF=G2Z-R+efV@@(_q}GQ^AM%O3|BO4Co#}8C{7B5S z!p4P5!zlYjm24Sw;H{eW{ruLOFHiO(q}C+edwTQyzFVPt%=LrNCrEGhemG@mu=7OB zVsG96s^j#ltpjZby0*sjqb`cGy^8e6f5puC*2?933?eT@*Il9p<|q@Rk43JhG$FI#)PsP9XOIf?zxS9Kar;f$hd(|5|lzP~Y zY)9;8G0S7K_lvxaK9zNMP+diP>wfpuxYMF16HH@Hn`IzbF11@JsbAW!`&zlq_pWc# z$xpg!>96z1M4_1UUE8J~wbvo%qYsJmU_n|HEDEqs5=>GqUu z-}9?0^UgllQ|*rm8HRKEdF$+a%l~&yW_Y;P8DF<>DbID;aX0a**J>Z}s~myrXc?Ej zG%|_(j%IIMQ@`xCP;}SHUj6u{?&JZFS`q$HN_)21z*Ovxof^P#aeAe z&T8_>U7da!g7j_he%m>s`$-x5e_A!ZSv-rgdD0B~dPUTJ zwNT6pruQ~G+8pxQE$^MST(sdjAKw`9Jnpol@tdxPhX&prl<%&&J$)US9g%$}N4&R< z+c{Kp;B3wwvw-%@e#f_QJ~^7Z#Psj#+&E(UqW_@ojXXsY2m+0e{Lz$-Kb3X?CL5}ufB~*2Yvd5@97*1Yi+w^cUBcgN~sGuWN>I9?Io*H zl%RO?6N!)+7N$UR9V4eh0>xkAmt|Z&zRqmF(KUPY?Au(w*&`LIi-z?Zst0r}cbYfY zox9YWGUb>Uf3BvoApAw)M);@G%Z++d35cgHZdZ0^^-m$2B;72AAI8WwV5_dmWvv-} zE88`V!v6Jg{(@4bNRinwuA5KUEL`UE^WHz(?OJp+*Y6ph@I&Mp)~qk|Z?%?-?SD~RT3X(-Wk>|K>E@@m z)q5+va}KG!_U6A3TF5THO#W`IkVw{be}gY;da?UY8JU%mkr}^bCqC>G_+BmMTgJTA zh(kk4Z+SLHSnkR_Z`Ql#VuX_T`6p`++bZOyJPu?sz34qEy=28d=hzh)H2QwSn3YmR zfY$1N@(tS6l}f{HSuv0A9<~-f3g>yDywMRBz3*9fYE1if$6THl79q2DGoGs)6Adw7 z;SlnjR#Lh|^7C!GQ>(aXt9r%uI<2cOb7sy&&g<_?J)C`8JJET)mE0-0OQNPzv7em= zEtNWNi#6K1%-*q2P%78cmf0tJm{&=iWA{jrfwqq0!OEAo`IqyX@1tIZ-c3lppmcQN z_R*e=4W;Len?moysL_I)tQm6CqmD62aZ^<>Mj_si;Rp6_^F8Y|&?r~Nq= zCl5tzD`)bqzQ&Wh>hY(9H~so$Jj}cGpNJo|c5wN4_`5^V1J;H$6LBi z*;Yq3T)Js+G@BKd^(o0A?8vaZV1GgLF~P!sc8jj%z$fcvlco=?hQDU#I8izL{b<}9 zA(r-g+Z7tFO$Hk{engfLPG41kzHLUJE@ZbCI81Za{AuY9t}LCyH46(z2kJK_k^ezH zSE=8Zgn_%4u+`sQlqBrMJL3AKp29MQ#Jm%S96kbikWVa<27jM?>5Uv6wIM0`+f&9J^x zrtWBaa67kUtY^-IQ)*ClzM|y*eoVXVD~pQTGB#Ox3F_58JEz%1y*JgSY{@LstBE+7 zcqnn$`|PKn_Gj(w#;N@?#WE6w_nXOI*yWpJt<%3Ej(610qXfBs8jId9uv5RBd^3s-JVhdw#rZqICINXenuGd8ssY zS+r!aCsDI|X_9EWy!g!@5B|S*(ehBuGNG`0akdQYy)dLX(d|v>8JkvEoM{(Xo*8Ni zU7l~&RzTnr@!kt_iQe;*y+rP=M+%#^q1{W`Jt0vl0E?2#&6UK(R|D;`GJ6YPE@}dyMSFv#P(G<+42pj>?Wixk&3UEj$ejsw=A}qr0p7I_Z$ZwbDQua zqs)8Y+52IVd$4d0kAJ;fpp76UOd3z$@Gl-t*PhI0%Va8<{tE>`JUw-fsm%NN1fjb- z88>2dZ#Mda_ouWqbJyP)y&ur{C_G=c!E@YM@h(%9)QxN3!X_$#+`@xvY>pYvCBX_QuK_`Os-g`7w@%nhDk~*yPE2(h&9h zwhF3pUx?z!kxou;n|35WF?*kx9+57xesz|K!q2TjDXn?Q zvi4=->PGi-sSp3!RM&5usL`&p{W;`>Z)5PlU6Yo5@8Ep1?Q?5S>0xRlg7&kt<(z6) zI!u>1cGEIgbRP73+L4myMjGUDC4sdr}AHRUcmZr>TVn-sP70L3y;|-ZPw`vEHHu0&5 zaN#GVZ>@H>&+RyAgsC{#)%o$zEw$CpC&@tu`PW6tbJv7TAIo2TWE}f&<4Sygng43% zpzX%}3hN%UIN$_hN}4ZgW3-mcC`%c8<7yH}?tuBw$E+dg5lbJIIUsJL-IP4Kez3%BK;n2ccElz4Xv zyg#>TWiEej`i{C8q?XRY*BZ9zJMw{BpvE!#+uzJi_N|4M&@XiL!j%I%PVb2~*?loR zaYwDZ$n^FklQZiM9=YIp(e>~7=aXB?&K$ifZTem^-9%F`(gQZgd;R@6CM7+ZH}?7k z8f>(ixoz$G9%+<5yCbF#r*!bxP9GoYG+cJ_1@V+WWX?IY-s92x0-~f_>%&?T^YyeC zy0X)4umL^Q+UvJ#G->_r@%96|Lt0JBSDud?^xLW|-MW6y=%x+Pt7xtU7>(Ya-jilxQMSI{@=gybGQvN1(+1z0w7`;OKFDfE)Y;eDRe#ED_<0_i zgXik$w-2^#9-^tp<>rGOC#VPXc7|rg-pO3dyCr)ZJ#gHZX{mhG(#KUxwX2ruR}DS? z8p<+%rH2%{6}@}Eh2n<(q&qztwYb>YmeVqaU#_7|>Pn<5)1h+QzH?Z*IpH780mNPF zaCV-@W(-$k#D62R$*zd$qNL*mq|D**@;#_JPobB0PRlSXp3AAzdnRr_X4(5VaZ6Cs zDbJJts)YG(l;5jygT1H*&o|})Dt-(~{5IN&pXoey2C*xyz`@B=ZTjsao+DhhS3+Rd zf%1l}PGwtXEdz$@nsMhpwWufrTo~H0Z7__oyC;sRiJu90!87c~Gu*Vbd6_wNQTi}R z@HBXP&vQ-M);xy8Hrk#RRM=T?C4eA)W>&#r56j;}=xx_yV-6}_poOdAUFltMHap{l z6>g0JTMs|A1S#AJQMenT;2Wagr{?!+{?13Q$ZG*xl@&j;D1J`lc`d75(;NQ8>u_vi z=%FTlYH|aSg%<>or7h)n0VVTlyu71tvyy_F!H{z35EZnof?CAU$k6`HIk9&LpHDgQ ze;3w1MmW(2=B9?CZuC-LjDot^LQ}TgcpApR+X?e==UY&3ZKR!#=R*|!av+){)g zGeRFV1+ucCo|5>=ahtzL){(~C#%;$1<@(m`bsV>K98aWqvh3JY+!pSdWEr~59+V-% z`ez{=GuSulZ|ojenv=szE%PD4KYo#crH1yhB~7$d=9kK2NS{jG4tJq{)daH%=tXqo z*p1uP+z9B%SAdlh+9uV{%pW=6$+@j0B%qGOVyxWfABeY8+%wUe!?HI!am!O^3+Wi| z9(w+83qza~h3@Wg<<7Mpd@k=)-!X#d2}?=4=U9Jk!%P(=b3&T~&0<#++Ahi5fb_f8 zgwPj1b5K!SbS;A~$syZ*?2PxWxY9h^V822001ZESsFfXS*vfO?Z*aHYpr)cD{z$|8 zp^+Q>ijFHP#{2_W8@z!8{Dx}zOnV1VxmPhJErz+FYAb_R$-5X)wv}WVFb;NBY+cJQaJNw$f)g*l zIWRnbVPIsxBJ+yVs94HdkCnUbGR*_2;?=a%1D^FrFZlw-B3jB2W75)QS4)PhOt?*>qtn$2%$0t=by)>vW}~13>d0wo)Z6l2xLsPVdWQ^Qfe7w+e z*rb3hOYYu@^BZ>T3v;g@41?;giQLJ2{+!XO%6xAahSU_}+t2$dtd0aEu5YDE98;6K z<13AP|9wS9o+|V74>Ff2GFc6E4f!Zg`QQz_#!VImT)?-KDWLcXLmK(G^Iuxd^Sf^j z#ae0(p3wxQ9ypQLU514Ry}rjr@`ikL-cO=EQ;xtH@2Yk$zLMf{QX=a z9qvjB4x>$ZhXXjPKJ%u&DdyRL?TJ>DKHP^ExYwG5>$ijf+@o#*59cNNb zy_oSC+6#ZAa_@m^Ql)Aewmg2z81Hh7dbyIg3M*=u&s1PnJgeG-beOoOuYpX7(NrB@ zTV~*Ry+ZuJ$U0)fVR_Hj(E;q1BCQXVAU!2%4^(?wg2#ZhCv!a-by|9*M(ILh>qZ)l z(nZGBF*O}Vn79+81Yr*s)oa77OtHYA^jLg>$m1>PoTC~Z@29dktu#H}6U0@xBfAt5 zjpbcN7lK_-M5)c~Svy`9i|5KWn$6$dYbm1hXs+?5$1WSqva$DZ*~h|+#ynHC3v;pp zRSnxzU5sC87v7H!cw#BCS8AJTlTo_F*t#1{AJp96PUjnqITth;g#%07k}2ASKG6Z| zu8XXZ+IIA_QM%&TI@QmMYUk6OVJ*p>8ewfU7vtx8g2QL8OWCnyXpC9(@R`Q8F-g8I zHi_4ZJpYtcQMl7zM3zH$Bm!|XLyj#b&*wz!+3k9FRU`9#!J`jqjdyn1Tb@>v<*>7; zO?{!WFI2-jF_cT_QT+k$#7A60Q!Xk|B(>Ets2a0I6cN8AI!~uuf+Jc^ASN${qKWA# zo8H}{Pn)J%HjjvOA;!B8TVdjuThy#{Q=L0LJiEZP>B;-EwH@W)(G|Y@HeZ8OXG>+S z8$4Mf0y!z#vX|CJh&mh{v6*ve80kye#%||Gz;v3g77qWLIRdR4+z0@}eeXytlgHv6{ zK&@}xl?0yX!D)f$JhO*yzhK|))%SEKO7LcH)RyJX-WVb4P$mT*VDh`un)pP%B z_@jZog3vb~Nl_sj@8bp@HyqHJ4H;U~BwKd~4?iu8hdb{=HC3)DF+Y>FKU)ll_uv@fpy=d2)C#cke3 z0U)Qei?Z#?x7%;4(TH}`8-5vfLpSG$Y1Ltll*bxCF1|4mcC5Hp?EnW#3W(%7>Q%>w zjTq$cK_Y^YkO+GdRV4gDu#WT7gr)^J>#xHd1jMr zOnA>wA0hHhppIzJx|&2SAV(rk2-P$Y^8s8VHfoeQ>TOO48!^mD(3Z{K7_OEGeE8H- z4Qw(yzT&q0qLF4B^a0gQM|+{#Fa6iy*S4iR)9~YX-$)gq#FcDklcfMkBQ*@$*Dzsz zZJXe8NM`eOiW;hn`e)0eIE~a;Y@fg+kV$y~$(*LiD6rY*D`aV@#)KOU_f)g$T}urymHz0yd{#rk!ij%RPoxx}v+Y@#UvEtGUv2WnG(2MQ~Ytf8v! zWY1nF*|!uDdp12?hD&el(c~Xj+}24iC^_tgLk#toNQLa>WvVzG?SY;%>9OmxxM z3HD3tC3O;SSHIhG19G53B4$h%f^z9nV*Cr4{GO}P2e7xj-aQ?@RL`n&34#kE9egIk zZCllN_T@zIom}}_2Br=?5*plKm7=kZbStKr8aUVo!R9VO$xV$0F$OUXK%Qe}O}KU< zP)4Ax!$Yf&XESB@ez6qD&`8DR7Y#OVA>ESylJuNAy^0#chj!aP9My<%(j%mV9d#2v zU*`-=JRysGhD7j~p($_CFDP6qn6#=TXlK^(4mEGFxK-So^qe_8pQ?tEN$+!qFAevp z#HcnV?!qXj zCM?-qSU1giaD!kDH09Hs#V`rZAJOMi2<+S5G8l7G%Qaacyk zu%(LqWQ5?OHy}6*HQ0r2`?gS&*mn!}*>~F{&dLbAZK-lP6(NWpOP}A>bntTaMrUJa z9k+;8D3_H6=F4fn)w&fEzJ9dtdTel&!{t_=dqWS8=&ikxPK~_$*AHqOF3TFWS_+hD zr1BI*%4z#LwMOnsiaVRWZ8ybx(>se7dkotIiZoPvo$Mv*D?p~Le)TE@AaDC|;vBlw zX<;`?g`vHB?riX-?2VEp6gccu*Kp{zWrig`5I&pceC=TnM-rG?EoC<~CdXiAujiUQ zjF*!vrKN&#ex_EHm8R!QT!>Ll{4p9gl>Oor#jG^ug~85YND5{5UIWD$wf}LH*O!+ z+o*+pu0Npjfw~UVT>Uh!>0(8Ufr8URsb~Cxy%a@=jvp00mKA!_QFZw;ryJJogArBH zryms&@|!N!#~9pjdWc8zrwmdQ33dLc=(VhnVP_S)4yW5X_YXOcq6>mLtyD#(oALuJ z65q-Sz3r@W(&cp9?f#*MBGTGP7O6cXayAr_c_%Bx(pA;0$LV(5{lgYpikjXZ)YQld zS#(uN7(@u0zL%j$v=06t@kLgsxU1@kAtZ5?s$-lcfm_&`F)Hqv7~dnC-!*bz;**BX z6o@UEpmiQ4l-N2W$ita2`WTTIKPH>MdGtV9y+$jZB675pQDnv|F@9b)UvgCRjGzvQ zBGLYX#HCw_@oVJrO-JJ}N@h&b3ChFZY*~$FJX_Wy!(}G>WHN(cyYKmajocTB3~VbG zSsW!NBZ}j8$_ah?TGed9iICh?`2M*3F?lxjVB>i#Ic_K?p|Y!<%7?HUb;5+MYbl%1 zGw){9J|Fk`1_x=+E8+FTy)BS)h2?}0->RNm(?-~eOZu6)o4E76-d#GGMb7sDynP44 zW4=#jU-IW~Ni;MDQ`&cb$Y&_(mD}P64CP2ApO-4-O^pYT25+4a+cHc-r4u$Jz~i=0 zF)0u!N4F>PjG!!{$5LR2W~xQuuvof|07Xsck7{05G&Kq#4Zb-y!%Z>__cX0(68l?X z!52j?B`8af9g-M-RW5&g>^0_{X#>Sl_=+W{ND$bgsoLvmFVS%sU z=`{xx-PF@t9vMD`>)Vx|3|kXC+Y5Qv^0`j>?LAPor#RS8PDsA5>WPCkVm(LnN65iV zCo@cTpMdry#lHvL^o~@8jSQs{m<7WhL9R>iF@0}p4@#Oa*qYr?F>=C9udOO9c@z?v z3!{nL2O`p86z3wRvUfb;Z|O3e<c_K!vQPRghXgfKKNda> zSf^h@1L8md(ldR)6l*D>sfuv3kLh|Fpp*WN>^AisOyQAcpa7$IZAVmMe3e|j`-I*Z z!Bz{h@A-n(5o?b_MG<)gWj-}sypA+Tb`v_lks?9H!B%m*`TGhE-a$*tQ<|yki~rfi zH20i5mq63^!j3C*`7)FJIf1{0*C;t)U2qc_>6r`@H<=Ze`MB%t`W%+bo_4wX_TFK# z+v9Z7mG`c=T~%JlVz}yUQp*vrlbxWo6aQOKC+Yss-mBLsNUK|#8cUD{yl&P9I7W?W zNcWDeAeA4r6fo6H4J?-2#`I4H4XKRt3eujrZ1G%vZMe}a>0N6l-5>2_e{i5ih(0bd z9n+29kcKF?C-^n+(VLK++Ru}e?PHg4I6P80qc3I)zQ{2T-U2u3C%xm6?SQ5%CQ(G) zhSXv_Ax6EnhOeNhu!vjQ%wHDT8wq}R>fT_%o0?k@}2VxO#Ssy5PU6VFzlovE`Xrflk;nF76S(gDecnex7I@7s(8v=s}H%DX*^~ z>J!isM7e*Z zz6D$7kUUI+@HAs+FSJ{=SQn|g^(i0_g;qVS*z$bx#5_#IB#X%t8}^}2tm(13!8G55 z&nH>+2{%i3OzLb=64Jbn?cU2I8cgTUUsp2+bawPx}lWs$IFsZwX zdBIkB56v2y4zLHv4hMxkY(Pc8=0^(}^f@w2xaFXr&^S!iMyEP=Fsj_1&Ygoo!8+-z z`ylV~?;vZVZR!=IXMaV?frjXE-RqbC1L=nD*Z+p}hNqEUZ`O?qwje>h!O@UPP>|x>*fK`5 zD+l5wV1?^vzW|TzBF6_y1td#P*l%!dmiI8Jr-~)EG38W}V_q@Cr8fg^eKEyqbg_a+;umjXy^#k!fz^MdDFq@N*Qv-*dBo#0Dpy&sb`|xz5 z7RnIr5e=XuK~TzPsz2K;zr)ZSFF)%xl!QsmDpm&p@ELNvsk_B+p7&Sy%5h65n)wWG z!FGXKrd5k(sQ0&qyg{UC%7d-RpP-#^pSZzmj=ndOFshmeXZcwY2x$3P>Xc;0sZ%0X zwx3`k)^k{iLOdsMKb8Wfzwsv9--2EV)DnX(atQQIJwP(jR7*3Eu{jXLTl*&o5Gq%> zX@$&HRD>jP^l7KZ_6(C~Dp=ve99CJO;L5}k3F-&yIXBBJOe(e*&Hy9`SR~Rmuq3f4 z8w+n4?aB&R*FH*FL;JHpAA(luL?evaMzd}>Pw1B4ww|NRHy@nbpJ23di8dD(kZEW* zQfWA#stjOIjYc?I&vgRNU!{8fXb>69s`S}UBc;@Q`|8kmcD{R zZ*BW%ubMrTO3^0+YQGhS1d|;yj=5_vjv39y4#fWg#Rh`HDmEmRPQK5gd!EtM?*D-) zaE}4`{y$BHidB)gP(b_2BL5$o`t34*i7? zd@7LclnvGa0!oV;{wUe-WB>KsCM{G1k}xXMURbh$!(*5l`^wX}OYEkAG)MOJU>Jwv8r15fk;G zh7=Wpq-H|cjC?vh6K>F3>oL5t4-#P_^0Qc{999IYAT6Qx`*6HR66kkfP|~9P@vGq+$S=`WLrAP-x-1 zf&`=(+Cs8|(hMvlC4A{|7You9&Hc#VV+E;>7MXIO;sKFKt#@dF=?@qxZJFIb%Ke>R z*V99H3J@+$5@u+60vB#vR3pnW<7W9BlX?%a1KgjUP50RcxV1q>MzuWxTWX$vM^j!>m}5Ov-L7@hW3!Fs`!Rt$c`xc^ss)^F1oZI?x@NCy+p!(B zF|ANf$qQtc%IM)EK*!Tmtaf2RR-iTDaKhZ~Z*SxUvPflok5PXHD5Zm&=d-!ybbU%rs(Ix`sfNx=HVo)W+JOc|Zc#pRb{lshLV{8Q zmd|9~<#=ziAgxuTz&7pbUFlrVZ#@())shA4>CH~_qZN7K;KpBw8$Jw(6?bMJXj~P5 zw_T@%&P$IaU&)0y4}U@g=sY>s5TmYouAPsL= zg*_0RcQ8C&zsmqa@B{@KUC$0C=Nj4uq_0H@xDcVuYkLqVP{}ZU*I z;M)c?Q~ak37-z00ttk4RtGN1~DgX0*WnK zfJK4(3VrC{#O1@*6w;lV1kMp!c>I1cpd6#^O;JELe-j>nNYYdQ$1rdi8qhr}Yby$L ztMtLKEl7Ngj%ZqD=j~V>TjV0*E9teZT#X~ z-ES=rA*G$YG1NdY2_7hT)Lb|nk#}-5vq{uewWcV)a(3oG+Fgm1 zD5@p!0J1a)ER~Gz_|$$;+&0w_SgH_d6{lJP4V1v1c3)+ zESU0jJy9_U?)p!M$yknkNq zVd%Ng69r1YT33t=ldU)`2O3H*6%Dqeo5aS45wJq=J@Y9fsf(+*PJZ=%@SAv zF=sh34h*w*rWCIBB!+orWl*EK7eM*m6E&nc$A^p>j0$8JsLNd2fvYu;6C+i1m5Z^- zi#0F|RNqF)BBO%g2@2R~*Q;@GKKGS@kNGkssg1i{6-GuanH&G74o+O{8I0P@%0L79 zod)!*+z%kwBk-DO-wT<+Vj6Xo|jJN z<|rphqllelumlTkfEk%3bV+|%f^xCyc0Mn36aF~!Wee`I+kC`G=egq|#6iu`sb|)) z-wA1yG+M1%iKxvBz4D5OxRXN-i!RCv%^7{6kWu51<6AvaT1mbPJ|f~ryaov!0z&3k z<#sGOlP07$P8FI;8aI27U{++uqSK#O!@^?_DK#+n#E(Ex5Ti^5kZ}SsCLdv6Vh~m} zFmT$*!S!E_EZv|~jHqFlWQVfCV>$RyrbnY@z*q?|hJ_FfGb%y@MNy+>Iv32jiFL61 zzyVc8zyY6KsSb$HbmHDHZnpDv70hp);hf#*Xs^Ls132+cw4aX08&giJg-dw59++Qj z!srX*{TQs*xC@>b$$>cp&a?q5)zg?mGioaXHQpQV!y9{|`oNj?%=-Lb)LrDtK+9`w zI5j=FuthSUP4Z#&Vk-kR;?K(>&x35Dh^YP#ExjtkpkR>uLB}R}HvjG9Q#!jhD%-Vk z_H!xXg)3hye7iftu!V9sTB5})aUsdCy@^UVhRKkpwNnL|^#mOD6g6*~|5MG;l;5dg zbPQLEE;%PLx&=50%CmwG2CNkDg+xRxn7K6x%A=z0d@mRVYSs^PkqhI*3P9_m%f}CNRj;=W`kUcn4RvG^Reg@ltW??GmK)rdd4>Yk_`s8-Ud7h5O4GSGHmW^YucYr;HKEA5z3JH;?i zZ6u7kCI})0$i)()0-%Z-i2|}nfna!$0+to`g94y$=k*|Rv4q8`>B?y>LdDW%_k`yR zLsw%O(qnG1q7Z|)(Tb`ND8a%si^pTNHp|36rwzPY;#-Q-Po{auY6t{td1fJy?wyK> zI~-L`(T6=MX&zU|2i!%D#QCd4x!D4L4S~VOw`s!;g~!E%P9lQ!BVG5ks(W^HTiJ^I zM$33Fh!gI_QR#R=4cw=>xdV7RMkD}J&jovKe&Gj1X$!P~lU2jaPheBI`__YI~DzB zz{;n-f|hy#mY7ERu-$+AM8&$E;+)>cIb9PMKMvFK7cLY0a$6;m~_052JYT$0)|J5{v=t9BC%MEpg~nfDcTG^_S3MW z4`4fYx1-lh;peQ;0@fg6Qlt=D@)@D-lHuLL>+Q|X`LWv=q=jtY{EV)d6McS2%fYCX zfm-ip|GUJo$1wjrfV+ak(bmHS=1kaQuZR(!QCk_P=N*tB&?NqqdHhL&W6NMt|~?K^&88-RCElj+q_ z*Q7mUiq%+O+HV27rNi2Rv{m1L9@1uzgfGOz1u9GK>-fj*p~U$z8N znEK3Fl;Xa@$37Zd^dV4jh?WQ|!Ol2i3_^|Zc_1nM*a*M48nMM~RNCTyqoo5K$kYd` zYqhJ^dDas>7!325s~1=kBT660nbOXu1I;C?!3FXK8=}gd8~$8ty^IBY0Gk6;x~ua; z#mMw!o{#XTA69oJQO&WMKB(+bp`>p3xU_{ZW!^utAn06u2A!+5WCl|bSTg94!^m&| z*ST^SQ6~vycL%h91K6u^B7|pSbSq?g45lDnM|LqV^#gm18o~5qW(TGQ?rVMTc|4>! zN`UqK!j+8hA66HSkJ0dU`^(X}7C^!lv)!)|4+0NLgVhFP_m!Ys7&#js$Q$&NF^cRx z0q9Kovt!~vBA)$%1>$Y5JJ3@cZ(4hQG?_I10#XHtl+FVSZfiJqO=f79z%TYPz5<~jh)r2=*VMtjKx_*3 zi@kqVQ@D&I}D5E&1nq!SXKh zdr)c;3qsid&6NO&_h(K70#otN#7e3mf`@_Lorl;Sja`sA zUT^eZ&5j>g;%Qo*;u~}26C#Ip7ha!@k(tH9X++0aE{p>MHsgT_;+qwYNPc8Hq>YjH zSnBBCFR&@*5q)5|PIw8*zAGgqgP;spc^*7sC#CJ@PE`e1a$a^CRDbif<{9=kv&9?q492 z?<=KcckxXUe$3<+vykZy71nW^%c;i3yk@U#NjIiGr5tN2*2LxLVF~T6DO7 zVssS8eYuSk7>rsOs8#6Wy_m-pVin*{3Q_tSG*D~90xf0%7CH`EXuUtM&q}EVXrYA| zt=y*PDl&BhxeAIYjvpB+&AZeY@e!Z}_~VS&5Fix(eMS)N2`m9?bmJ`M(u~^50IKF* zPI0&Hi2*NsdT1~l)G1*=(F%7WKcc#Z%AW#Ds(z~oYAy}mhYv$(z8lng?DAR-36Q`^!}PUQ-%F&T>s) z16C6LsrWCX$$vmP1JT5i%fIa$afnkJRFK!%e(WqM(++t`8w_~tO&~+}irmbi#s{T^ z1(1IEZKDiymWE`JLu8+h{JF^mkUISqDcB64$3Qj1Css&%Lg`p+&3rYMm zXV^U=!`RJRL*H{56r$Pgf=C7&*=<5F( z$#)u(-?Y$lo=-T%kb7ukC=WFlx?i9VMkCJT9vZljlMnu(#|FA>G{3sYiGf^pm58ih zXws1lQuqHKI(5_wa|g7T1Fm+4--GRkCfv_3Kr7F-=SRLr@9Ea=#ne`aHK9h;e{R&V z`5hsLsu&rlnm71e+5gfJ{7Xxb2DD6UtbZtK4&3bGsy??Eb1b5X0TdR~lotxM!a??B z>ba9J0mB#iBh)AiMRayHVjZd-eU}({lbdba>;pm#;wXZEqePCHwSg8InHBMC8GGwa z=0nXjF8uLc7@%q)fbhJ|483wH3{fjfy!L}St=b&49uE+uo#*U? z0nMel+0%xbAKWv5YXm^t$lbT65Ye^Z23;R=>usXvho%}}UC_}YxRcta;#+_&+JETG z{lvM>lP}tT;#1TBK2L7EJtAMUueA2akEq8Jy}zgRM{)?k_%ro`U{o-){>XrShN1a$ zQ!a%2I=GU8-W@^dBKj@=+PC`wsW=JLCO>rke&Cm!m_E*B@WzKaQ7yp!*V4<|~N1(*8;=mvI-3vHFizT_6TmPBqQn@e&yOjA=jA%BvLosou zOhvtbp9bKrP9nk&Mv!CD6?%!|QRug)LG-q*6S3tC_+ zl!FtY-F=XvB+V*4QE&HP}%3WM5O%V)!gW>t(j^t~$ zyXy$g-q7%jIOO6WES^#tb7NK`ONI(cy@Y1dh&1hJFK8EMP#O)4K?g#d? z+XV?}94Egwf`v9;nqwHTx+Q{Z!+!+=D32PB-vd#X^D9N8lcL{CfO}?aCAep%wd9In zaQ#2fCeXC|zm_ZgVCEfnc!BXJv6pO zp0Oc!DzQ9vrht=U(8(4pU;*{XxE0ep7#eb*H3wZpV?-j!eI8wK!8wNh{HvLtx^3K3 zu=aoGjW*CLVvnKUAt%XdKs~1{(gQp;CrBe{@bSt3y)^~8i`MA0Q!#{WB^F_FE<386 zO}s=O=oE||g*!izXC+-daJbn^bN@`f977Yy?fav&AX1;QkFPm2EX zv$wMt?0tpd9@g$N3bP9%K})X&L!p6Hg&WpP+N4aPeF8U?R-huz{PM z^fxq|8Y%-9j8_iJPk>%pSNoqtsO>hKvOZNyXFWFysR0@wEt#R9gAV#__FXq*m#zgX zc(Rc`52WoTyogoU1r3K0^OwLqChq{~{MC6_qq(hd{>pEL;_d6BoejRSPQ<7`Nq#Of%qQsWj@p> zWSP!_?lK$c-AeEXoSjAn`+@&7hCqmxEeiG&-`5x#e7rJ%LP11$>%{Ed#2GS@e{e?1 ziH?pcE5ja@B2LZ#JmJ0;0lI%wNOnzop(P^|Pai;Vb_Fw)dmzvP2yj3Dl7Y*LgUBORe3wfa5M2Ln&2#O;_u^nVbyNR;|7#0|U) z=jSQGl* zePXD>^6;4Bq(3V+j5HOTwnXw+9wH@rlW@V@r6e2)?M+znE?FLnuwA~$4f9%F^4IM4 zA}p1$g75!FvvMmS7UzhXw#Kt_3d<<&uGuLY#->6vAuGZRLbb0oLH{ex!fcRG0tHFP>ed+)fb6c|u z_O>@2M6TSt`MXz(!VOb)gI5Xy*=;|(Iv@N-2L07$w)PgkdwG*`?2dl$vOMteT|c~> z4a^7pA{AxkjK6~NTQ9uHFgz>;U_1sG_U0vjvK~1%i8myF+k7a1HM6?hb>K;KAJ`xDW2Zoe3~7NC@ukGLP@Ox8A+= zUftjMbz6ciMg;EXISnE!R5zkN1#vvhE0XZz<~lQg9~ z$bk`jCM>o6bm%0DQdrtaRkDV|gl&R*C*!!qfI8bPvKg#X>bPP$^6PeQCaty8mt=u3 z3LFEfXOmYwjs>r`kgOl2FMRx&F{(>4)DQ_T1J;D_Q!wr%fp0`BCtbcurY8YD$Chn< zH>1uojOW3nlYb!AyS6~GBj&e!2;R(qU08#wyw#EfL;O{5`mcChY_rzSn=)p;8w$?B z`zjx^KvJ>WMN34ni|x=@=`pn??O)?%*9nO+b#i%D44gfJ3~~g1lzy?HIk(K;h*kJ} zq+e^3dEv~RaL;Obk3;-w;Nps~fUT;4jAC*OX*qlYKmiU0M)m)M2=C28U((sh!_vva zSi{%F(%q2F$I+oCWx{EI14jx#dkK`sFx1eL+Am75j6ryT!BhDbVXmLId2^Q=9`!{N z1%=NQcV^YS?!@A}qt>x8{M&G+!F5xfY#+W6DgVUK%rNTQ%8n*Gb{|K zT{i44=~Jq2eYphI*sHdyQtPNQ{IzZOc*Lf;v9v{-?a}$Ynq>N|fJX~P1H$rUP~H{e z3mJOEb2@SVU(Z>?%2*)?Nws1hGMj*ejg>OISKvk$@tlpUG}C-~WxKpv?bmBq+9m5f z&5k7`5=jyd5*^$R!~#B|6KnzDN1IQ)b{*_AwKc!wrDn~er-IgU?(ccXY`q@};vzap zZKQ-onJM?w&-T2rXUw&jw*>EhZE!i%y=03ta}gpqtra>%z2+uUUJC{6|J0fq18=OJ zn$tJ$jo)s3dPe+*DpjxHcZL)Fji<=X zUff3e%CK)G_!4Uf$e!3^n(!xvqq+01{vSgHg(%pCSFM*MH!6@V;=^0=l$dK^L?XT| z>E)|Djj1scMD=@ys~)}6sU!8DOrcUh&_Wciy-}j6i8Td;tzR@-u#}dr3Nc#ukk~=? zO%-0(;iEIP7Y6#Mf?)?}0>xhlw6PxuF}IDO7dt# zd5IKEbgq}s058HE&2(vHi_MXafs|mJtXp{2r1fB?stw7fAR@ zPLwj&j_v1h6KH&$+@Fq{dTr?o6$qbc`9z`i!8Sa}z%Se;u(&@A&Fc;}^!1To{(|7M zK^fB`$->m;ux#IM1;0e{o=Cljll)w^7028)f?D-ki&Z zIL6^yV(E2*)xU3Hhl~P}DSW^421VO{1dIN^z;bc3eanw->XsfJwocaW?Ejxny+x-mR#q-N zUZij z%1^z4Se>YaFjPOqXiupL@7hldY1VqWe6@DRA9Od5`A?0guXR(rlB5!8s6YQslFER1 zmWqqb4vNx|EuT||V}=2bZ{yd2sfWkkze~E86V6c?(@giwrj6 zDS*N`_|Jk;ktt4+-fL3`-5iZHRX??O+7I;-p!$vNZJmH5c z06=$de9uGMYG{{I%m$ziP@SLZ(y_?i5exDm#1@>!me-}tmP#VbzNQo-o4<^LzV7Tb zR=@XiSAX4#($sW>zTP^1GA=zTdDd@G;=gt_ie3|}*r)WKXx;Hjr;Bk*En5%-Fl#LM zbt*SbVUKr#otYl>Jwf*p%g&8}6ZPI3nd>Es-e&`-6o9>TEa%nlQ7!XSv|Q}DQIY>( z#<|KkD2SQzF&R18mE$SjGs#@#Nx}553j3wYpREMsF*3mYkE@;KS7Lw<82d4V|HRz* zRp3Naxj+WQeidMBmEZ97I&4`r6-dX<4 zXA<_PqbzGysFO#f$08e~=mc_1WmU6GpFZ#&Qhqn9T~sc?kYWBi-0@&mXy)m#o*7uh zQXZ1_w6~=*5r`3Kw ztHy$Ow6d0zK76d$W}?4hddksgzP}n2p4lC@5}N@PiEd6j&a_IUrdR@vnXfb(mrL41 z$;WCm;&g<)Y@6^=ruV^~xO$sZ<`NC||^UP8{eu`_mcIx0eutH=4IfU0?H zTHIr;RS3;F@0QxKvuaF9Zw90MumWAp4-xJWja`(Ii-o{KAdWT=%3QVqp2bSp_qELz zpE3t;DNPSFwMr?umDd|*| zR1m9-(>*cXwt{czJPR17Bu$2qg;zJ5(3Y>zT!yhjQLt{ zq!8b`pUQD|`IQ902aD zKkA~-+JC&mmNPD@>>x5?t#L-z@%u!zMl>Op+l-WMHAwA1TBYEQGA^IzRg;c`KWY*1 zT2bxAvsq||D_ zlaWL$jWvQT!mnmE#L6{4pZcWE*Gufx?>%rX3B8YpsnK1ES&uL8CUwtZNm{ARt*%qO zJXS~Z6Et)_jxhTG-YSDetUr8&Or{c&So;wdp8Pc2-`NO*eReoP1MSE6J$J2-S=-Fe zZ?af+Fshd_r3mme@V?;q?iaIqLpTt3r6z5g7B>~;=c>E9_EQ|^UuwZL@2M@=w`EIs zPU&FaB+r9pw}z1;rQ)%XK06Tz*>+A(!`^E9Zc%$HR?5x&_5QNFa*);+#1Y-dn_!=1 zBZ+oAui)lJI7S~(+;x1r?U-)6_lX%5z66@|3GRa1dEWmToIMA-+4JL;Ux}8v>ETNg z@I#Dl@aVPdkqwi(j-aF9F%M;(j35rZq+}53E@#Aka*e`jS%YcoHnHQq!M4X(NiI@^ zfGIYi!x=xtpQ}H}y~G9+HAisS${oK_P08ksgsGY41@p=Xo+1h3B8^6G5)Ab5NCa9e z7l)_u1S;`QOB>3>brkvvdZ#%K-ea-Lj%djW zN_0$#elD|I6X8L>mbbClFHS!nn8UeLAk@j2kNJ06|I1eP2V#zr}!t*MiH5+(~?CrB+ zk=>tKY78WVF%4+^n1PsmQ|v+(+rArLAn4+8F-d4`@I zoY0Ra)YUp?VJZL9n0!6o^ad|p`qgU%cuK#5MugzeO)X^L!V;G$t?IY{!#SP%Txhh6 zp=8pd`5t3dMqeiWgAvZ^4gFsxLl=^K;YcuHsH?!{3Xh=`PHky z4E5u8Hhvrs%fLckcu>i9l-kOg)JndnRv_*1OOSc^5>^ZrApYoNISmKA;0F4ry19=W*zDmFM3uf0|_0CMTS&5J9{+Rr` zX7Y@0t=laN^O}3kp}>_eTO7kBXU*HtP!~@_)6yLdiLnOAI@*|jOY@BBg|a8`$J77v zG``%gd!{P(5)d8NGac{mIRgAzPyl94##CAZmMQX?wDasxeZluL7y)~d;S^u{57gsd zu7MsXb}S~e+uqgMhJNWG<uO?dDg!;b_3(L|!>_%W;-RB|39bZ8Al$kh=E)?_DIpO?;|CDUnBA_KR{jw^o(`qR z|HQIkCV55oX<-$-*5Y`M-2aCaKB^UC7pc%>7)fLuPhXtt52RSA!S@%j18dWcpack5 zm|^R1<@5>sEE+4K0@C1{8s_XL%}%O4IIK_P`w>(DuWyT=tBu7hTU@?mo1NK@4EreWl>Ika#hPjaF0 zEO(HZV9j<&=*p}&l?LekEsXqnjH3}e{Cl<@?~}@Yg58nt7Va<6P5-9Z3vi1jmLd39 zf3(HHA-h@)ZpCg;>v#fP^h<`Ty0P2iJCQiVFyyZ|ek7Er{Nyg&fgiZF3Nn5vn#@AHhep%X&y*Cmsnh~uO+YNCPeHr;XLY;2R~&+z{Jv0!ky|>3P#to ze1_`~ki^khBPt5VBcF4$bqKGoJHA^Le8#wb*3 z+i5e(e@kxJP9G40v{*^2&?}3y#3h2LN%73P>wz{9+24Ts+K}GjT&^UvupWKeu+%Ri zjJd3uWN!;5Vc{AZO5zQ-P`LuhLK9={y?DT+qR-RQ*eKe_G2~env#$oDE$rCYcC;gQ zTf}MSYm>WHI%E?FA$3WUR<%6B#9Rf&T85}dhq)AKFcNz|dY^E4EfO8gxX9RkDvLikXwMl?>d?mx4lsJT=_wIs zPA=g3b`}5Omi9{zJyDai(b9g;Cnf#usTB82EAHZZZE#NxrWz{9a@|!W+r<-1VBBc# zYI2)XE_~b|mV;n`GQ=0*4_KL*Z%9onk;%3HhGFRa$vR8;c8FRGlpZ&Ik(S~q2X3Gs zJ%(8*@<-;@+HhI)I6m=N$uF7#f`Mhj$`;Vz0EG6e}hb?3_OndMPyL7hrh zbd|#7AL@%-xn{vMR7(iV%g$$TAKcz z$4QEPhg;fHS4Az=WMJ~Pl2Zk&k83}fmz8p>18Mf;I^Bb&uH5@d1NX#r2jFU`b>QXkMN1)A)#p_vKtiWXF-^v&(@acqt(J_8q!or0TCxb z`neHeS%cU%W3i%l?tUB(J1o}pBZw=3{&9$FLwigw)X+1pL@7vWf>+wlo2a3|dyT86 zSHQZ!*z_uPGKAuiTqRV>1$wGTE_Y?tq^QS|#LsIQ7rHlPmQMTW+i$Eg1Aqn&RU~UU z^diIGmhOs(+jf5fk1x?C`_GBTR}ujyvwD_oN%p^smS62g>m_zFU5b{;joqWyV%Scp zT!6-VY*k)&tHf4>xx)W!y;ds)#Mw$w+T&43&sw8wEyXtPNPp)nIvbMF+okR_uAa!yH5j zY&L{ihkj#+#m5DzJ$5t#re9lTO2mTNv(nx8*Adn4=*_+4<)tQIx{SaT{N|5~Oif#DvbEJ(}6Q=wj{k2l|Zk1A?+_rcVU9q-Y*hOOQS)oXs0zU7D0 zPsIZ_MgSZ(L)ECmmSv5Y6b>eN)S~L}2kU3PNN#cyE^5sc4A}qT2d41r)2FZI<$r_P zHSR#nv^QCp9&`3DccwHFzrV&6(ZqdCDRCt<@HCuFec|)*tWXtV6Cp?#UE#CB6}P&O zz_ssyrW|8=a>{nk`)+xIQu286;sxr1uvh|x>DMT+Jpco1tw>os4=`-uJ3C`z9sh)gY@gC+=BcENjke+0WnoIJ!OhnQUSa4Z#qvTHhbL zn)3x|{$+?pD##SO_)dm6UUl%U$71vRb`&tzm(^5U}*2fVs$Hoo!d zl!$jXD9M4EIbYuKJkL`+jlGhxv^?BrH)zewud z05G+ovXC-5j)>x)oxbH-OCyF&+2@}O8OD!t!_XWeZq2ruR)y@39J3S`7D>$-&15g4 z?g_JJbr62?^=u_Ty{kD;-XOpwv#X^#*$*xFCH&|oyrq6Msv6p`ZI-%tBJ_&zLR7%b z8H;3aCwr>A#ZJn|V9z2mt|bmcs06q)B-V)M*AZ@rbOkjhBO=MRzY_RcIM?urTN4Im7CF zTLuCQwgun?GY=AJzK`JTuUBB^$`CZvfqgP&AZ>(DssLKyZKp>=zP62V>iVd4xy}JY z(L_E9#s?Uoy31n%^?|3OteO#~6?O9Wb?o=OWQ~XNv!3erS9i%D#0VE!r^jP0V>WHU{G;n&%~~xPzP!)u=!qzFJb_K zp2cgGvW+zuG&-a<*1#{mIV@H;{_9pp;J}r?_^nNcdbTijoBfQ(SG(VDeOpk15RW*$ zT6(SJg(sr_!Pu1Z)5n=T_ghB=#7yfR!qp*@B=*LLjeTWg?j}#M#pl#ed>iVb^=}*L zBLpT5e|$9|YD3p&`+flm_wITQdVhuf;3i1k;_636D9h~6pQL*&HsTbmzUB9KbrIS5 z(#L81k<8*Qhmo?M+Mol(?oSnI@wj*sJWuAm3Nt1@J>6CcTCHC;mR0#-Rl%Bk*;wS3 z>JC|XPD)SmB&OYMF&=qj0?f=}!#sd8G(79q^HqC{Z1Rmw)KrA<|p z>5qPvZ{Yq6T7-e^ZAr*&UqXI|sN*;C#=hz2E8i7*2_)TgcoU0f~y)I=W zT3O}RLP+S6-~iK|5Q&c8{P~CxWuQgWYZ(%kTJ1*$$xH^z+npA8Odxw6$$PUaURuO* zpE5o2!x&=HuVk+D$_xGHrvpQD-mm#jmg-J9POk-2Uk=cB_#MQ$k8X#YkEwnG`#$+E z1qw=$cO8oQahfo%*xDG*MJe6bB@`kuNKDp>xst0xDaPRT7xWr}NrlyJQH9vL$Ii7F z3nP0box15E+F|6W&M}IRu6+l-3&#ZV{7kH$=^C|-JjTuAGBYLOJ>rWFJO`+J4Rec1 z83vtH=mB%y13{k|A7{!iM$z(me@Vh>>RI;-#pQEI>wnJqPFN=&#%W+iocnljgBe__*_mMeqrAIs!jC$z?G?+goqOP)UwoanGohdZLVwmiWXNqq56^DA!q5u-Y%O|h8 zY3RRlG>?zV8v(H%YiHs>1|xqP7fUjDGM>9M8|#cw??`MW6#ahS4juzDJK#g5WD;6- z+tUwvZ!5Y2$75gX3o&sbeO6AXB1W_4g(e|U^Tu#p!%Jgg2PDKfQvZzooV%AnTkk)e}0JHezSMUIJ+mg?Efij^W^Tw>>b+}xEk;Yd9Si5jbQJ~HHdTknF>dtAU3DnF z#0~_56DjM*O5Q3Q$QkKn$Dbe7JD!@SKhn1)>MchKKM)2t{*?zZ^R+CsY{>PcBjr%C zu?V{`y)@j7F5X6p3?FQ^_js%`G+}Sq=&8GvoA#xIx~q4eU703#G;4Uy+^}OU+rgf4gb80>6I!l$)pfH<7cxiV$q$YCB3~nF*V)gf z#7~1L!wvo@^J*waeUH_YCbE`b_`RHHE+dGA!G_*fwpu>jWkd3Cv7{Xbzy3kpOEZT< zLK=4{`YN<&eJVSW&1c(wPJVAp(9-KyULXee(x3yr$e{^b={Vj#tc9Cr=MH}7T&`HZcTaOP+|XHRaEiq|rG@4( z^UKfhctP5X>8Pq#x%dPM5rs+Yyzpa|jMA{6r%od<@$OY$Hq_8aWw69GP-unpr5fFJ zEZe~ND_HK}aFD7;@&cYlMR8btj6%hp7qMQz>H3#*hwTw~CeaC%UfI1J-cHMb+qBUq zZ9u<2(eT>5pYCM8BL*?~p^#;zyEtBH>ix3)kFyBH&l@qzML1Y~b9q7oa{F-l5k3Td zu&tjHicsG(RL(b!%hSGmfc~UuvIw@(hmQTxQ;^g))F5$7Us&^pv~Ua0S`)~a_cRt( zh45thnKZYS+=0Ihy&KRPSuswxVygDA*6L9!8k?rY(S z#7f&#NcPFC3NjRfLI17X#gW&jPfr32VY;nOT2s@aJ#jz4O2-wEwK0kr+MMsfxMGzC zC3bRRjz}oTj6rPo31sLg^exXWzPF38sv~zQ8;Qqhw$Ae#f?k3c z46fL|#_cYc42ZI@$-;EdDNX!s`$)#>oP+nS+Ymx)A~_Z@%ecqzO9W9OogloR&wefJ zJibh-fcX^@KR}hSmZ0BS;ghb7;i@jcjJea0BSkHYBgjlrq!N9=PP2hAM&-$TUYU=r za9N>|9Q{6q5}q$GT+OiH__t?B?}m?%jbZP`&SQO~d9WcNoHN;FXZJ*F+sXRDZyl_w ztgo8Lh8_nnPzKfT2b zsa(J;GR4ShIJd--jd^;_^XAGC0dlQIxD+GNRnOon_sB_KP#6md*t+B;DiFt#3HvU8~LV~;ELk?q_9 z=ez+g^n-ZMfOY1FV~v){(TI=Cr?%Di>oHaV4}SO>4cBy_%wcxX8sjZ6LzctTbeXaw&$AP(VfkjJ$iUdFb8zkh?9=vsK~L_+%TL3T z=~}|In$Des1IM28A4mkR0ZoPxk!lsvcyXOlny5-9qDr~i4u2>@i#mxG*++^kZV4GaZF1+3sWEEW>&hL+O(6xS_3J zN$+2`>WYO8Qz5<+WWjCUo!8Z=ejav+U;Ta1GE(>n?jS@WA?@Ot+uc#}FCQ{hzq0bS z@8H?XUy-Fv*na?Dfj>_~num}OH@bScPk?HR!J!zMd-K#iMs^2qYOn9J>&FDnHSZ7j zPzPYS>2XOF`Dw9GrJI7;)#HmK_7;ui>zhpabni!VKaL;}YoDQJt&DE;pt;#U)B7Xo zW6WxURhgIsAy!jzGWUEE8^euyy&wo*Hil!C3B&asFU~qofF?XFp|H zgAKy_xA3xC{$y05CjD?4E*bbUW~{ErgprVKm7mq8VZ{4J)YR6Ylw0$-SpRUe3wqaJA(Z_hq;<9DmzHv zU9?AR2TgBuElS#iy9iv%{FP6sZzU$zcwHcQM3{@gc0^&F>rA%%*WtVOi|F{BaCRMu z<4C*)Dfi0lXCytM^av=k!d0aqqsGF!eBTRQa7$O@*nCIWYa2Cr+vZXX z(h5KKgO`?z+P)3KNS`a$j2fdAglm4)xqdA|-CTdTJII&7n zc$AFnO9uIePaaBP^9Du?3or2sdR+lgBnAxN#CIX6_2Sl&hds3*`_N5ppsJ8E5gO63 z>Gdd3>gVI3w%{-4lth?zP$qKcjL+HA@m~};JxrurFa6`nNPD&I2}MS)35(>HxpQ-$ zKoK)`B2l-il$5Yg_c}}-ex8VvWM)sZ(6TO?F=qO@vt{aWdnOgjcigZE)rh4Ng0~kwEE9_?7!xT*e#kDbL24U3~P0}#T0MAlIJN(05X;HU{>?L z%=)KhFZ3;ee>p69DNY9Q`clLjXkQ@-QK>0mDwvGID-aSQGV#K860S3?p2R>^m60W!+z2%_e2`y{qq5zO_GpRzEp22o?!v>^SWS(uVe^*X1c7)3kIgm5>O74M8;sdSrYUn|#N_)-`UCqM z?ORyEMEn=cT*LA5BP@X}+9|6QMxfe0fA=v)riWT|$=b*JRqrrgw$XHfdbyz?LZev&iZmJaNoc-O(9T zA|#)2TG?e2sM{c&2kUVOg4u*6EPC?&5Oo7$^I|L4uun2qA4)> zE5jGQ)3TPXo-=q|WWkbJk3h>yAUbrA>P zKSrHufiKZTezf;1QuxNj^%Ge3D1tCjw(%eBiR@cG+wA?+$Yxtl?3EN?=%kh;61fgI zr8z><%c3)1d^;*9IeOJ2?3UQ;A9W}?_%VXqfsnxpA;9;I1+3hi97_ZHLWQ!bMD9aI zluvca5Vgv4Ck~7%DsuZ&YjS!;h40w!HTU&Hbz?Q4_0GzN4C4i&wC?(w{m z>uUc~BPEZHmpf$!D^ z85`YG%6JdHvN>g7tVa)5dToe~EyqbOX4z+eR8s3)dV96gfQ%uJ)K`9nDs0Q*B)Ij- zCgSW>RtDPd4`NgA`r1d{@%N~`g^s-A)wa5;2Uh=>@1JseOmvIS3U!tbyx(E;Ph5q! z4=L>9BY<|vcKIz1dX?cR08vM;VoxSyMNfICxeW%GRH;!{0yQP_9X?&@EgzYP;Nc5b zz68-N_&hzNQhlA^d*iJ4@`5bT5w*vutgSQ!IZft1i@}S%tiOkUwy|Q1_I3rEc+(CU zl(6Q)vxzmkIC<6${&Ive)CJk%#O1tt{0VX3iWW)syND1Jf|SrP#{_=JQR)nkK)_SN zOwrdn>-u_-hB;%vMaU*HYZ1}c@J(C` zFZECNdznD5+gUBg`sk7seq8pwjtyb`MR^3SyXf3mfjmV$l^)iK!*uAs8UfQ^3TE3( zFfb%ku>WC77W2QSWIcQxEdL#kElp8!UZui`grfb;8v-W%)Lot~oR@FEPSQBUH$N}B zG{rm~Kdn16=`xltmHy7&C&WF2fzcL}S4}O0D&fC0>!z;yA@{u7OHvZhb8_1A759U; z2><$6>YyeUE~{o zo?Ys&_955(MQWd9E{zB#(Lu5adk&wg`c9<3dmX zE)9i<@(v3tdcNMAsXXZ5QL*h&OeR`ON7k+jag%+L4ha54y2VJ%q|-+G9Qi&ClT%A( zlL4)1MZirH3F(h7X&@HK%Fm?kwM9j`HulGsDSy1$sE(c;DH>w1*bRqSf}j@^!84XO zF8K8r8Ld~dTeQ9FfV7nrS$s~I>v|RQ>yHYFL4$5Oy~e0I37R5ji&G}}pgKeXQ8 znEq-sl+OzJkK*&ED(WmYxmJosG_Sm@O}(+S$sIfSa|%VIkGixK8<;OY@^ag$WW8tU z?Cugme=MsU9`4c}?NH9W{u>J9d-0gFZv)fT2>)qd`X6P_+oZpTjisaIf89C%nU_A% zHFjSSzyb8C6ka^#KA5Y|GiIV9tYq^!(rx;IMut%IzdQKS{77*I9QEp$yu(e3%0|UD zk?URCIJIjr%2ql5D#KH@?LCQi^G;g1#Pe~^Q!^M;@QTZ*%NkIs;3&6Im3hVr0snD6#1-z+%tJ$M2_Mem5FdA<|K4_^_N z}SxK;ytSW^=&c{t2@K!bpF`BSWW)K8;yCKiW9(6GSyi}Yzyl2#MP@wJfgcs z`qOXr3juc_TzQGH45Nu5@5^tFhb+k=>Jroi8hyOG6rjRe{rBw-AH77?taOZBdbrO) zBI|9CG5u-4Y_$IZ8zi6PtD^&K+q7u|Yjahb9WMbp!xBxh_V} z+GrmbrIZu@^EhHATZI}y1ErgJ#w&h375MURw6hr=3vXv@aBm2X(s^lH{ui8bz9(H= z-c3N2|D-k5(q~BZyWRHj;Wnv6vhk?=*h6c=NPrGe3;kDMV_KT}mk8f9{s6@0B9}V_ zo5>`4c_wQeb>rR=Ba_125&U`hS*Y(rSGcE}5+~|L)t>)NKwX}U<_!G8pBlTeuOHW} zvh@yPuv==FhaYOzT^^M*Ewu_E6U5VdQ*LZ}trNE4>6WcsL-=lm;Q_KGvrsPbHR;3; z#;rwY3uzxUXzwxo5)Rc9|1cSPbeuT zHbI3BIC(cJbi!6wS+RK$bAXn$BOR|9N0DE`%h^;3Hsu>v1ObSKQkmwsD_rpPh*1O6SuHiazrh*R21b*=zYIvM~{QWtZ2S-W&$x z*;=9WO5oa)0+N}3gEa1Vv=oH^RYYlfB!FmibtGSN7Ur+X1fZ2$B zFv={o+T8ygvJuD&sz?tmf0rWVq_ZuP`YuA1xB8@lPBF}|Q-$7l8Q{tO(t17baut?iDEtV89J|bSr(YJ)Mg+yuYhBD8*$ zzYJS)|Mr)ay~~_~*d+_k()+%>tv`p#lUtEP6H1nb+?r=lurnB$o>}Q$Y%7ofSAGgT zzZQMT3^~(>gVJoth1}`?Jw1yIY&D!f>Wl(A3K#AaclY-G`iphIeu3&T)iO>#1OU<~ zRs!f%6FTulp#N$uV>7T3zrKn0ib?-dM#lcHjQqb7j4xa9ZsK5GCo} zG-vFYlyC+|HfC$;Vi^<<(QJyGjoMrYu170%v1RN{cte3a2Un~CCIM^2m9(_ROJu}K z*rX&Xj?xhBw7OLZ@cK)}y*^PbLvyHhxfhayu!OJ%m)T|EZ_j;O>9tVqd1vpNFt;-4 zUwYbt6haKN(n z$MdQ@k4G_J)XFbVFfXKgkeQ0b(GOL^3+SWuo*%Z>`y55^d`^@8?iV^>+=jXeCS|Iu zW=DUJ8iQ0nm515U-FuW_*S#wdJGX7#m&Fx>LW=8jX<~+v0V>EB@@w1iK zKk6gK=~&XBx6Kp?|DUM)_&?OS+gMt9xc|3;?%#)h_tpQ_&&~X!Fpe^&z056HhNW(H zNJq8RCc?(SZH=?ZW#EkH7LoWSmJ76vBG1jgd}!L)c{C^c72X~$i`48OPSw5-?}?P> zjm_^(g{FV$^(`FfR>!1UPxP-zdk|xwtds^4KD>x~hjwKfg^a$1qAahiIR)zymp7B{ zot=f_`aX>~=e?Xk7hX4gZWp2w>ehpxhvnYR`8~e3&MK67FQ8Uq=*`-bSm6D| z!NHdH-Ho$Yz}4|c0wv&K?P`zG2zq~gRfP?`KTR)h^}ZbJyc6qv^nq?ZiHSnbC!Wf+ zH=vGlGh!kMt&rR2J#FW8(WfW==hK&Q@2;oKDE_+qTJJjO^A!k^0DvalsfcyIeR%DJug^+nP$`{GvBU%*A@ z_}*D`0=oiqh#evd(Dl1L(KZG^cVF2-<&=RpuLn_Yh`RgSKEDE9AbZf6?DF2A``e2d zn(d9^bN8%=(--SR4Ac)oxSnp z{D9|+trz|A@{LS@&&}q6@%qa(U?Tu}F`^;{DL;F7>aD30?RmUCx;uM)TzFCu+iErL zeZ9tpJ|FD8?k-0?B|tAvPLB2f?a=BvXjpfKZvC;b6#;9fRT@hb_e5GtCjP|ZB;UmF zq}N1G_Oj{nL}qUO^3@YX;QG&d-{QYr#6jh+SR1e9LcH9qr*K*!ye8y9tb-Vvf4q@8 zpi0Km8zj)HZu$H>rm2nXS4^KDCUv;S`1NSj{WD9ZYaEho0L@+C$&QHrhb?fzazcgd4>3U2CP?^ztY`x zJ`BP7d-fUicc2}SR3G(45)T;4_GFv7F&k6#c5CnLbql^Z(0fZrf4qSD&&%qOst0HI zCvi?cU*?9K^6yVvwcZ^DiN6Hkc28}jzUW>fL8Q*PIPSL?`lO8^s8~V@7uIT$`~aqI zRtJbjFn{^UnzMd^BYLwVOjSsuV+asa3rlEXvvq0~`Ed(iqrdr zrkZ>Nzr7?zY*GJk=EgYVw-aQ`f^s*^`Bvsh-1zlPdM^juE0VOYhx#OJDy$Bjiqi zBJr=LqQr#%PjO!!59Rv*og7W2sEEXv7LllgtQmE*(V$Gl!6;)(ku5Vs3>nLF-7|BKX-?<-UeD`!J+I%K^T(XybHA_8=lxl)`{ug+ zXoBKS9fvy(SNR3rv5--t$eZ)XPYQfzh{$iM!+-7ByD1#;$2y)fCM#3|AAL^Cye6L3 zGF&2hGrfbhCQyO!@V08;e!Vr-E6&?)BQJLk>=hvReM+j*E}nh2yT!Stw-eQG?Q(Be z1repE8>csD~@)EICOkZMt}NH)iGnU z#9hQsr>wE7yXhAHvNfn>YX)4$MlM|_KiCmESdX36JTY#rH|t#i9Hu^l7!Os-JZQwQjdZ29D%EF_e>Ih`5X7 zIg9OReR+d~^NAnn_37{G%RiJu+uGHU@&NX;S&p4owcEunS5c@Gx*EY#FwePZ2;DrC zaOxC`{wrOICtsPut6cS~cDrpbb_G2ElJ10GCdjomO@jT@}&3vW{ zGVZO~bf2g3y&l8Ok1Dz!ylLrvaEE_cxa6|%e%G;~(f87d{s))sXKU(b{L#qISY_vi z{azdPD;j20^NQLm30~#TR%5*L#*^{S6@ffSc%CG%$V@>-@TyJs{TJ36nB_RtP*DWFP(6vywOY`%`iG~+^uUgDHb!{N zw?%|e0ReB%YX0$X)OdKk_58eSt!NBobA%SlEk^{xOd~)5)$!YfqwK<|ncwGEM(M6r zOyzm`;t%msgUh*=v+L_D{rGD6uY{wngx3eRXmU zTlyiScC!Wi=B`sVMIhk-5qp{n$R)ZHu94{pXU`p;uIzECHU55HXyznyle)eFD<>zW%9f$aGBv{`~Ca6&}l z={||4TT)w3^_rc2b6;05wX!~@|?XlOQz1_Pji!DO^ z%AzISt?os>vm9MxTe|su+2#;+W4gV{IpHg}{uDUC$~;g;=9?ynyK4iHk$9xAtJSBk zD-XLLuNGhx&$889jTLV9t<1JS^jRV*;-fwC0`DP(IYNN#T!;*r{dZ;E2e5wm%>~Z>>A$9$9xbKe?(W+ zm?E(%hQVE)In$wrgVy%X`ICXw{)v0riS4X-BJK<{Qyupvpm3*!=`-bZR4Pf=l zQwV0b^rk$&L|1LDknRv^nCs~6EN=6lRId+hm;@1~ zht2oeq`!4MUn-D|M>_VGQwUbL^m|B0cHn}boN__Zrd)FPG|7_gX)z$S!zU{ayQkgb z47sYkYBNW$=bV`|YS!ocr00sal^*6yB2=rTAIiftEojaXL9h3TD-J7&KvMp`(i9(_ zj1owXdw6|D#^fC3>l#h_(YflJ{RNY|FI zG6aQ7=U))KRl56;;A(QsW_CO=Ba$AdLlMN2sivBRzXFggzw$j3@WzuxC9M3^%ALE7 zzWp--N$yy^xYp#eXVV{ze4J#9av~+Hs#G8L{B?|~Fg|W{yKnLtQ&H7{3!XQI3S3JZ*EI+>TM{IK z0%l=${B&ASuO$MnzK0I@l(0b{I4c38gldXVK3^l3S{l^pn!m%iU*;$$hs`S;)BKbt z`_e5CRb>JKpeh+=6sc7U2yo=swA_Z?hgE?{2|-P@x?qz}vtHpyu+U;VGVe>9dTw1R za2Jo1=r5Pw?WgrCz_r&`$lf1VOVDrnjs6GGR(gOPJ?=)E&kV_p5 z>c+2s({;ame=%bZzp@aiUGG>b(11tA1BV#?mkVH)uuGFN8W;}X!O)B|`e&y7m zH{J>Xn)5!IS=&Xm!4O3Rfx)|oPS@O70jc$R_^>krc9vY z(>|lg{2M^#3XnM*?!0Q~)2_4-_cHm|INg=!?jGwM&Tc+j@XSHz&c>>5a#l5Q7|h^i-)TH%QJEK2MZOocUDKKTBI_QE&dt5~q=zHyn3W z(&evnNe$>awc|pLY@&Ndov7YgO7<6N=iFejQGq3fdUNj^@&1-hjL|Yzvv!M|2g&VD zAl{7(rDz)aI;G^#Y9l8C?o>?q!M{t4WTkj+tEw z4gGe_&1rq@8_oAbsW&@zR2=XwJ1@_3XWQfSKa@qB_qx7lt552(tbMcZt(ClVo1M}n9K%e={+J<6{n-x8(cfvl*6#X z)+-=AZtxT1uk}|d9Z8^KbVDm#_C!5v{t@q`!uK_@{4{foPf7?v-gI3JdyTFE^;t)+ zYTbm?)eJ)}&&B*8cKY=%xf*R=qrC9h_VhPRVt_qK%Ru+F``{J{&;IvH_6d1E>Ye}y zbE+cKCz9+3Q=I z%!2zd${tVEg{gMUuz;*65_3qshJKk>B#~D-(Z%Udd$@a28BuD=Ug9BLNsc~qq zutUakuXBm-)e?VYcIbbd5A7Qd=}a@aFM!q4h<haRhWuR|%uMg8Bq4{sE7i=2RrSr+>Dg*vVuma-e^b`D7GZe2}&DX`&H<(u^mI_>uaw3*(Q;~Q4k z_5%DVdy0N2pWH_trH{GUTbzz+Hh-~euQ)9sYHc!Pf|osy#0;oYt>npB0vq0NBe)GK z^t}v9MW>t%<>PPV5o(1I?AKYln1$Ltb3-PR-4s?2X5CJ=7}c=&zOnUG(rSkz8nYNH z`6!f?yjJ< zTpIZ_0?m8dgyMhJkxh7Ty4tSFjQdprSd?b;`K!(L7U|(gg?o#1Gh+OdUYn(!E%>zp zgPB$Gl^MJrGZx8)@~Bo%SrhYtVqw&*O9-fNb}zZC!lt^MNs~QZ_AwIkAB`cUwCF|w zawAL=2v2(pBp_1P0iXH|iLuZaR!Tcf5{M?j60j@&LshVS6Xc+8k6R{E*3MJg&PC+5 zG-UEScZFc;3u1|twWfuQI46++RqoJ;!nVAip_33oVkggEo!kfw$Yc!^=0zuQ_ zF(<;^+vzW^=9dY76G%3HG%0o(mh*!FZ8(~NjlR9cK!$2T=l(fSL(=kj}1^ePtXONhcnzeFv zyza%kH;XwCtn%JoPwOn}zf$eSp0N7q0(_R?BuARw)?p=JU zx+Lb7<|Qln(@4Q+WEEF!m>g5+s|p$l8vwO|_bU(oR~Uhn+1rdIlg&L9){ednPPa(k zXOSVn8IYq;W{)d8s|_0RwD%0VSaQv?#7mtkZGxlmsaBGhcHoP%yzX_pH|scj!ALyf zKFon17CX94K8JdWz5qDI7_KXf0D77j1vAHs^{)c}PH$pR75IegsddoF*`Dq0|$uvJ$2j^rgvjDB~ ziq;q`Eie5cTN$`*!e90(w+;sdvFo&=4X&XpPAh~+riH)=zRV_js%Oyhc_JcW6)|N4 zKdp&(Su+O@R@d@^L2fpe3F`?aOPV`d$w%u6lJ&UVRWqTmmlU)j_+i`z{!=7gI}!&3 zgGwze%+Cpn*q%P=%0Qk;e?B)ZCD$1VVs*8m-(Fh*O1+Wb1}ygq`jZNWJ_O0$dAO-E z&}7p8EDSJx5Os;CV<5-><#kfoNdrM?8FP@Vjwy)HltrpvyGIRwaIQF%e9KG0cI+vr zK!>#~jv(0~j zodg%N5#oy^a#@R&p!9J_g%|0Fy7WaASpE4q#qxayg0y2ds314nc%#~2qUw`~B^po% zUrM#yk%frZ2}!85^B!)8CD@a~OPWGOdys52q^B#D$D7L5^FCeaZtYym14r-Zd}?WV z-EB}R`)K|{?rgTf5KucQMt%_J9ldU(^lCjMv3AOTy$7cRV@#;i!t9;0ST}G86vG7X zlE<1{=`)m%m!(KzsBZxq(e8p|_eC}s!<}64l)~OmK`RK5nsTE&N~3HwS3HeM4-mqNpZ=>o*)*`4_kBU^F?4i^ zR}*O7(kKO)FpgTwAo96SbjEmT)<+1z@~6KoH^RDTL98V@n!-TXgHllBM1XqAnID!R z^$2VnTf_=Q==~z@c7S_^P z+H={*ADiMf7_02jk2`NLI=;%W+yGZ@u&Bj-u<0^U+4IuTDnX?w{!^bA`PQSETaUch zR61n@M~!9#d)f-sW(D_8>>`#NrnDTPw6L8q6saHoQ<_*(`M>}duQA!A+@b2ZOvNe% zZIvR)&e0PpP2*B=xi1}i&`v$hMGCdjBe}tv&OLYIa(kIypFT>hmOfKdBRwJ)cMTJF zEqZsSt&m`6Ij`ziiT=LJ%&$!iSAmf4dud4^WDuuD`1G5#4uG|`$K_hdGiaj&)wncf zZa&!R=76H~tIf>tfr+P!fJXTXt;yS&&P_oZJeoNlOEnd?F8!5O)@;XeF77s{i>YDc zRPHQ$G^6JBEzu$S(uq*MU!A|sI(;8hyTA3eq=qG9i?{6&`IUB-5wW=V3$&)lt{kb# zz`gWad%f9?V;W(U8HTM#$7ax@fDv}6bUQdU;Qn!e=JLGl2-dwjV*~$3%GQq*c62c| zg0*_}XoJ1<^Y2GYMXXC>wVLIOhKqXInL7^V#PTb`J@b2Krq;JIcP-pHfSJcGY$Bv3 z|8;IQwDXBey~P-_*;<~0wB(c^aND^B*y){Qob(Y_@dn-uK-Hp!(t9#9ESXZYevinD zwylL*-i*k-Vr)pj(2?#VWNnh#R+Vap(r?3c{Ev%(x#c45=9fKdbZRmU`SXnRQi4NnHnbJx3Je40 zBHBlW zGMBP~PiHbWioe80H`5rPsz7e=dHK_sQ%YPR>MO(`g5TkedXMzebc_0VA>2GUy-Lu0 zvA%hLo~Su_ba&ETqu!z~?GR~SFAU_GQBP@1x_oOnLUQZ|+aOBI*23_QNAJ*YUWA;> zoHy zt80N(NWx(6A8K=-ZOvpGt5Wx)^zYyvPL&*%Z-neU-KdzhKWveal@l&I8joPDyZf}# z*78q4q={s$08MXC;iK*$MsAhI6NfUZnRdtN ze&QX@1NU-%LvZesbf!(L!2P?`E;`nwfJSyb*^f$Dic{W8JNpTY2m7Iz>%CdYGP)9M zTM;U+eq&K5C@Ks`GV8(re@z%W4K^o52oYwqID<50xS2UtvNav{w)mSd{{S(vTokn%oy-c7GVZ0v$Xvy#Gcv4sS-A)zJqK{@3LwCMN>T6 zSeB;H4KAo|v5ejC_m2>8qT|_#4itrQ6t2N=MbZXCG_xY*CZ;os1v7xyQ_d4G$b%vR zQUZAg3?oqXF`Efo2L#z=Px3q%XO3t9LRY;2cY@{MF$M*uU{Ga1KI{Y0gN4e#uY=HB zBV6`+1HjP5$h%)hsYOEs7Y+HP9Q{oVm@T-ZF$ibW)_+_C5Y8;%EKB~EArjbpG6Qtc zXfBcMWryhgboN$W`Q?cqzl@Z{3}GdSvPONqT@&5P9w9CpV=gsd%#7v zO0r_-8t90OM#CLD|GN-|VA7AVqi-G!&}TNp;EhwOTfzPLda2QX$xiWOXNFo*Qn3U~ z=3Mwxi8M104#J&T5A1O4+se~2f?e7Vx_W_L#x2oqBeb*IR;c&Abh3j`{SYXmaUi-u zAr)da?<$#@*>vkL)LRT_AIj?oBT~~*cyp?vvtcE*CRa-=N2Zr%(0xJjh*peFOF#aWZKawnk8F73$+IgCe4;?6xc<8m2a z-K7iLOMl3pvMZV=St}r!2?;rDL>!I$6f1@PRI?GaqbCbeRWUX5_kTmbX;!F7SLZ~HqvE@ zCDM#$e=2F`iH@S)_AmD1Q}+9&rtF(RgVpDovAIA=*#{_M^qPCw2c775FX9QZVCN=j zD`aeDv!hW4Ypo5on%5b%H6&}>g$@rh%~^~I*tu=_*M-_`g?4J&2pNak{sTxSW_;C) z0Z@}*M?e(3V@wr?+Sk3IYQAEZ#+4He{{RA)1K~l^$;XDtmA>zl(pE6q(RzntE!m^F z?oeTqe`s$(`ZtSN^>ZmMcI8A(3)v8Ci!B*L#}=pHb{evE@mUHhXgGB>0vW%w5U#<$ z!;l5Z81RY6+NS-Ed0{X~?`Kca`w7WQaf*9s*n|LmX4^Yz8UnRO_7MEo@b4Zz1T{Xt zr(xQGvA*9GUuN}@TA~b-Gkrx0+n?OFFqL#T)NXW8v^4uI0X%_Y-KfjQ?$O*PaBQl z6fogfnnImzi<2y*GvJK%*v{#vGE)^W>|J;A1j8O!={mF$G$^N=fkZ#mKJIX#R)%Dv z4JOzXz?|JlAP81Kma!kXIn<`4G8B#kwZpL%%)uZvwq0H8SWAxqkN+4C)OHe*8MI)b z;;|Dd9`~{%8yQx^H~zAHV%x`Su6{HGgYY|GH9y2H*qA}wGF$QQB*JM2&(5%iz27XO zlB9Lwp)cHu*}ArXR?O6cDZqYC!ZsLeVpztkb}(#thJt5`|2KiMGJRCw+2Gm~*q1L6bQ2xHNbjP3Pvi zOJk@tE+#9QQe+PjFp+cfcdT}ue#!>10w5wOmvkBL&67|sLsip^CBZd=-`y=hsdQIa9{9y&&Y zJ|}+2QbCvDJHVOk$!Ja7?9kvu&_jo9DuiURkK&g}`uw1qAoY)nKS0>u%t{G$@4+_@ zC(!-Pr%uh?9@OpKbo`{rHCt$7sPOfy7 z^)mw?oOZJD#O(1aT|ZFa!=LoxKv2(|qy%fdcN6S|wo}kkS?mG*F`b%1@dchd&&>NN zhS&u3dT*<+D^ttpiz0@3q$)q{WT;8?{ZxK1fK8VflWNt%5Mhh?=E?-OwQ2#7k(cEI zBw>PKMM8Om`BbBJ8afQ*&Qb3jgDBtag(G=_gKn29w3Fw3cF?2}Ci3y~0X$wTMHas6 z47m|;`(Jy@&F|SZ2rZJ-sx=|#*vK?@zm9B zWv!CuO4Z(!^UC=d44274f5@ zkAIz?)Vqt;SD(ph6Y{=CZzU(ffub@YtR2}|Ohbj!TjdUcB0NO0Go&0EIcI$zhG}oa z0`eEy{q~QXdwp<-B>c=UZZdMqluMc(90yK=kTPK)RHj@`l-tiD%I!~mn{aqeVnNjX7UDP| zc|Q#CCkI6C6ZbK(1)i~(2ZwR78z&tyW$0&pmTiS@RX|}vx{2<^uOooeA(+&(q{w0k zD&860752sQE*37RVlv=PAOO|XL7SnQSx`lDI6@fH2`1(W z{s9~piHkL&)z~macETb<`xzpjUJ=2KPSVLt!(<9nuf*!WolekfK)pgN(!T9HA^9;* z(PfIR8bY*af-{R5G4$IrAA1RxrTVHHkmOo$IjoF`|JuK`8`g9QiBdA zTJ&?7GQw*Da_%Z2xe=#9twG-=S`4uzn(Rj=#-`RVO5$oj2!-TeNSTS>d6?~9AuZ4Z zSS8VhLW)c`OwmdocFiWI!^RpwCB$rM7V$Md$0)-PTZ4W?D}P07vwFX{3{*k7Tv3e! zj>c9rhmf`uQUZBW-4wb@&Gem&7w7>az0-o#xcCPNxL7aRP?n54u0bS-O?z;{l@yYn z_WRlHu=NYkMw38b>?xzLeqa_>g9$Ii>uEbr{L1u)F@TO3# z&D*LJsfm+0Y-KZ@>bRtHRhq%dNI-3?fRacr*-X#vk;SH=5#Cl00f@*j z8zjLBA2L4s#%EJC`qj1fEiZ`4-M$Nz+v&Fw0-Km2OYjsCaehER-l{F^Z)6W4~!O zDTXo46Kyu_qupSVnh~_zt94@Id0Q? z5Wo9z2}>v2$^p*ysn_Yp;fj4^B2sNZT{nIq-sYJWA%*6nf~3*stHHeWgH;4w4}vkL z#*OH=|CP7g&!7AH23$cpZg171z{3=AEypk=Jow|}V`5W6d7{~r!hywQK*E}VguM^E zxMjjKq;cT<+}0sC!8u;J38tTKL4MZG0h6D0j%n(Lfz(rkM6Gn0pRSs9aJwb0g-Vp4 zGsq-A=bUvfh``lHysZqcENr|DH*MF0z>PI?(9Gpm*bGE6ArT@FN&KzI{g*^+HY`%` zTM?sIL~I^Y1ce~|DuR;$3x#E_dric?MavA!nvC>X6vByQFevN%Uobv_f{AX>D@Gg6 z&BRk`ia--8Srl0uLayTy*3s14A`18UJxaHPsgvR8FcoOS^>hGXo>1Hn%`VGA%x;L= z5B{&*X8OJx6xR$HZ_jxR>zdy!6NO7S123}&Jbwh6Gf)mWmuWy7sxy`$6jvs|;S{Rn zEyfz_o}DM8JjEH%Y>GjPX@=LROe$Ojj|Xpv*cP-5bKtrFFJb+`{3dH68)_d&y-0}A zY8&lQ+Q4q6dmMMejWCJ&BQl%VmO$|Ujj)5&JBZ}$DIFxMtGm(neV}IUEUeP;S@r{N z9ZLOFTX?1`!X?bm+M+)7Zbk>;;ASgErzyhyx*KhXqdOiO9RmYf5!*~0!%W;~Ves3f z9RsPC2u?#<2|Y^W9JmXnUt()HLH*H^L(HC#1mhTGQOlf%@OV2z^ZeFfZ|W76GQEmM zg)2FwqZXb`aP)nX)J$qeO5E=SJS*(Szba)fCph;giQ%LZi8d24q3DPvdqwsLB>j3C zli*V+@+AUo9|!#abC^&w$drcX?C}s{WR1P!TJ(@>HXkneF;RFTCJ>Env|l+BDy~P! zoCIUCtQ;CEO-Mg9okVOCVgDF&fFQd#)n)W3*^bAoqk>s$5#cu?Vy1TuXX2e0*DkIH z4dgD+Xi&>kNBwu|u=WngFQzduK9y0uSYb$kMG&AgJlWY+*uMwlND!V*Gj&*$f@go0 zQGL^q<-pcoq~O5~V=@+__%n28Rf-go5e_MszxS}h+s0ttU@3Se#-8%Ai(@Ffj?mU< zuQCy{8fT}&{3@n;QiQP;X@i9#-VUf;8dMUWsk@2Jd_r`DzOuJXreiTq;}C`83B7Mw zKV-|ndlsh(`)uG+b##sQ-5-k}OgTvJPQ+KOs&g~GIbjh*@)e)^QxXG<8ZniF=T673 zN<{71>4}LkugS3w;820_Z()WDb06s1MV|C8e-RRVb6@Ap_0H8z%-5s*W+w^SMfAQ) z3s<$<7rt~=g^l{oPae@m7tYKN&848a7L4g%x(dRI=Rg1KE}ohKfA>CHYh3(xrf+C& zw0o9LQYDTojCoJZ*Moxvz+bw1PSN7*i{E-LjLrR}iW)uVwotr4FVLJGn(3=oB{ru_ z9i0bPR;j)oSg56U7ybl)oIhGjNBhpmCNK^^m~)D}w19#Rz&M(v(R};Bk|i~IOTocn zJWEA+g_kT}zI=&)bnGe4cgXXDBOTyRRsi&k`4VZy!57>Ya=y_VI*1DXWCd&mXKnoE zh4b71obL&TUVILJvH}{w!4urCLFc}j^Ih1`yTsv7RzMy&=7W7T{AO|P%Q@c;4ZScM z{$vFRfkR&Y`Ssb{IGk@bhTbI&f3gDhFJs_vy-E7FZ@2IP!==*SZIlNI2l#SOT4fXVS=e87E6maGE* NNP~Df<_G=P{{aR;F4q76 literal 0 HcmV?d00001 diff --git a/results/tables/intersection_tables.xlsx b/results/tables/intersection_tables.xlsx new file mode 100644 index 0000000000000000000000000000000000000000..50c133c737aa60d96d240aafb9a337aeada8c104 GIT binary patch literal 32241 zcmaI7WmH_v)-{T|B?Jz+#N)sR>|a*1zXT*thV~99Gx%zX=oqF)u*QQI02GlB5Y+xxhzMU=7)XKb zoB?*uCR!f$04F0hcaUvm0@SXTgFxDk?xINn$4ETsM(186R|DeCv}BF=o7@zTPSITQc!; zL2@NtM2>ai(AJW$-pB-9Ej8v5Z-k*wg|Uqve4{>*XmNh|^dq)&iyIRh%q&CeH2l{RXvYVUP588(2e&iDAV*8m{aM3?TLrFgTj9Bv&1Ef~w^ zJ_QGy&*a#_kI5uG8!i(@Wl=&f(h8++bT)not8XgEu0E?BB$HNhGE7s+WvvR1Rq9uW zbaR%w+HG@aq*A2Lq`I#^knp>ULfO2(AFe;}Shum$R#o;ZNKcqYjQTET{Qb*K4s^TA zi4JZjvyvA2#Z0xUdAjR{KW?tWyeas%f0fI&8lEoF!1WfzZaLRB^eOWv)s>LN^(fZ&Px->4#Zp~?bmuI31~cVaiQxBrKy%yCZa z7oI}aA+PIf%7VfQh$NO#&|UCdgQo|)p)3UWm1mzmyfYJbFDS|4#Z@fZBNx42s-&*$6RMH@V>KQ-QV{;aDN_?#VH zO4LXu>^%D@W7E}__VJ&g)`$?@RlW>_{AIZR`>cHRpF=eVI|BYSC*%HcUxM!@bQdBH zzG|pRKNb8v^IpG}rnY1Dg6Y#X0on_;_Z>7aKHG0ujUP4VQ*;Ttf-XYFnDcEkECl4$ zuxS!kX0{ya71-rBkgYH)Cv|@kde+&taNwP0*6syLW`7R5;aLbZB`GvMszuJ0){_O; z7^1%yU5?QwsIHOH-?kctBVQpUncOEM*##=0rhG|2-u3MN}nha~YIJN7=6^%fdM%kwvYZ|Bd^aSM-@;MFB6oUBh>z+s)_nEh z{!ugZkIfht50`cQB<`@DUKf;m%payyTZc6@tV2C3)o)oRWz>uY3A{U>YtG;n7hO;Oq>vvvgwr|Ja;t zUx9YVUqE(!)Hra6rag-2h-}RCgu^opPL_NwY%!ik<0H}j{%?mULKuGBJVU`7VkNAm zU{G2pzf2&HFs72}+;TMQifN@p6n-!TmzRZo>79TEO^_%bY(>{4xFhKxGLyYgH#bU7 z{=4@ac6g&BV@Jk!!*d-8{zWbenQs&hzt7t)Q;6k_jKEktredMOqbcdtye<-$6<8;b z(9y*b{oW|u(3v1iPo)SKX{cM3Ky8wxz8-It_0b2t^&`F$fli%s;2(vvToz5k9I)O2(cv(l7!a1HqhL@aErKI9ZuF0xUG0UnsG3`d0w-F{<7gjN3Nhyjr2zanq;~ zk)w~KGNNUczHps8PL?*XgCP|pePP9QeS*vA;G3R8H!{*V(Na>oIy!!j{0bx7&G@_N z_mrLOci-pdbAJtug?K+r^Bst#fuGLyFYzId*F)oe&(nPDyJz&im!a$spU20!STXp; z-E?->-KnZc*WI|-^Eotm^@&>S?hg8La|jH9U$(y#7ky%)@W*qg-{Zx&YWDW?WwVJd z{B9F`0eQN=1w$S$=Txbl@3*P4Md3G>s;dV@=c`YT=R@PGkL#f(zR!=a?5@ehVelRN zGWPl5R`qW6N%g|U_wka73bNPE{`~ki=+V<-Dp?isG*=9MdfePy-KrFWpTVdg@Z)j6 z$EGLf^El+`p?EyIOZ@qQ%J2EH@A>{>RqS~?IXlPi*SP`wPPncmo;m^N3AaPIL1J zln38uE{hK`+6UY1>&_3<_At0RX#HF`W{j-vIbN8AX&Nk>ifOXJb5}Z?-@;XD6=|QN z2NG;VADXOgqU7HV+^G5ulbGkHXRrtPnpO(8KO_P_5c^$Fht9>t-cItEs_@1_>3)ub zzru8FvUO326+P@cI7<-By@bM^UcYD#zGv{E3ECups=;^k)W^miF1?{ z2luR_TUC?scAmD&p?|23vKnRuIF^!+duJJC(!-?VHtUi-$lg#ma;Jomdwink$sUbsFQMq#cYNuq>G z_u7%ZeRHFJ>s%wzCG$HB-YT%oS{k<;e{q8)qUK!SED_|g?qK{nlN#kzqPzOAIY3ke zP3ce!2Ve#%2MNCuy>Y4+GE(>8h@`ybnZn-W);;a8W9eoc;17$TD5fH8KT()UBVIan zlD9T%E-+QcZQ2yG4bs^{EhqbUhj{hrbmylulh$TWUmCP<;!E=k>&@TVrTuj6Cfb{` zCl|;CNw%9Q8%ttXcsN>khTA-9VzQ+9nnsaXPtK>!!Myf5pm%@MIoC2z`>G8(>O-ox zHL;%aV8i@OXF}AC^~8!W$V$ZE8Mf=#UMp^x2u#w%mLuGqG$S205p zi#qJ!@#n+r_R4@P{nHDfeROrzmzLr_*hRDqW3?+0$uJ7bfFxtvCu zC(G8^*?KfNuIz7B0DHDBIzZ0Z3T3(kA#92#zf4#8fwgA90Uj`6E0?lCGv3vw>g~D- zajPiPaN(sB@IvvS&I(m~aZGS!LC0G)jL`2mUOBW&{TOH&0Ml2V#iTXOHPKLJd~xiR z(8|#)G%2cLViaghvRhH+o&ranN4c#6Y1Aj<01~)&Rob97X~Jxs@##^U?qiSDe?m^UZ>$4wgE-^TDP5|$8*=jM17J5dPU55PYw3w)(To}#hehu5|R6{ zhz8zro#J#zNzaDv;%ys%ljyFFnwItl?qb9JZBZZ+RdzGyq&im)rp>e6dOPc0Qyh#Y z^YJnhDctOEiMcBfcWPrG%Oo6;#mc+@t^cObkUE(4B!4Z8n$^^VMNuiy4tuc;0vHG( zJFFa1S#M93u8%sW-mVjp^^{6Ot1w!nfb}*{2)hR_jlm?ooxSH}UF7{XXGl855bcre zl|26iOf=sz0>!4X(8s-zY~o5*IcFidVp#TUTU|y=5Yc7i5Uf>~K~Sjqt<4UWHSepE zC@%(?pKF8irSEw3NEqRI-?DAIzxxGz7lsmFD}VNi(tuM4DMvZI>UiFf7$!)2YxxF) z8naDV>RCVDgFq#9=)|=Kd`dLj?ghzw6$$K+{LD+|zPaUy6Cm;)YbN^$z?s##yG<5A zGSP5sAm3&#rU7vMDx~Y^G+pC0qJQNtCJnXQzOFrM&H{5qbAC?IXZs?Rm|1hC&O9TC z)srx-%rZr-ivDu~d(1 zuBl%&?#y?jqr9)9kZFy!oGrS>55#+a%{hm%(ljLNFyA~jT0wi80?h<|)YNBPA5Mu7 zfVdf|mXo4=T+d9q1rH9U_bje25wMrYmIZz$AU0}{4Bs9NH}HPNKON7aJM6a-Zi!X2 zBpQ#ymsqzKTc#+R5>tz=&x*nOrs4I~YX{IiZ)yE` zITF%@_t`f*)4@`IUKId#e2U)6c4Kj{d)Vh+Fo%W zI%}3DeQ~CpMWe0Iu}=n=TFEmS4BIf)9Byul&FirPRD$i&w50Ge@Qd9KRA6~c_}e)_ zMGXnv`ZbF^4Gl0QdupjqGx$D4IO;Ua~hWkA<)W8CmqTj_Z`CAFL!tOU621cI= zPlM>oK6|+RFl)mVoxsSqQ^(z0k-g8?k7d$yOGC<6#*U|L6P;eKYotE%!TD(P!5~P% z6`Hlczf+(X#yXN}556G_}?GZf4HB-x{6~&bISaaQR+%P{cNFdd6 z@#HZx@uq_4ri$72gmy-R;rm|mRnpC+5C5JS@UVe44Kwe9d(IA`4NEa63pp5_Kn6}D3FL^$W z!vg)Fu}Ve8tg?~b+#ociYT@;2X7a63M1Xcj2ngsyh$%|Ugi#n&cDG0G9W%(rIVC=- zDed5bRW^{rY-}y>v&K4c5B~5Ku>Pd)nW~)4X&tJGwa%*)GDjx;;?^7-BM|Q$wDNvi zSIE^?-by*h8nT~5sDylDM|Y~&pd&3V@CLf9n8UmsCJN^~E-eK82#j0{9P3C{BN`3F z2~ZpkZ%nTGIc6$zH4Bp@Dp3e3NF zD}ne^#I0PSC}(MD)4nx_Ck1L~Qt(hXW*CG2{DS9B`g&066yj&2-Nq>I3k&fibrqwo zZL&(0xT|+pu+C*<)kG=QqH-@3qlw`@Gbh|MQ3G6B3G*K?x$+{EM`S8rI|Er}xePlA zsHmR1^cQVM+`OhDvcpSVdB^$YMGbuo)oSHUo_DVm#>bf&8O3R1AC--|)%zM`RV zT_|K)L0wZ+I&(OP25$SXXocx9RO5i$zw6P;(|jO0iLZP!5;jW6h8tffB`ws+0s22W z>Ta&G_%t^11OBSDO`I3i+7Hwi>XwMgbs}@23byqp9}=06t{5=|;zTqo$;u`rWm zH-=EA5cEfBGrwSW-MG$M+Kf)dLF_7T$Zwn}L!F6%anx(qA+Y4^SsC0io2)le z7r7hmvF7V1^rdP)K&$=oM`1x0{5jIO&U_2{YS2xx!PM|MWuBJnpJmve`>NRd*&8$I zPLFb<_mmB8puLyn2p?Y zb`|+9aNptbDi8fB%yf~OBh8Xly(S{9K45C(4IMuq(0arD$7m|ujb-HP8>`}Won58H%DEh(-;zS4j33X48S3_@ zdg!aBfVX>=g~@biS}g3XvZ{PMJ}7#4R3ZJt$E5RG=kD9TO~-^kzLIT_3m*b-i{2%WaxDVz*UPiM zdZz_g;AFKRsLF>*P&ku6iy7B$+Rmn|g7>*J7aGjvVdHpv>HTqJy4q14Q+9Pu8< z1`kHEjbsTb!%_?q&eB1RvR@SyBdyJ+-Sgo@7fKEwfEa1_ccSwh^H$pD&51rV2lkuGer?GkJ2-;gv!cGJZPF z9U57vzzrYwNq!HbqTnLD+27ODEuO84R6mT#ou_^Wfz9>68uB_4ujgAQjj-qPXlzk( zkFa1mVR$;W>$R*7pUY=8RYkkzWoFKQG zzS&3Qhni;Z31i1-w-T1^ck{|XVTFn3h~7ybnP|taj^K1aK_7`A6eK(^nh=dvd|%hv z#5){7yZ2sRFvEi=Rid#Fx-B^QGbnAZTj68*De&!gtH}k@#zJxIzkx_FtKCDdSwX2O zeDtmdKp^tuRHnI+I{p#Xy3Qv-0%CO+p+}uD-)K#&;C;NibS&AJ9 zsbgIxm~fyVy3Db8ptnLtOEVw6%6PkPA5hjkrFu2Gn5R7X)I`DOs@TLCNE>c8Rv}vs zQjfiW_B#Dk_Ze$7wi3us@TGp&KqUl{)HjmsDdPt_51PGvbsFp(TVQGul_N%r;`!F| zfj$FL9&GYP@svKZ4|}+O9rCBBJ@mcs?Wa^mzwqcV&(8-=mWn$OyT^B_Ps&I#MI`k- zL=2jrb4Fu#zULY4(4BVAt$iw?DDhcdy%mYf!)QaHM`^uv4lR^s?;N_qZ;NKzBXT!4 z;nhzd1R-A(%+i1?#}D=n!Z_3n3@8S(-tCliAIg^nebgsfo7#O()R$C|o3z9+;;^ng z6fHB5-_atu!STyZ$$&F0RQ(N8+Wti_t*?$R$}m&q&oV0)Yiw0bmgbZA{hhC59~kcC z;ahv5d~3MOrXG28qafrD+0*aCoQ8<6h}aR*)fgdD?Ooc`plhiW;I!!epZuVfA;9J+ zbD#|8u6C8uEO*QOsQ>x5-;0+RhBc<2a!0raCS_1pL=LGR;%{DG^yJWVux+O-Y&7Ck z2Z>N~dwnb4=lo@{>*6dZ_(v7Izy;qy?8l*u|E8})Mm{el1m13&zXgq5+1zsxQKgQfFo4fd>n7GhkuwUG4zT}#B1mv!ZKiBvEj;jZU$)YzIzCJ zn+4kKzHBhM^FSqTe5~%t$sHOLTHsx~*0-_G*F$Jdiw(ph32&~u**j{krs1McUJb~- ztk}M*sE?RMq^HtOMrgB{WP11O*rm^PvI9gUoH19=7}i+wmy7D*21QRZ!1)olvS+0y ze>^{>Bunq~mC+5S#b(FG4PaxzF2L8cySn0TSBKDQ+TD7?a$SO#fyyc1iBfFMqkx(+ zgzuaXyB1Z3ez?a9+RLSRhgRkww5){x3I};eT(zQH^Ub8f=Q4Bo&^x&aPc5XDG3M-R zRQrx!0%ORl=uuW49Z7Khgo6e993tIsUCwTvXgDA_r35$@l5YDbbqL z#y7b_LQh(lIJjKtNj7|w3K+!_yQN3g-}+olNX^AtXp8I4rMwE}dn~J&XX8E(qiVtH zM+|(=1Q$jb6S;0Co8a?*AN&0Gmpl^4$X=7;Kef8-qO)`gyzG0DJ!Bvo=x&NmyZ)HW zaTVX~%3@hu`BjM)*aaJmSlnLb`E@$h+I}X7?8&RZn3Rpg4#O5+B=ljU)jmgI-R zFykQ%ed`R0Q?ET-1y{Wrk@O#0IkJ!@Viul*t;XUIF@N5MQ*@=WvUc3^6a%k+K-%HnUZRyrZ=4rx;7UYg)CZUq;Cu9S4l&oLT^#w_wfT?#imVM zeVwIkdQvn|_nk=()pA#Z;(HHXk$%MWtciq~5RHSbav0Yf7UYbQ05u`=?oXl-`9S=8+79IhB|iL)>zuFoo2l4LIWD^n z_nfQ-!?uXDa-T2?DyvIP7T(NyL^_H+bQZr7Sw_hy+IfA9bW~O@(Dq61PU?qIY^R## zkn_~ZABCV-#dz$RSN*{7b%ytc9YnLMiqyWi7hj=4ehD zHpCm7&!vR{m}DdGWTBCU;v!{*niA$3+P@J=sS=}$@IuiB)(#5Pq!gWLi*orJogH-f z)eea%QW*?}60?kbn8T=l`KrLW?MA``3w9bheke|3kYdF5Ui;o&bs)&2*0LMW34*gz z6mjBT#r6nu#*huRUC8kkHqM}B28!U@Dj%97mz7fXG3~PyOQg3YGUk%|WJO7YGs!Lz zdgY{*NaPLOa7~zpm%pd8bz2aE7GW+n4w{ZfZKU zW(Oh5-}&Sg8chNN#jpEOcxx`mV|(WsX9Ho5TV6e5)-T{5a8-I-Dn~Y7(t9qTenw6O zT=JiClT8W|q)>vPzYRj<$S98_M}rFY@s+PkKepKDfujbY!{)2n!#tj(5-|VN=!Uh2 zEFPxvc?Ng=2iDHfD{@w_@VlMZxyqXMDJ$&P)PwLfRu*q;>-U3|6ZNED%exa-p`X*U ztlm!U-@uFo?{AVC@UPsLt3^bJW!mPbT};(OsB*Ura04;sI_Opc`#k=TS+l0%B~rTh ztY{8t_&V2+Zqr@WogHnKXW=J*KzW-)Olm^YX~f2Ut7rr*R8WaX z>@BgJZy(*RXg?j258I!9T&#kYp)HM>3w~(lU=;*A`E)iOMHgzLI0eJ(+##;{Y6O;@ zH6z~zHBpqOVuE()<%SnyS-z=qq!z+{(L)XoR>I{!fH6p zYSyqSmu2jia4s>h)0_M$rnK4Zdk#yEo^j(D43O5o&uX%)8r5t;%zpzq1WlO5?>~KS zjF#<`b)w)uwo`vY}v9RTU; z8fbaO>bt(VF!o%`60-AFmidqO{NM_gcsw*(yW<&~#6jN4rpnaWQo>**g$c2*-{g9sdYzszh=-bM(Q{ZLqD?4*e3~^a*^M*(_5vojghC z+g_ioWB2uk!4>bdvx)YB+7IQ%_7SuC?56f7P?BGe?DQ8;_o!!)6*Ycuju}97q|_PIaacgI8Z(Q zB{cP_JSHAJGHHKm(g1S4x0Tk+eJ9)IMfnDVp|7wD$VL1u27pv@%hUGOv$j`wW?8-x zPO%rMz&|F;;Iwx!Zflq*+Z1#mf+d_jP`I2t3bjWp>M&r8(CN6cc{@{T&ENn*WTb9Q zY&pFBupc|G_eccj>Lr)@r6^@{AM>?QI(e-UF?BIePMH)wtGq;nKxaZm2qM&p^LJQ1L%p^rPH}g>0sarX~;l{TZ zQ;77}At70ZTBK@WiOr`#`fyHa;-5D_CFlGqTr7$;I@RL7+85Wfr}^mwGK~+VZBZ@3 zVrij)rhd#yJMG>oy@-7SVgLj-y5|%eR`K%3rpMJ9TRLLu6QovV1Ywie1fstR6)etp zszGb8FEN*%HzjD02)^heyw#LO?(RMOr9aK5Rf8o`Yo6Ck%k(RO6}aEpQwq+tJoCy_=WSM(MB5wko zkqS)C> z%Dyr#o(<+92ec)}>^7lK805Zb`#Cd+k%Zkk=WMR~L4?0*cd>dWoQuHLP*VZ zx#alaZp|me5SdNc%~r&yL?Hb7@1KP&tXN^xGq}xxwO&M0@Uq%g8sHkmu|O?Rzd6IZ zl!W4)1j=K|hw{BjLU6YR@2%=z760`XA+G3Ky}OF}wl4-vKa&s}IsHd}(-b$>L{pm! z>jp!$`TfT6do)au604o(mbi05d`R3>!S2{xcTR!|N*yN6{iL=$#rb^8pMuQAxrYBa zRf%9z>Qb0mc5y&`+(lJQlwO|MMR zjre-@iK~V>bFT{q{Y|A)Su;PnFI-W(z&T|SzG3sf3G`G-V`=!I-vuI^oSD0-DW*mw zv=CxJW)-NbMBdN9zo7N8A}U)bHKILSh_3$NK8hD!eG`pOt$fgfThRG23U$W#QpOEt z9@(}i8iGk8xYI8fP56+SxwFQNMzo1@aqrxCgfx!~v%_8;;X`|qnhdKWbL}tdSLE;^ zZ4(knmbg%`2No3MMfWgSVXo8$u335RA0n_$eDmg7ZkgsuJRkd{ozCdpkSvTfauk|~ zd!rwKG)e=RGG|5+i{vOz02wL@*r<~Y)Rmm=9R9KMU5onggmJjnr6ev3*bR4GNG64? zk036}Q#08E3YOfix~i4+af+GS^R6#?1Z&(Gk^wuFRg=ED2T+x)#Ukxj&W5ez4H7=K z6FTE_!ny0{G0kh=-py95u&@iTsFLgds51yv^JohUQ{bFtZeZ=0MN;u)4^k+raWfA_ zCNiWM78z~>@o;QENSV2nHZ2Cp*z^27%-g?T;y?RFK1IlD--dd-TN9f$!xMrwwlJ0l z+_XbgMeCm&lzfaa$R%(`ze-kWfNlGxlZ4)W6rvt>;J_Hwd^H%={yzf9-^Tx(~# zaWTYys${-H=`{ONstK&Ak`C^$X`Uo0;--=4*-aT1N}FAB*Fw1X)$7q5g>kRERcAE+ z>2Rwr54oF-%C14TG0nj=e4Ar=Km5EW=*J%^wjr-|#ZN?ATw}qYLcwD3gLCJL4`ve6 z-Er@!jAzNjqA4pE4)$0)soUN(y+V02t2L5%<1~f0e7$Tx!5Ah?W-H>nJ4lw>RHJA- z8{KWi8cUN;cR9Cj$nt0Vjgnlu?RK!TaVHXCw{RtQETw|49(l^TQX*V%zh7rq<5wW8>i~8BTfwV$3i+>OO@P3}i?t#{)b_cC_x_w~ zi?$*nF?iK;!*U<5S@nTgHvDKS&u=r09kLcCyjJoq*)>J?>1#l0M7?wS`NG>nIZhE} z`!n5kclrssf6p5dB{E6K*N51ht@qWJt=lG2^7<7T@H58ZiYS_K<+jTRW0RxjhO82b zk~Ib9^;@;i)Rt&lNupg8b7U#1+l0J|qCnzIc4JrXWJ+aOew8H_LjdFDvQ8&ULas&~ zva+zGe0>Biqse3e=oS&H3J%8CA}R>VO#YOqs^n~g(;|48N4nTs zwutoA(mJ)dTmP&6s{iI*l8@M3cg(FkyH-`wJec6bQYBhBes^=(!`*@!WIz%BX}=3srj-!! z8+LaomCOy79<&)%`3PRY3)>nw-BiR6<~kd0l7foj6y|sq`{(4HkZiLZ8B)e9n(+t;U{da1aH5)D|=L zLcO{yX$bZ4?MQNg?t;UnKKi0p2C%rt7*v7AoM+A7a%KRDcM?B&eM(vU^>f_Wy|e4F zIk)Levx$zUnXo6Qi|p;qj0-5+Kg%C})o&5?&Oo#6T8wck<=8RtRuM&6xPWFvcRk}rpX z^!!~PMPxmgB^c#kY2uW|M4n+{2;fb@6YGUK!!?WYdesWE6l888imRXP! zBc}){j79D>1~hhXv^Y>7mYDoqU_|neCNSnND%?dJH6>?K^VwHT6VuaVIy!ECyVx?r z)F4XL+&`AHU0;MxZQdw4rL#+$(5>#45kO_iHx~XjV{<6ddkcy_<-h)!!t>{Yi{GhK7DQFcYG zQ=>47_64k{hXj#o_tP#$gwWFt*8mGPEK71gu0cjiW zP{7|`j>6|TlU(b9zS7~%V?lEJfgG1#u&VyM^JE?Nr()4sFFK2EJ5%Rfg~c)}lhc>P zx%B3wt3=Qcer9eMxBV3Nes4 zA3jBM$BHui5UovUsCWG}6^jBn(9zK&T^tb3v-uPiRFv8=7?@dLzCyq6J_T3VH$7}vyZ6P^R_g$p}? z7Q;R__u<_TtGUEc;kMbP?EXZaur8$oCNegS+)C&h3*7REjX1q3iqY?tL{tH~co6)} z%rn<5b+^Smes&gxiuo>_G2~MmV!^~)!yl#I-y@Xl73xY(FLYVE(W^JmT1S`*gS|~o z2)(`<8p_E%k(YX#O1sqGVv5SQSyIOe^29bZ3e9Im2VnTw*XE)s*v>5Kd$@5Xa%0c` z65INP%R~nNv38t`o9>ae!HA&A7DJUIcB`$E6nnHxc8#g^hID47-q-b{WO1L9rdg!Q zB*~nr^78boY>og4YpyNShmRo2+DJThqd^wm=W|N`alo}bQ4LN?^X0@Q9c0BXX>n1G zh!f$eM%Da^Mse`n`8=#`&igDT{kyPq1z|rHaKy$F3-SloOM{l`Q8D{oeCp)oXv8Y> zo02i@6Ax=WB#Q25+jjP(VjkJO9$o1wE<7$Pvz1!TZGztVHa0MBLG|EZhwgBjYVzq{ zq7{nW7~F}MylqRA|CYD?kG|+daNukO00I78a{iOHeXM8Vw8&532T{#Ef5^Nu*PLQZ z#Y9<5=LONPdrl7xU>JnkdeFutfc*|3x~8vQ$A_k4;+x7tmRC=#8;#Rd&(vkPi?-ZG z2(Mqss1&%|Pr7LPPv<mHZ(OKY-hH^P4zoyiCJ-Br2B8bd~mc&mRkP?$YRZfJ> zkZQ@4c`1f*r*)9+_^8kzI27&=g;9S5VQHUj`|u%`MyJ`!Q~Jk}TNp$P3BW5UdL@8{ z?*uX*H(PeImn2IFb{9Xa5M*v=Yj6{mqb4M{(60TC07h&V{nV`55oLK3Hy^&x?Kfd~bjS#uq!n>4?kM0YAwzoWz61K-|DzP(tGyu?U(kMb%IR;x)tGJi_8M!c6oZ$@~px#3Z7Dpq}p z(+;L-ovomF;EBLJN+j@RDHv_9CIL>jyS&z~{BcNsg|^o7wIAj6%y*SJ#v+`0hOEzj zIPTJ<^4=F<&d?eV-X=6DK7AbtyCuRdQ2Sc=n_XtG+g2j2KG-h#q4(=j9j>lZPuT2? zDi`sRq@z5Q5{Ic(t2F1fjICIozLae}<<}JyKV%9$oUY|x-SZfQoJ5ktsHtqF8pO3! zj^-&(L^ag&7aI}auY@c-?als>00QN+!j|mM1jW1$darrb{mQ*YEUD)tVHK}-T89T) zq<@ePhh|3|SiTMM(|yE;v&UV>cNa%xPR!NvU9W5J>MU99apak`O6wwZn&ofl`umaijg`!Ucaq>Z`VI7U$is zgiA~8Czx@%Es#`_7gYWLHIHXtpv(wUd1&WhQ`_t@6%}-SI@gvU>spmw_}gV#R95h$ zU*qzjuIo5Rq+fU;ojTU4c=eLvwYZ?8&b-PxAS2H%aYl5_jLQ*;H8UT($L`IdQwt0j zEeU+IBatthO3ulX0Y({l!4HR{edweZ{e-k*R~AD-#bWdGt< z3DS1DTe69-g4K8`j!Ws4f{fZ#KYA?qxv;~VucqwJXCCVXZX>b)p$G;yPj#NgeQeT5 zzqx$3FiL3xw%MX}IeyMBYB@+Np2I7~qG%0i@2U&%Wl~wVXA*g$u5hu#Ep&}tXc;?a z3!equewEe1Y*wzBr5l?=u9*fDAB`r^hj;aW?<^)A|5N-`_){7DqF(xEdG115AO&ep8x;XNl^=vv68JH#{V{aYpB@DE zr<@N84+^{yc*kvmL?B>gW!|+QSKj=uy^M(EhE<@{$=l|kasvg)1m5Jv`X7@ND4viM zaHdIhh5_M{os>-ZyL1wB32jr0lom7=eXQN+DE@0Y>}d4VP%P@SG`fu95joI)7RTi- zhoQO^D!z&jS&ak!xf(RACscvYEQiDeZ%hvIWLK5&3HO6e+pNQ!6eFi~6HDc#qqg}} zWlH?)=Fbgge&2WrOy!RnGR&ue%o`|^5Q*$9c7DQ*@mCE`l2f>py)tfm{CQK@diw#1 zF&sV5%7otibZ@7M(DfyUUVGorCco;Zfc&<4e~6I4x|6vr)yEqZvz*Y7y|`nSt{!FS z#=UaWrjG=y zjdPByuWf)dH{>No&0JG;dJQu>kqQu56gh}uNF zEUf*=|BXhP|4XBj6#(Gu^gp7$e;NN;WB*6eH~x?2IrK#|nOU%a_`bn5858*B9X`S9 z=4h)-2F~D45s5Id%qCzcMP~NJUH$gt=Ye7MM%FbY#*Hpk<@1|3is)&YGDPHRBaTvG+Fc2tcSKm^k zJRI=ul90;}bEE>Vu1_DDEM81oeBdWN8Uf3I!Az>QuQ~;J+GA$^B`I~2)jeB%LBry| ziuvCC|M2?1NEK$gTb3h-diGkhwMI z290Ult+8B{z@qivBdJWE@^a{n3Vndj_&pX=bv}nVMsW0}l%ky&lRJ8Lh7V1NT)pCbdv~eo_wb_E>bg5w#s`bRM?!jOIIJagCX$0V2{ndQ{UUCbT_}-^>nevvy&G^o5$8>`{}B0*YlB> z&+SvOs-Mqsb{Cwl^Y(bC*{|*8i0FD3S!@9E5P1Rh8Umie&z{m_sYHGLF7HC_cKYz2 z?=>&|hT+>qeq&T!cg>IezU~j_RL^JAel22;({QSj=2M8@^Ii7yqm%dL0RHOZ@#^!_ z5I)uF)6K)f+~yOZ*Td-B=d1H4vEwHQg>Nqya`*g~5dz;yP8NN7$PyTPNZyG(^+P*6 z*Lra4a)DpycnQxwXU0aGP#%JP;RDrOK7OJ5yHq~s=ga?Km>t7svhqAF_V7IZ;O2LK zbvR_=cmC-X0zX@)@_Xu8^?R5}e_&7cyE|JC_4~VXJZ=)T>H2(Ld@B055ApVXKKAo^ z-fVwhkJ=o4oBh&BsuiE-ll1Y^6ThL|SU-0+v9oga^=^pq!?+*XnxFUM2FwlO^$>b0 z_B@X7cVB(F^8D03e*2{=+Yj(`b6o89!aDrf=lOW|)VJ&AQphj&`gphbh2o)?)*GAS zZ~frqVBe?6=c~)(7n0ka|HeYP;0I8#m1^J1>czPdiV8Sd<4xqvHXLpe(_j+A&EX~x zxX380)}BSR42M+0zDnu7}lYW?T@(OLzkcC*e%(d`C6s&9uHq` z>|P3OCJP}iCojEMe~Nwz>A!m%d)yxTd>b!BI}G`=nlo=Vep+F2Qt`!2&35=xIN}~0 znh8I^i%^D$(uP!z!@nG}LxjQAY;lWha5{wpjAm-AnB?ZYFC9-GzVbYB2~vjJHzYT! zfg(^!MK~OU1K0Q1!MTg9J94;&8co%8-7NJYj*IK-~xVGGXGyDH-$aNz9zwH>wDvDOAMI7@xM{qUR0YNh_&;IwH zxOnB1ZH51*;@{o*e=5`{UOH;mklZS9!0{igLTe?gP4mSZ^C2(K3a#t;4+CD5`KMdP zZ%f86m8<{{5cG#+elK=ukKHNgPpNGU>3`WtPmM^ zcRlGtz{a%+>uj`6#=Qxd^#=V!Zj{KW~wp79HeB10koQu&SaxAHl#Cz_*u@-ixnbDKUf(3V7l-} zQ^I4oY0WXQuu-%6LuU2cgdK@HaYSa$lOUxhDk&@0Ut9r|@Y-77b!OHD#aT+R_nem` zZ@r0X_ey9T^P6UtOk^VCXylv i?lI?1YnD&F>DE)iiHdh47NvB(DF1!~#$ln%^` zL!m`b;kKo=Ror~X&3@xjtgTngO^ygEGBsLvLAtGISJGiyg+<)W93!6#((%Q+lA4gT zT4|)ymMwBPAW7E_NNbK!{RL^I`@522k=()wYWQQQ?XBA{tDF``%2dc}@s?#~pFJP) zYy#_WkKP1_hr5#QZc|9(7tF|B>9je-#a%}~^VQn&0xO;4qcT$~Tdk%RBxq^Hvz+#n zZz$Su;6@AI_+fpjL|Q^#`pE^21z9J1R!mUd6yQI1_a@JVdv1|8>PoIn$vFPZqeane z=Ge!HdCyKZyznu3D6bW)mG=^^Q>g21xUQ$JzY1%3A#Pex|DB`>FHaPR<));-l()~L zvO@WwN%HF5R(++y;+9S2;##}_9gB%u%yt5J~ViQTI&{ro{*2L)|F@CgWxF@~(3dE@3#=oDc%p*2J%Kk{+t#<0qLv=i0I&n|^7 z?>maFo~=oK76!2^j9qZpFV!HkCW*78U7@ws=+-pVJe_Su{S7fM`&f%P=b9B_N)G&s zWoGGeyeGtk)O;5$F6av}T-Na*AL!EkDWUQ2_KAJatTl^N@RVj>(Dj&p zV4G8an?iHtD=VG4Q4g0FR@$-jYXT>>PLj(%yH}Fc93)jOBUd5M{+`{WXsGN~O5E4H zSF(Az+f6NYJj-Kqq5GzleZkec{eoVK$W7^yELNMQw%t2L;6+ykv&)F-N9`5$iWXFS3o{2L(^*RsN^WAQbEp1W+ z2I)jFn^69umpAQ|clV8>-7~Tm-8~Gd;|~U{0YlkR>13Of( zgkS`-QNF*K^gs%4G9o-^I}~IF9t^4znz!|yCRm`@ccRi^lC^+fd5|m>g5_{T$O`IR z+E+BwbN0cQ0Lm(nV1b}*Z`ZJ&oJdIQ=d476sje%WY8I77>0N4SKrBbMZpP&Pq)u)D$xs^(Q<4*hlx6i@52Uo?=O`M8tNBf5ytDD39&2%ATV8>ok;dWzHzQVUbk{CB z$Ja5e_T@e+gL?m9)m0_dHLNt!#(sS6^J-VLrq)Y+sPvJE9_;F!lB|E5hZBim&+fc_ zG;}~JoJdV?YF4GP;o1y!q9=;ZRAN`gUMq=Xc}y56Duxs+NpLoXuJn1~0!>9YDk5j9 zo`zjz1a3lC#@vvF@_21%jVHPvn=)lFxhw)v0o9aEz*v&;j;fW+%DygE?^&uTK->H2 zmV^&pk9N<68}C2fU{@~A?)AT!peHwEYDt)SF!qCFGymM+4oH`X+`vGMvC!MDEx&BU zyjEy)ajDs(M;4TJysN2^Tmb}Q0+E*(BQVsxms-IaP?`_rsvRZXR1whKJYZi(_M&E* zh0x6AhG%Y+8R(0Xdt2$qbI012Buu6O-NZ(Z6_%zPQ74cA3p#hISHR27aUsI@k^kZa^$8|^BR zA}Ch`+9_UDlq)FE3WEy5O4vIWe6b{Z{~r_6Uft^CuZ8GO!AioFfad@1HLSeWXSBeV z5FZ=tiueJ>Kwl#)aIA@SYtdg`i^vJI)99PNg!sIXfxvy(DhFWhz!njUnICzbJN9}> z0?qgm;&X~W{`<{&w$Q;?U0f*GbzfTPk6MMP>{HhhcSpgTTH1#Vc$nynF84REG4yr8 zSp3E4W^LL_&nR~ML|Ev64m@J3u@1ZnGk^!Vi`wRao5)&HS}=j-?wDK_T5OnHU8djr zHX9q)3I@U?xnAWQBpitq{XF8mB$&EeORW3O=8dqTql%5uu=nHX=8rqi8G(V9GEKR^;O1@8F~Fb3%s42@I(?A*Y_FIj=h_a^(+z&l2Mew z7B2LpnE(V-m2uk^R@sff4O9uToh1Q-He;rV{hV4(MvP96Wz0Y{K_}`TSitQ7i;O0O z<@mcc=z&CHj~FBDyg$Y8Sqs8~V;ICV#)6NG<8wCX)i5GWAI0!_3!g6rAYWk|pRqv? zppj|%D2C5l_~LRix4A+_xp4#f`keUn5<4t_S!;aX&#Z}>Z~&U<=JZ6rV!!s2=Ue9* zUdZ_b&@<9JAjvXvdz~5zz)o57fCNj0Jk+Q?Z8&bqy*Z_t3HCpu|{-tX3(NZ9F#etlt_0flEFLe&3b;5*@9n-D@ybUvyH8h_0REiBYjydT`S`&5WbbGMdFd zh%Fy&&wpqx)A)z|gyU1h^mxDK9FB>+4CU3Yqy5)AAkjSCe+ClqOrkBuY{@P@?ctA14{72X zk&052t6^9W?-;+)Vr>_btX0s*QTpS-$Db|ptiyZiZ5yvifsbc$jusF5xX@FAYfonG z$n+m(N@OCTjkyP+kV#b9R|Hi$1>gSuhhJAHR+K>``zYcqML<~J_HdLg3zIF~!WFEh zlKqW{@gtL~7ikj+4)-vxnmB*QS!FqXNNI_idvBxs$s8tL%_{aLV#N@A^ zw%)Xm;QwecBka!Q#N_jf4IDJ(4T68#0=MqbHn2XT{)6f1m|>F5G=7w41X zW6Ko$R)`nzk`ByGJX)(B{wR3cue07RnVnzQ)U_j z8>HNuJzq3dU(|p06njf964CnO{bvh=gs9rX(d*iGaKMH=VQ>eN@EImbM?Xo81CRHG z-~QhISBDMYua&legK5a@{7W30&?#XMq@MWJvbbb@(L%~Y)Y=G%csN?TV}}V4WK45u z!rzJ&zB%8s9h~PKo4rsWd~+d_C=n7EmJ5U>pu)<8NE~AQMcXC8m8TqytLLkz;NdQZ zZHpjc^vm2vT>5D-IP<&xAF1xojyi}f&-}N6t!Z=1*Cs(NEw_SpW#03v4@=ZYe;UU< zCa2RDH)TV{)7tGxi7sBLm7MvJ%`GA(_gh*Df-GD(q9K>YC0dl12go^N3a0LHUT>o1 zHX+u3{Jc{2+Lri4r*3t$d+A#f6X%oBv0B&-JJU0`Tp1no;eyDj>iWyc{^Jv*47Tg3 z-@4~6gN~a`PV{?pXyWMuLDBbSYpA#87DIPLz0-_yuwI^`{0uASCS+mewUN_GB|;a& zt+Kb~OVOOgQDhecDnT|pHtM1((RTtkL36ro2PlskOvP z7-onWs18ia9*(u~-AiU3yn-x-t-f{drmbEOxl;a>ZoBBM7s|;*Qtz`psUx*R`_`Zz>17QTQ!sy1Zy{y71aF_TNFy`69kJ= zV_#=(IaGaNZ#ri0o$@BptK$x92`OB#AKm!FFbmt9R)HaAFfmWm1F-+0N`*)1I66AbZ^81!Tj0w@3PY(s0cL%oxhxo#1n4WQAFb_*y5OJxECPflqO1I_eUIW`y4H#A!u9?7E zW(dL5TSv)^$8u09n_@kAf-oAUXNfo`g%VKPPiJ}lZDkpT6{c(05W_;a80g9{((ItQ zg?3<%8w?rBD8Cu1NsGin{k~H-5FEOXPM2luQH$T#^9xtkx#ziVnz_yLmRwd_t{nu& zw}*N0|8q9F)P|Z=#Tr*xMp!j-7Pjq^NcK0Wx}TVQi|t=2s+;kDPi}KN>`b0)mdo4e zcQ$dE#;dsgCmaodonu5TY{n6;<%4aC(rx_oV%0KE{%i~9B{11L$jP(sH`vtaNyyl! zHDtLN_xx}w!q8|Ilyfv9VTEF&pM$|QU!d!R%RjU032b{lp0m?%UQ(>XAF&jfth>M> z=b#uL_dfc154mq{$9+?i017xbg`4&UYSSicz-XH-ZcQ=76uu?>ZMm$ZjC1A^K0Qaa>*>rS$xR#}t&b$AQ(POLw9;X&`6o#nW3Pz@ah;ohjW3RR z@m5k%)518eLznReV!7@B==MAzl~@xd;5PktL`%4#<667F1|oGhpWv7J;4Jh2Y^U=D z%PN^HDkGNx{ak;bK@5n!>mhR+w-NPFhaOtKKU}b970kg^U`3PKH2&K)k#)=_@6h$B zrOVuNl|5iHxxIPZPO=~ri|kFJaI{}o90$Pq5Pn%axOJ-Rw%;U}&xkbX4*c)15n@Ml zHyk^rMHoBDqGCtnCyX7SA00ad8wEUU3>3#k`+Kl4v+D+S)x6a5V9BTAF133BL=tMT zGbt9?ea|4OTar%^swjJOP#GGAjp9;w=D|u#g!8hwjyriXY5%RqwE3k$)ba%lXnrT@Gx3sIZkZKyBuG)EVIyww1Ot1Y1As@B z21z*xtS-^`4YAnIB%n0!MKE@{8k}Va39*Qk8;z1^85+M4A{0sjGfW8*B$*&4=q7>c z=d553xPYv{%*R4Plmt+OL`hUQAKRe;3z%U_5Kz<-vrz_-5+Lc*R)~f{T!V;*C>m;lj(3ivO@!FEG9$Z zqgs+E`O{X2UHQK?K#89O;(Q{4Mg}r0WCR_?K>14O%(kbzaW$CCLUJSl&NhKsD8b?N zL23CIla0>TUPV{IcO5^QEZ)>!US2|+pXJSUYFo_Ab>2U;H_7|nKI3@{$Gq{SRwNwb z^vZtWMrYi6SVlmT*_)z-6EgLAOPugzJ>FzLb+RVLJY^G)uH!Si%wb9JaL!=gWn$l% zQ4?}MHfu69oI0^qHh^a7@^Y!~a0m?DN{vKJn<;*8LpPx|wO`{>tH4tyE-1>R3E<>K zZMmN|gN;Y$iX2T`P!R_6nyznrA)McZ1a(}-6AjOg;lNZ1Kw;W<0D$}-W?%>XJr1Vk z8ifvtK%Gd?N@RojQs)Y0mOMiX4$;ZPz0qoN4jmcOH*$MU#C+15g|JdE?+A4};j5f} z{3-_x3FvQc&>PRa!yf#JK{PmO7SP8{BGHx936*f?Iz1M#SsduGNC^o~f;{0U#Sl=2 zt_O$3+yuZ4;{jW|$Jh_W(Hu%CoPv48fa0%$4B39Js*- zSuI{J@Khrp9|+H4WBQfDY|~5WqZvV-ZdRm$x##4c)bPw_Zw{w08Xh7@r?+DS>GZj! z0=|c(&oc?;@Lel(DbWhmhyil~E)rn42EQW|?7yl`B-|Z=Bl8($4TlKFcMK7t+m_vZ9l zsss0zxE?T(X?K~kxT&W1~;aPA@YV9gAJAH%^|CzUkg)bNy`jKwq{E|SD-i?cvnA_++g3m{@i zLc^jOh|5T<$emEci!S2%h{r9qYB}O7d)i9(jMZ4y`u(|&CW$OowPmKRh?Jl zPPH|is}}FL%-ry__DrksYVjwfDm2e4vwoHh;rU5b+!Ngqx%w383wh%)mao6OIL)f3 z%w1c+pUQgVN;yVYTX^>S*%$&tOsrx)-|dW5l=yaS^u)P{XJKpF63R7ORIN=(?KheBbRDWdDMhMI&uTm=&p=B<`ptf-K%gbx@!&hk8PF0^ zKh!}KC{vZ62+W6ptf(BQ!emoSNW0Qzh;@ArEM0#S%ObEXf)!OQO-AbFeSWHmj z; zs#gC(;Aw?%Y7VlEHjb{xFU!v^$Q9ifx#VfY!S)Fsw7K$LQBcDcVD>%+RR^Qy^Cg?^ zyS?7MQN}2zq%Pmmu88M+@>JfdhE}D(0p~j?+gfmQr{jO#YX`{V?G;KY0rdrs&&V#O zguOlzzE)UR=la@NQg=XmcM-4neac|Xb?t%H_`qK0>eE*Jb5sKOH%r>Kr4eK%j=a{J zYO8ezqHf(0t;C^c{vpa+yRK7I!&bm9EMzg*^#+4wg_DI%>uU0$`}Onv=f1xah>ddH z?!bZ9nMU7EMl1psv8@NJ8@9?^G5COyPI%N)lt3QReXQE>-#?nbq|~o zzsIh-Ez_)K*m1}2)JB4Saa(qtMThH+Q>V1fw?!L1bG%c?vH*V~SHE>+b>#b+yS`Uc z*}Lo-v6?ly7Bm@EdYzH2?g_6ya*Bn6*v0knj=*UuDp^_g3fsC8AIq3zWxaZ>tdhdd zwAdSSw&9Pcp&VAN@y@LPziK8@szL!mBO+aYt8D zigw*&DdI2ZEF=#fj4D5G*`xwLQSE>qp1SwHZ%;bdQ&w4Xv%hoqlA)o&pmRCBLsjrA z&C2%O9XHk4IUff19~^AGFXz?w#T3>Gda++M62IqN z@*#Sl@59&l@SL$@;{;p&^VL^bL-_EVufLf*YWTI)%(pe;Ypdx`syALSUSd5`kooRl zeAo*8N%fY8-;jUe)y^XoFyF|FuNbC3soo{+df$MbuM4H= zcleGJXTFFP-%U$@QoY6CK?a|HQ|(AS%$JDbYg_40s`rvHgq{&EZT;j+Tt_NpKI{nJ zKT3a6y$i<@O8@jW(vcdN&&a`tBGI2zZ&x)^gYXeaBSo1HbNINfJ_`xak&o0Fset(y z0et2I{YmwfSWGBjJ^^B+F!ML{_@n{)lj{8p8W`$=!hiMLfsqQCy^lY|r$4FQqU@0h ahkuyA`loN9d|!Pf3jbz9KV5S}>i+>C_LkrP literal 0 HcmV?d00001 diff --git a/results/tables/mdd_filtered.csv b/results/tables/mdd_filtered.csv new file mode 100644 index 0000000..744c58f --- /dev/null +++ b/results/tables/mdd_filtered.csv @@ -0,0 +1,52 @@ +,study_id,pubmed_id,publication_date,publication,title,author_fullname,author_orcid +1,GCST90101808,35347114,2022-03-26,Transl Psychiatry,Genetics of age-at-onset in major depression.,Harder A,NA +2,GCST90104443,35330412,2022-03-06,J Pers Med,Multi-Omics Characterization of Early- and Adult-Onset Major Depressive Disorder.,Grant CW,0000-0001-9342-2138 +3,GCST90104444,35330412,2022-03-06,J Pers Med,Multi-Omics Characterization of Early- and Adult-Onset Major Depressive Disorder.,Grant CW,0000-0001-9342-2138 +5,GCST005907,29728651,2018-04-27,Neuropsychopharmacology,"Common variants on 6q16.2, 12q24.31 and 16p13.3 are associated with major depressive disorder.",Li X,NA +6,GCST005231,29317602,2018-01-10,Transl Psychiatry,Genome-wide meta-analyses of stratified depression in Generation Scotland and UK Biobank.,Hall LS,0000-0002-0624-5303 +7,GCST005691,29495898,2018-03-02,Am J Psychiatry,Molecular Genetic Analysis Subdivided by Adversity Exposure Suggests Etiologic Heterogeneity in Major Depression.,Peterson RE,NA +13,GCST009979,31969693,2020-01-23,Mol Psychiatry,Genome-wide gene-environment analyses of major depressive disorder and reported lifetime traumatic experiences in UK Biobank.,Coleman JRI,NA +15,GCST005230,29317602,2018-01-10,Transl Psychiatry,Genome-wide meta-analyses of stratified depression in Generation Scotland and UK Biobank.,Hall LS,0000-0002-0624-5303 +17,GCST90058036,34586374,2021-09-29,JAMA Psychiatry,The Genetic Architecture of Depression in Individuals of East Asian Ancestry: A Genome-Wide Association Study.,Giannakopoulou O,NA +18,GCST005839,29700475,2018-04-26,Nat Genet,Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression.,Wray NR,0000-0001-7421-3357 +20,GCST007342,30718901,2019-02-04,Nat Neurosci,Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions.,Howard DM,0000-0002-6005-1972 +22,GCST010016,32231276,2020-03-30,Nat Genet,Minimal phenotyping yields genome-wide association signals of low specificity for major depression.,Cai N,0000-0001-7496-2075 +26,GCST90058033,34586374,2021-09-29,JAMA Psychiatry,The Genetic Architecture of Depression in Individuals of East Asian Ancestry: A Genome-Wide Association Study.,Giannakopoulou O,NA +27,GCST90058034,34586374,2021-09-29,JAMA Psychiatry,The Genetic Architecture of Depression in Individuals of East Asian Ancestry: A Genome-Wide Association Study.,Giannakopoulou O,NA +28,GCST90058037,34586374,2021-09-29,JAMA Psychiatry,The Genetic Architecture of Depression in Individuals of East Asian Ancestry: A Genome-Wide Association Study.,Giannakopoulou O,NA +38,GCST90058032,34586374,2021-09-29,JAMA Psychiatry,The Genetic Architecture of Depression in Individuals of East Asian Ancestry: A Genome-Wide Association Study.,Giannakopoulou O,NA +39,GCST90239706,34924174,2021-11-02,Biol Psychiatry,The Australian Genetics of Depression Study: New Risk Loci and Dissecting Heterogeneity Between Subtypes.,Mitchell BL,NA +40,GCST90255679,36685848,2023-01-04,Front Genet,"GWAS of depression in 4,520 individuals from the Russian population highlights the role of MAGI2 (S-SCAM) in the gut-brain axis.",Pinakhina D,NA +42,GCST005902,29662059,2018-04-16,Nat Commun,Genome-wide association study of depression phenotypes in UK Biobank identifies variants in excitatory synaptic pathways.,Howard DM,0000-0002-6005-1972 +43,GCST005904,29662059,2018-04-16,Nat Commun,Genome-wide association study of depression phenotypes in UK Biobank identifies variants in excitatory synaptic pathways.,Howard DM,0000-0002-6005-1972 +44,GCST005903,29662059,2018-04-16,Nat Commun,Genome-wide association study of depression phenotypes in UK Biobank identifies variants in excitatory synaptic pathways.,Howard DM,0000-0002-6005-1972 +45,GCST005690,29495898,2018-03-02,Am J Psychiatry,Molecular Genetic Analysis Subdivided by Adversity Exposure Suggests Etiologic Heterogeneity in Major Depression.,Peterson RE,NA +46,GCST005689,29495898,2018-03-02,Am J Psychiatry,Molecular Genetic Analysis Subdivided by Adversity Exposure Suggests Etiologic Heterogeneity in Major Depression.,Peterson RE,NA +82,GCST90014430,33541459,2021-02-05,BJPsych Open,Multiple measures of depression to enhance validity of major depressive disorder in the UK Biobank.,Glanville KP,0000-0001-8321-9435 +83,GCST90014434,33541459,2021-02-05,BJPsych Open,Multiple measures of depression to enhance validity of major depressive disorder in the UK Biobank.,Glanville KP,0000-0001-8321-9435 +84,GCST90014432,33541459,2021-02-05,BJPsych Open,Multiple measures of depression to enhance validity of major depressive disorder in the UK Biobank.,Glanville KP,0000-0001-8321-9435 +85,GCST90014426,33541459,2021-02-05,BJPsych Open,Multiple measures of depression to enhance validity of major depressive disorder in the UK Biobank.,Glanville KP,0000-0001-8321-9435 +86,GCST90014428,33541459,2021-02-05,BJPsych Open,Multiple measures of depression to enhance validity of major depressive disorder in the UK Biobank.,Glanville KP,0000-0001-8321-9435 +87,GCST90014431,33541459,2021-02-05,BJPsych Open,Multiple measures of depression to enhance validity of major depressive disorder in the UK Biobank.,Glanville KP,0000-0001-8321-9435 +88,GCST90014435,33541459,2021-02-05,BJPsych Open,Multiple measures of depression to enhance validity of major depressive disorder in the UK Biobank.,Glanville KP,0000-0001-8321-9435 +89,GCST90014433,33541459,2021-02-05,BJPsych Open,Multiple measures of depression to enhance validity of major depressive disorder in the UK Biobank.,Glanville KP,0000-0001-8321-9435 +90,GCST90014427,33541459,2021-02-05,BJPsych Open,Multiple measures of depression to enhance validity of major depressive disorder in the UK Biobank.,Glanville KP,0000-0001-8321-9435 +91,GCST90014429,33541459,2021-02-05,BJPsych Open,Multiple measures of depression to enhance validity of major depressive disorder in the UK Biobank.,Glanville KP,0000-0001-8321-9435 +164,GCST90096931,34782712,2021-11-15,Mol Psychiatry,Genome-wide interaction study with major depression identifies novel variants associated with cognitive function.,Thalamuthu A,NA +165,GCST90096932,34782712,2021-11-15,Mol Psychiatry,Genome-wide interaction study with major depression identifies novel variants associated with cognitive function.,Thalamuthu A,NA +166,GCST90096934,34782712,2021-11-15,Mol Psychiatry,Genome-wide interaction study with major depression identifies novel variants associated with cognitive function.,Thalamuthu A,NA +167,GCST90096935,34782712,2021-11-15,Mol Psychiatry,Genome-wide interaction study with major depression identifies novel variants associated with cognitive function.,Thalamuthu A,NA +168,GCST90096937,34782712,2021-11-15,Mol Psychiatry,Genome-wide interaction study with major depression identifies novel variants associated with cognitive function.,Thalamuthu A,NA +169,GCST90096938,34782712,2021-11-15,Mol Psychiatry,Genome-wide interaction study with major depression identifies novel variants associated with cognitive function.,Thalamuthu A,NA +170,GCST90096940,34782712,2021-11-15,Mol Psychiatry,Genome-wide interaction study with major depression identifies novel variants associated with cognitive function.,Thalamuthu A,NA +171,GCST90096941,34782712,2021-11-15,Mol Psychiatry,Genome-wide interaction study with major depression identifies novel variants associated with cognitive function.,Thalamuthu A,NA +172,GCST90096943,34782712,2021-11-15,Mol Psychiatry,Genome-wide interaction study with major depression identifies novel variants associated with cognitive function.,Thalamuthu A,NA +173,GCST90096944,34782712,2021-11-15,Mol Psychiatry,Genome-wide interaction study with major depression identifies novel variants associated with cognitive function.,Thalamuthu A,NA +226,GCST90058035,34586374,2021-09-29,JAMA Psychiatry,The Genetic Architecture of Depression in Individuals of East Asian Ancestry: A Genome-Wide Association Study.,Giannakopoulou O,NA +231,GCST90244040,35730328,2022-06-22,Eur Psychiatry,Genome-wide association studies in non-anxiety individuals identified novel risk loci for depression.,Cheng B,NA +232,GCST90244041,35730328,2022-06-22,Eur Psychiatry,Genome-wide association studies in non-anxiety individuals identified novel risk loci for depression.,Cheng B,NA +233,GCST90244042,35730328,2022-06-22,Eur Psychiatry,Genome-wide association studies in non-anxiety individuals identified novel risk loci for depression.,Cheng B,NA +234,GCST90244043,35730328,2022-06-22,Eur Psychiatry,Genome-wide association studies in non-anxiety individuals identified novel risk loci for depression.,Cheng B,NA +245,GCST012090,33479212,2021-01-21,Transl Psychiatry,Integrative analysis of genome-wide association studies identifies novel loci associated with neuropsychiatric disorders.,Yao X,NA +248,GCST012088,33479212,2021-01-21,Transl Psychiatry,Integrative analysis of genome-wide association studies identifies novel loci associated with neuropsychiatric disorders.,Yao X,NA +249,GCST012094,33483693,2021-01-22,Mol Psychiatry,Genome-wide association study of patients with a severe major depressive episode treated with electroconvulsive therapy.,Clements CC,0000-0003-2278-6465 diff --git a/results/tables/number_of_samples.xlsx b/results/tables/number_of_samples.xlsx new file mode 100644 index 0000000000000000000000000000000000000000..1c42258c225993778748811bb5faa9137f450ac5 GIT binary patch literal 6872 zcmaJ_1yq#l)}|Y2kOt|J4(aah?g5650YpGTkQ4-I9gr9VB&4OgQ$k{BM39h{hJWxJ z@8SC2I+OxU}HC&1Z@^Wp8YBymW+ zg9|HoS5)rH#ipwwS~jGCCT|{>6~_|)M8Rd18GW=#Y&qBv;xcR1)A?h4B&D{&k8F}8 zVmfC0!$W1w?bzvsYO;l`)JeL6v|b~!uJY%I3e$Q}K`NHD#OY)4qCs~pnbgD}>Dc_$ zC~MkGvp7C{M&&b7<0D%XM^Zt+S@3ci{Ny}B(GPu@X{f*EaoZukJ1}EmuQF{U%1rnZ zqM!OUJ2V-mPCQQ>C)W{!g9%%I(CIo(ae;&s+Yrn*Yw8AiYWhYf0V3-_zX!-#j8&1| zGAVUP-*@AUKjpAG#U;Hqb@xD;#L-kiMYG(7R&T-pP(gr$)BIP62w=Z3k#Tbc0bD^A zx_<5eFSCb_U7Smj23*^@aOHv+4r-LK%yjkSHge(tF-TW%1R9ayHYS_JV5lV+VJt)UL{3a}1zjzfP80Ah?b8&1q6T1CF)(}&ZAvdeZTdtk{@ zV1{3&lD4gQkD3+5ia^PVRa;RX3Q0NGsU!LXE;f>Wa!{0K9ZM~$Q}!&?I)Z1IvR~J$ zpF$y%Ap?;a;y)l2dMrNhFd%Ge`GViEo|C?`q*GaL)Fyi9>HM41Q$7ly@7dcI;SJ;t zaw5HK)ayFC>%KT6Hu`Lct&X(M|e26C&+&a6)r4Pwr)0>o^I}5oL27cw{ZfGaAU&a^nAGm zzrv~LS!5oO)I1WZH%^}(;*MD_cu{Aic@sXeoAJs5Y;v=tU6PTtprXiJaWo7 zOXH$Xn~gZ4%{xqU3(v5O+V9S+ew4jlLw-D(Kn5ew8gd1TrVWV&6>W2;Hz! zxn4kwPB)lrZ>0%_Z>JBGydpNhIU~XTVsW#-#+Sds@AFEVr0G>f`6Jn^s6wJ@a#7Id zOL?c}jtr(-S3igmot3~Gp@6yj?^%g=*Hs%gPr%QdOt`(ixM3Cy2Vx#iHRU*%lHrbJ z8R(-W=k$NnR4Y0U_$UpGujb=ME=}i(RW8Q)oUV*k_lXFX#g-~1tkFwx#OgjVdG+p? zr-?BN=Pg5(yp3AiMqkcyyHJ38cMc{-AU^Hvlr2dpAn8eY$Grez0A=zE56ZApkcp#I zV;eCreVupK3Jx89BPwMUPhnV;al0!)J65s5cL(lesC5kG<`OW0=%|N$)cbldM2ZxQ zS|)F>cw%IM-JDkNmh=5Z4{bov(YKcfN*xf(c3PxWGUR)Cf)_YTM^l0%Db-6Itor3z z%x-Z6>lVpDU19{9jNF8n3gjXe`kC*c4abRm0CRod)8v#&Z*F_PzM``&;F)dnGRWBT z5d9We`o@e6au}-Yf4uKxFk~M)bN*Eoece2rtliw4Zqfa_LP|LyaN~yGD5v=gHq<0( z$C@j*IXMMMD%uIgG${3|PF|g$$eBrXc4W5uTP<8z+BMIefTyi<1Rf*nX@yF(h$c1386 z+`*}?oI0`}wVeP1*1Az+D8*V|K<}O~1LFSZTA(?N`nlE>H1AlQsjB78LHP@o?jNM` z3#M}`u(U%(8&}9CT!TUJ@sD6J{RNi0ClFR2J#_#e5YW}$i}SZL_d{!->yCkoYX=S1 zRf~>0lK7xP-1w-+4INgdQZ{rpkzbpM=-anGk5~dIPQo;E9wD(RMoqX&Mud=jD8DGW zs^!%D3yuZL5~*06a7rG3Tld1VN7{7H#08-XhTh?gDVs51&T7N#SVg6 z#mpXU81}Q8?H_RqHOZUXQBgAPPIQt$!XE&WRgrJw*I%)G8_tajtkyBhqah+BE08Rl z@@@Z7#FB$4vaGaAwZ&~LO3KZc1!0Ms z1iSVBUJ?lZiiMYhl_$Vf2Lua=z1MBtz8Gs$N2J9?Su&uV<8aFD=4*g<2&k!6k(rEO z&x7X~Lf}aqwxKaps*QYJNX_Zgj1ya&_Fbe8NaJ5Ln(1o8{dmeH#DB2*p~){PG_hOC zB!09P^QCDmzZO0Ozc9f|*$P5<%qygZNews9w~;$u$iAA#EIW!g1lMO&U0j5^Rwc#q zB#S$FLWG4UV+3n{Q9g>x<%+x_=j{c)Sv_tiZ?C{$u(%n*1Z#Emd4jmG7Vt&$7X% z7Xj9FH!`|w(3-_t+ULIj~L_WS6S1fx>Qp|BDn>JYQC1{2MEgbIP6i_6|zVA(-pd%^TmUMKa+1COtjLT2Pd%Dm}qMZHc6O!D5 zwpt7=@$eHPUZdk!Dz(fnes`=kf32~nrNEc}#dnb47*Ae3&-?t7w_fo0+iQFlHFp;V zTP(5&9#ASil@WgT+>W;}q996&5Pe8m+#BlmM3~I!_N?GT3A8ia%`DGL8XO3s+Ir$YLR{TI3Y@3e+p3l=9d!#DEHq?|2 zaA}?(>`U`V=39fMZOSvTb)nAkYPvK=MGC{=Vd3MFLq@7ZXX?~_FCuAyBQgNFSe49~vJ+fq88SJvdFYe$CIlx*H7eKEgOMjh zn0cDkkUmcN?p9~1jLLA=)QfiOxe9DUueQj~lNvn4bJCtl)T&&T4s~+eYx2$#9mX=w zl~mRXNI{5{Mp(`By{*$|5N;yre&qCrh1$gB)SfnJ*F+y^rVm!4-K+`N`5S73TS9Qv z_8=d#WO3gKTo~c=F9*H%AGD{Ll7<%JeXZ;7{wVj7qCX-lcGI5Zd641#Y9_6kij))` z*>JxU!2sl{9QP9yhrvW9WmbDb9gCJcbIa_nJw#)Oqc?tMjbYxNYTW3H@7Mj01IjWL z^hOXTmr5M-wdm&UUK@Xl!Kp4`>pm-4a6ebm1L$W%2S|t4hddt|*A4)~QUSG%T|}PQ zVF8MHqc=R1^YSkrSk&fVOs3H3(i34cc=sqLa#%J^b-l3=YosMRN;V`Ozxpa;R>DXf z?ilet>zhzY+0C+TvulW0;)ktTf^!YLdOO?wRy@(d0{2litX5kD_0$>l382o-B-8~Q zZK*WSv{h68d54;MV0k>-88`D-gHhD(Fe5fI{8Lc%{Fb55h>KXK=*(-Hc!zh3hm`n| z!k+rm>dSyPIj+f*;!9RMo(LS^T+B9C!db76P~Zz`;H4|65@am(ZH}~nMae<}{dzT> z*y2Fwp<`xMYSptEzSUW3pLm{ixf%+aNNB|xs5&R4MuUvkB+Sr>)h&08&S*SG7lD?)#IMm5)xMGXW8BCO@t#o|tz$ltbv_dHMydkS=8H;R{2qSJSh)9&#%C zSH;7z^rrM@WqCOA>Fj)y$^5ZL*qBkahUVV%EKQ#wH^RQXMHNt|g=03k>e}bWtX(RX zW}~S6>qfx)wx2u{btj7tK<^-m1Kss0xeaLcL((^6#s~R<8B=~%k$jyi-m23eH9wE>ial0)X#n-N&{!G~T?bTzWSYDX6uXrf=6e zo~Nc4dF29y(h%N#zu7wyze*3;H9@$cUsVb@FrohG3gF zRR3KTclFcfGcB(v|QZf>=n?!AKQWU1OcF?xawKLNX&_Y`Db{p!B zvwT;i4uXE2DO63qCB+SABq@y97Jl-Z3}d<7b}v@}0&8!c-#64DxEkEGjvk?^6p>ZvAPW zblpwas&MuzhYG!3v2Kd7uhma-u{T6Q0Sh-#$tWU)hx7>cMMT7px;MYF<&Lto%a zd~(=}F$MKzcAQJwN!-p=EW@$nPhrip2Jug!qx&axUJd{N$m{Q&>gVBSU;TTd8oA}1 zB4A4^IBy1?w#qpb9cXYL2N%Egg#(zGJG@CuDpCSm1B{>qXC0hXuC1NhP;`dXg(;#` zIZM*iZ6JE1WcuO=`qE&S9QZ_rq5LqkY%&&Kv8;Q_5~wJri$a7b=2dS{^pQ%z#8y?2 zA813xF~#G{YINc#q8pQ6r*|fS_*J$180Fxz6K+FbyUKLA%d-wOkQ*I7H84A%X4ktk zx~fh_fM#t3>Q(^g3Ke#({FtxSA9DYYfF}rju=rj@hw(tF zY2j9oV$om2*R!u+^ULymAH9p(H9XVE!i zRz{%EJbxN*_$a(b(ljfvlnPzp7$bqzXrQE75wIUCAU@EkQhdlh#$t)A;~TMwNLae` zMc@I+c{u6^?C+Px8b?|4ZD5Lro6E`WDg6 zmHHEtIf3O%;4V9}@>a7)F{-WBj`DFUP{>8pN2+a?pc{ofo2JcLu-&{{UZWF=;LKP! zbWN#$MF23=MI#=&)g<~<>%j%1@;yNm56U5dTG92wukK;`sP_oiMQuXYXG)>Sdoqtm z7b|2+gZftu9{TuW>*ahMp8Jqt(RW$ad(@m>Qs`w|qFOmA-Itr2L23|FHFG*K*aULA zzgTt|?u%2IKQd#_OXuSQu$vhEY)1@ANA>cBt3rI+9p3>ToGyn5$NL%^PTgq6u5SxY z3KjQ$_*cYWICwPN;8r*qdt+Q5B-*i1Tw1Qm$C9{YNQYDKIrnI!jd5w=@DOm*Irc1= z(!7y)^N@MNS_c#1+qQS~xOU;bDq?;`Yo&ls(=bH#P{5_*h{QwSrF&-bn6hR5SstC@ zODcLasZcz6f(*Ef&44d-E+5)y!-?>DK#4c7tt(qD^r#&};XYCqjh)B_Y1~2_(l}k) zr9-%Fp2K+!wc@T~s8XV3N>w|zJQswri3L4hnT;=HmRB+IG$Tw$AIPa1N;;0wLxI#IYTE{e+r&P4Zbf!9r}qt8nJe6Q`97VzsQL=a``i=e zHd)7Tn>eJ^v=!~yh9v8U)$Mo@;Co>8D;An2H5NM^Hi~Dsgq>qR5K8CcY1u3R77S_b zG96(EU6UpYqb}@QB<9{E1&vwqWNUdyfz}SFz=up-lXNFpnH!?5Tj(QFApGx#BVD&hk~ldpjf&OE$<;(#P-WYfY(H z-&qqG)UHGc#+$|IB8Y2MSum!!G9>G(Ixr(&WYHs?)#LBwk2P|)uaj_Sd&Soi?iCfd z^2|1~`dFCg-~8lOzNr%0^}}lChoAdAJOT;gKkWQnQu>yi|0Pu+w{Lg2dQFx8R=i7* z-tIBKq$-3CR;vF8gZ;aKyTs!ylln`lLWW^=>vvxDckR36+ATTxOR7TZV4nU*`xjOD zyZT+a>6U@}B~>8=uo>as`MBTh+@(rx$*Esb6(Wi9)6Q?y)c>Taem8oTN4RBKeo0lx zAnH$}|BrL|-NN1V^OkS;B~>9v=zm%G5Bu=D>fJf%zvGGn%a8xDt^RJ{ZnwT2r+!IQ zNH#3YFavjotKXIHwyxWT{!6MtO!5Dt{HON*yTQA;f7|hXNmWQJ%)7t;&EE$9>3^Ck U$guFi!C}EZjIexqLvnliKf;%LX#fBK literal 0 HcmV?d00001 diff --git a/results/tx_enrich/go_terms.csv b/results/tx_enrich/go_terms.csv new file mode 100644 index 0000000..ddc0a4d --- /dev/null +++ b/results/tx_enrich/go_terms.csv @@ -0,0 +1,22 @@ +ID,Description,GeneRatio,BgRatio,pvalue,p.adjust,qvalue,geneID,Count,group +GO:0030858,positive regulation of epithelial cell differentiation,3/25,64/18723,8.30298595424994e-5,0.04799125881556465,3.75e-02,PRKCH/NME2/PROM1,3,aINS_female +GO:0002181,cytoplasmic translation,9/172,148/18723,9.284720354690927e-6,0.022459738537997355,2.17e-02,RPL27/RPL7/RPL24/RPS27/RPL22/EIF3CL/RPL38/EIF3L/RPS3,9,Cg25_male +GO:0002181,cytoplasmic translation,20/354,148/18723,6.034935546363268e-12,1.8702265258179768e-8,1.78e-08,RPL36A/RPL27/RPS19/RPL39/RPS10/UNK/RPS15A/RPL18/EIF3A/RPL23/RPL10/RPS7/RPS14/RPS23/RPL3/RPS27A/EIF3G/RPL7A/RPL13A/RPL26,20,OFC_female +GO:0000377,"RNA splicing, via transesterification reactions with bulged adenosine as nucleophile",21/354,320/18723,8.527948419500151e-7,7.696906681208437e-4,7.33e-04,HNRNPA2B1/HNRNPA1/HNRNPH3/CASC3/SFPQ/NCL/SART1/DDX46/SF1/RNPS1/HNRNPA3/RBM17/DDX39B/HNRNPM/SRSF5/C1QBP/PNN/ZCRB1/SRPK3/YJU2/RBM10,21,OFC_female +GO:0000398,"mRNA splicing, via spliceosome",21/354,320/18723,8.527948419500151e-7,7.696906681208437e-4,7.33e-04,HNRNPA2B1/HNRNPA1/HNRNPH3/CASC3/SFPQ/NCL/SART1/DDX46/SF1/RNPS1/HNRNPA3/RBM17/DDX39B/HNRNPM/SRSF5/C1QBP/PNN/ZCRB1/SRPK3/YJU2/RBM10,21,OFC_female +GO:0000375,"RNA splicing, via transesterification reactions",21/354,324/18723,1.0422977974782387e-6,7.696906681208437e-4,7.33e-04,HNRNPA2B1/HNRNPA1/HNRNPH3/CASC3/SFPQ/NCL/SART1/DDX46/SF1/RNPS1/HNRNPA3/RBM17/DDX39B/HNRNPM/SRSF5/C1QBP/PNN/ZCRB1/SRPK3/YJU2/RBM10,21,OFC_female +GO:0022900,electron transport chain,15/354,175/18723,1.2418371541155916e-6,7.696906681208437e-4,7.33e-04,COX3/UQCRQ/UQCR11/SDHD/NDUFB2/COX7C/GBA/COX7B2/CHCHD2/GSR/PARK7/SDHB/NDUFB10/ADH5/COX6C,15,OFC_female +GO:0022904,respiratory electron transport chain,12/354,114/18723,1.698069370239057e-6,8.770528297284729e-4,8.35e-04,COX3/UQCRQ/UQCR11/SDHD/NDUFB2/COX7C/GBA/CHCHD2/PARK7/SDHB/NDUFB10/COX6C,12,OFC_female +GO:0009060,aerobic respiration,15/354,189/18723,3.252170243494876e-6,0.0014397822263700888,1.37e-03,COX3/UQCRQ/UQCR11/SDHD/ANTKMT/NDUFB2/COX7C/NNT/COX7B2/CHCHD2/PARK7/PDHB/SDHB/NDUFB10/COX6C,15,OFC_female +GO:0045333,cellular respiration,16/354,230/18723,8.390432950595276e-6,0.0032502439642368448,3.09e-03,COX3/UQCRQ/UQCR11/SDHD/ANTKMT/NDUFB2/COX7C/NNT/GBA/COX7B2/CHCHD2/PARK7/PDHB/SDHB/NDUFB10/COX6C,16,OFC_female +GO:0008380,RNA splicing,23/354,434/18723,9.56260978898458e-6,0.003292725304007024,3.13e-03,HNRNPA2B1/HNRNPA1/HNRNPH3/CASC3/SFPQ/NCL/SART1/DDX46/SF1/RNPS1/HNRNPA3/RBM17/CTNNBL1/DDX39B/HNRNPM/FUS/SRSF5/C1QBP/PNN/ZCRB1/SRPK3/YJU2/RBM10,23,OFC_female +GO:0042773,ATP synthesis coupled electron transport,10/354,95/18723,1.2495335857215579e-5,0.003520276892864644,3.35e-03,COX3/UQCRQ/UQCR11/SDHD/NDUFB2/COX7C/CHCHD2/PARK7/NDUFB10/COX6C,10,OFC_female +GO:0042775,mitochondrial ATP synthesis coupled electron transport,10/354,95/18723,1.2495335857215579e-5,0.003520276892864644,3.35e-03,COX3/UQCRQ/UQCR11/SDHD/NDUFB2/COX7C/CHCHD2/PARK7/NDUFB10/COX6C,10,OFC_female +GO:0006119,oxidative phosphorylation,12/354,141/18723,1.5525975786513112e-5,0.004009583246867011,3.82e-03,COX3/UQCRQ/UQCR11/SDHD/ANTKMT/NDUFB2/COX7C/COX7B2/CHCHD2/PARK7/NDUFB10/COX6C,12,OFC_female +GO:0022618,ribonucleoprotein complex assembly,15/354,220/18723,2.0326057552656432e-5,0.0048454194119755606,4.61e-03,RPS19/SART1/SF1/DHX30/EIF3A/RPL10/DDX39B/RPS14/RPL3/AGO4/EIF3G/SRSF5/RPL13A/SRPK3/YJU2,15,OFC_female +GO:0022613,ribonucleoprotein complex biogenesis,23/354,463/18723,2.6717121336838507e-5,0.0059140256444901815,5.63e-03,RPL27/RPS19/NOP56/SART1/NOLC1/SF1/DHX30/EIF3A/RPL10/DDX39B/RPS7/RPP40/RPS14/RPL3/AGO4/EIF3G/SRSF5/RPL7A/C1QBP/RPL13A/RPL26/SRPK3/YJU2,23,OFC_female +GO:0071826,ribonucleoprotein complex subunit organization,15/354,227/18723,2.9313781484128114e-5,0.006056227254620868,5.76e-03,RPS19/SART1/SF1/DHX30/EIF3A/RPL10/DDX39B/RPS14/RPL3/AGO4/EIF3G/SRSF5/RPL13A/SRPK3/YJU2,15,OFC_female +GO:1903311,regulation of mRNA metabolic process,17/354,288/18723,3.71319720449354e-5,0.0071281511815515786,6.78e-03,SUPT5H/HNRNPA1/LARP1/NCL/SF1/RNPS1/POLR2G/TENT4A/HNRNPM/NBAS/SAFB/FUS/TNRC6B/C1QBP/TBRG4/SRPK3/RBM10,17,OFC_female +GO:0019646,aerobic electron transport chain,9/354,87/18723,3.910247501980537e-5,0.0071281511815515786,6.78e-03,COX3/UQCRQ/UQCR11/SDHD/NDUFB2/COX7C/PARK7/NDUFB10/COX6C,9,OFC_female +GO:2001252,positive regulation of chromosome organization,8/354,82/18723,1.5920489566435716e-4,0.027409776203546822,2.61e-02,HNRNPA2B1/HNRNPA1/DNMT1/SFPQ/SETDB1/GTF2H2/SSBP1/SLX1A,8,OFC_female +GO:1902253,regulation of intrinsic apoptotic signaling pathway by p53 class mediator,5/354,29/18723,1.9198597909498622e-4,0.031313923642913806,2.98e-02,MARCHF7/ARMC10/UBB/RPS7/RPL26,5,OFC_female diff --git a/scripts/edger_diff_gene.R b/scripts/edger_diff_gene.R index 529a3db..00ea839 100644 --- a/scripts/edger_diff_gene.R +++ b/scripts/edger_diff_gene.R @@ -34,6 +34,11 @@ y <- scaleOffset(y, norm_mat) design <- model.matrix(~ 0 + ph + rin + group, data = ann) colnames(design)[3:ncol(design)] <- gsub("group", "", colnames(design)[3:ncol(design)]) +# design <- model.matrix(~ 0 + ph + rin + region:phenotype:gender, data = ann) +# colnames(design)[3:ncol(design)] <- sapply(strsplit(colnames(design)[3:ncol(design)], ":"), function(x) { +# paste(gsub("region", "", x[1]), gsub("phenotype", "", x[2]), gsub("gender", "", x[3]), sep = "_") +# }) + ct <- makeContrasts( aINS_female = aINS_MDD_female-aINS_CTRL_female, aINS_male = aINS_MDD_male-aINS_CTRL_male, @@ -50,17 +55,17 @@ ct <- makeContrasts( levels = design ) -# Filter low expression genes +# Filter genes of low expression keep <- filterByExpr(y, group = y$samples$group) y <- y[keep,] # TMM normalization -y <- calcNormFactors(y) +# y <- calcNormFactors(y) -# Estimate dispersions with +# Estimate dispersions with 'estimateGLMRobustDisp' y <- estimateGLMRobustDisp(y, design = design, verbose = T) -# Fit +# Fit model fit <- glmFit(y, design = design) # Extract results for each comparison @@ -68,7 +73,7 @@ fit <- glmFit(y, design = design) # Summary dataframe map_df(comp, function(c) { - cat("Comparison: ", c) + cat("Comparison: ", c, ) lrt <- glmLRT(fit, contrast = ct[, c]) df <- topTags(lrt, n = Inf, adjust.method = "BH", p.value = 0.05)$table diff --git a/scripts/gwas_intersections.R b/scripts/gwas_intersections.R index 88c651b..91c9733 100644 --- a/scripts/gwas_intersections.R +++ b/scripts/gwas_intersections.R @@ -1,38 +1,82 @@ + +# GWAS risk variants ------------------------------------------------------ + library(dplyr) -library(readr) -library(gwasrapidd) +library(purrr) -load("results/diff_exp/diff_df.rda") +# Get studies related to 'major depressive disorder' and 'unipolar depression'. +efo_id <- c( + unipolar_depression = "EFO_0003761", + major_depressive_disorder = "MONDO_0002009" +) +mdd_results <- get_studies(efo_id = efo_id, set_operation = "intersection") + +mdd_filtered <- mdd_results@publications %>% + filter(publication_date > "2018-01-01") + +# From the results above, we manually removed studies that involved different themes, +# such as other psychiatric conditions. The results are shown in 'mdd_filtered.csv' +mdd_filtered <- read.csv("results/tables/mdd_filtered.csv") +studies <- unique(mdd_filtered$study_id) + +# Gather results from association and variation annotation from the GWAS Catalog. +map_dfr(studies, function(study_id) { + + variants <- get_variants(study_id = study_id, set_operation = "intersection") -get_study_variants <- function(study_id) { + variant_gc_data <- variants@genomic_contexts %>% + dplyr::select(variant_id, chromosome_name, chromosome_position) + + variant_var_data <- variants@variants %>% + dplyr::select(variant_id, functional_class) + + variant_data <- inner_join(variant_gc_data, variant_var_data, by = c("variant_id")) - variants <- get_variants(study_id = study_id) + associations <- get_associations(study_id = study_id, set_operation = "intersection") - var_ensg_ids <- variants@ensembl_ids - var_variantinfo <- variants@variants %>% - select(variant_id, functional_class) + assoc_1 <- associations@risk_alleles %>% + dplyr::select(association_id, variant_id, risk_allele, risk_frequency, genome_wide) + assoc_2 <- associations@associations %>% + dplyr::select(association_id, pvalue, pvalue_description, range, beta_number, beta_direction) + + associations_data <- reduce(list(assoc_1, assoc_2), inner_join, by = "association_id") - var_ensg_ids %>% - left_join(var_variantinfo, by = "variant_id") %>% - mutate(study = study_id) + associations_data + + inner_join(associations_data, variant_data, by = "variant_id") %>% + distinct() -} +}) -> res_gwas -wray2018 <- 'GCST005839' -howard2018 <- 'GCST005902' -howard2019 <- 'GCST007342' -hyde2016 <- 'GCST006041' +# Filter alleles by their level of significance < 1e-6 +chrom <- c(1:22, "X", "Y", "MT") +res_gwas %>% + filter(!is.na(risk_allele), pvalue < 1e-6, chromosome_name %in% chrom) -> risk_alleles -studies <- c(wray2018, howard2018, howard2019, hyde2016) +# Get ensembl variation information +ensembl <- useEnsembl("snps", "hsapiens_snp") -gwas_mdd <- lapply(studies, get_study_variants) %>% - bind_rows() +# Get the correct gene names associated to each variant. +# This is important because the GWAS Catalog API doesn't provide consistent +# information about the gene-variant annotation. +alleles <- unique(risk_alleles$variant_id) -intersection <- diff_df %>% - inner_join(gwas_mdd, by = c("gene" = "ensembl_id")) %>% - unique() +dict <- getBM(attributes = c("ensembl_gene_name", "refsnp_id"), + filters = "snp_filter", + values = alleles, + mart = ensembl) -intersection %>% - write_csv("results/tables/gwas_intersection.csv") +# Join information from Ensembl variation +risk_alleles <- risk_alleles %>% + left_join(dict, by = c("variant_id" = "refsnp_id")) + +# Information about the risk alleles +n_distinct(risk_alleles$variant_id) + +# Gather information of TAGs and genes annotated for risk alleles +load("results/diff_exp/diff_df.rda") +intersection <- inner_join(risk_alleles, diff_df, by = c("ensembl_gene_name" = "gene")) +# Save save(intersection, file = "results/diff_exp/gwas_intersections.rda") +write.csv(intersection, file = "results/tables/gwas_intersection.csv", row.names = F, quote = F) diff --git a/scripts/network.R b/scripts/network.R index 7b9d019..b73f350 100644 --- a/scripts/network.R +++ b/scripts/network.R @@ -75,13 +75,13 @@ addGraph(rdp, g) # Using REDER, we selected the best visualization for our network. # Nodes and edges coordinates are saved as nodes2 and edges2 in 'results/networks' directory. -# Plot network layoout ---------------------------------------------------- +# Plot network layout ---------------------------------------------------- -# nodes <- read_tsv("results/networks/nodes2") -# edges <- read_delim("results/networks/edges2", delim = "\t") +nodes <- read_tsv("results/networks/model_nodes.txt") +edges <- read_delim("results/networks/model_edges.txt") -nodes <- read_tsv("~/Área de trabalho/redes/v3/nodes4") -edges <- read_delim("~/Área de trabalho/redes/v3/edges4", delim = "\t") +# Import nodes coordinates determined by vivagraph +layout <- read.csv("results/networks/layout.csv") # Mark nodes as GWAS nodes %<>% @@ -90,8 +90,8 @@ nodes %<>% # Plot g <- graph_from_data_frame(edges, nodes, directed = F) -V(g)$x <- nodes$x -V(g)$y <- nodes$y +V(g)$x <- layout[,1] +V(g)$y <- layout[,2] V(g)$size <- 1 V(g)$a <- ifelse(V(g)$alias %in% unique(diff_df$hgnc_symbol[diff_df$type == "DGE"]), 1, 0) V(g)$b <- ifelse(V(g)$alias %in% unique(diff_df$hgnc_symbol[diff_df$type == "DTE"]), 1, 0) @@ -104,7 +104,7 @@ ggraph(g, x = x, y = y) + data = as_data_frame(g, "vertices") %>% filter(gwas == "gwas"), colour = NA, n = 5, - pie_scale = 1.3, + pie_scale = 0.5, show.legend = F) + geom_scatterpie( cols = c("a", "b", "c"), @@ -113,18 +113,23 @@ ggraph(g, x = x, y = y) + pie_scale = 0.2, show.legend = F ) + - geom_node_text(aes(label = alias), size = 1.1, nudge_x = 10, nudge_y = 10) + + geom_node_text(aes(label = alias), size = 1.1, nudge_x = 2, nudge_y = 4) + #geom_node_label(aes(label = alias)) + scale_fill_manual(values = c("#0ac80aff", "#4f4affff", "#ff822fff")) + coord_fixed() + theme_graph() -> p # Save -svg(filename = "results/plots_paper/rede2.svg", height = 10, width = 10) + +if(!dir.exists("results/plots_paper/")) { + dir.create("results/plots_paper") +} + +svg(filename = "results/plots_paper/network.svg", height = 10, width = 10) print(p) dev.off() -# Percentage of total genes in the network: 43,72%% +# Percentage of total genes in the network: 51,52%% n_distinct(nodes$alias) / n_distinct(diff_df$hgnc_symbol) diff --git a/scripts/network_layout.R b/scripts/network_layout.R new file mode 100644 index 0000000..2f60416 --- /dev/null +++ b/scripts/network_layout.R @@ -0,0 +1,16 @@ + +# Create network layout with vivagraph ------------------------------------ + +library(easylayout) + +# Organize main layout +layout <- easylayout::vivagraph(g) + +# Pin unconnected nodes +layout <- easylayout::vivagraph(g, layout = layout, pin_nodes = TRUE, pinned_cols = 9, pinned_rows = 10) + +# Save layout +colnames(layout) <- c("x", "y") + +layout %>% + write.csv("results/networks/layout.csv", quote = F, row.names = F) diff --git a/scripts/organize_dge_dte_after_filtering.R b/scripts/organize_dge_dte_after_filtering.R index ac22cec..0ba17d8 100644 --- a/scripts/organize_dge_dte_after_filtering.R +++ b/scripts/organize_dge_dte_after_filtering.R @@ -16,7 +16,7 @@ imap_dfr(lrt_comp, function(x, y) { tibble::rownames_to_column("tx") %>% mutate(tx = gsub("\\.+\\d+", "", tx), group = y) %>% - select(tx, logFC, group) + dplyr::select(tx, logFC, group) return(df) }) -> logFC_tx @@ -30,7 +30,7 @@ df_res_padj_tx_out_filtered <- anti_join(df_res_padj_tx, outliers_samples_dte, b load("results/diff_exp/edger_gene_rin_ph_diff.rda") df_res_padj_gene_out_filtered <- anti_join(df_edger_ph_rin_group_gene, outliers_samples_dge, by = c("gene", "group")) -save(df_res_padj_gene_out_filtered, df_res_padj_tx_out_filtered, file = "df_res_dge_dte.rda") +save(df_res_padj_gene_out_filtered, df_res_padj_tx_out_filtered, file = "results/diff_exp/df_res_dge_dte.rda") diff --git a/scripts/outliers_edge_ppcseq_gene.R b/scripts/outliers_edge_ppcseq_gene.R index 4744c10..3099470 100644 --- a/scripts/outliers_edge_ppcseq_gene.R +++ b/scripts/outliers_edge_ppcseq_gene.R @@ -22,6 +22,8 @@ counts <- txi$counts # Identify outliers genes in each comparison group +ann$run <- rownames(ann) + comp <- paste(rep(unique(ann$region), each = 2), unique(ann$gender), sep = "_") map(comp, function(c) { diff --git a/scripts/plots.rmd b/scripts/plots.rmd index 8741963..f469e59 100644 --- a/scripts/plots.rmd +++ b/scripts/plots.rmd @@ -13,6 +13,7 @@ Load required packages: ```{r, warning=FALSE, message=FALSE} library(tidyverse) library(patchwork) +library(VennDiagram) library(UpSetR) library(ggnewscale) library(pals) @@ -20,7 +21,7 @@ library(magrittr) library(ggh4x) library(AnnotationDbi) library(org.Hs.eg.db) -library(xlsx) +library(openxlsx) library(extrafont) library(VennDiagram) library(ggvenn) @@ -151,7 +152,7 @@ df_plot %>% ggplot(aes(x = as.numeric(x_axis), y = n, fill = type)) + geom_bar(stat = "identity", position = "stack") + facet_grid(cols = vars(region)) + - scale_y_continuous(name = "Number of transcriptionally altered genes", limits = c(0, 350), breaks = seq(0, 350, 50), minor_breaks = F) + + scale_y_continuous(name = "Number of transcriptionally altered genes", limits = c(0, 460), breaks = seq(0, 460, 50), minor_breaks = F) + #facet_zoom(x = x_axis %in% c("Female", "Male", "Intersection")) + scale_fill_manual(name = "", values = color_scale) + scale_x_continuous("", @@ -263,8 +264,7 @@ df_plot2 <- bind_rows(tmp_1, tmp_2) df_plot2 %<>% mutate(exclusive = factor(exclusive, levels = c("2", "3", - "4", "5", - "Exclusive")), + "4", "Exclusive")), sex = factor(sex, levels = c("female", "male"), labels = c("Female", "Male")) ) %>% @@ -283,9 +283,12 @@ df_plot2 %>% summarise(n_total = sum(n)) -> tmp_6 # df_plot3 holds the number of genes in the intersection of females and males in each region -df_plot3 <- inner_join(tmp_6, tmp_5, by = "region") +df_plot3 <- left_join(tmp_6, tmp_5, by = "region") df_plot3 %<>% - mutate(p_intersect = n_intersection/n_total) + mutate( + n_intersection = ifelse(is.na(n_intersection), 0, n_intersection), + p_intersect = n_intersection/n_total + ) # Join exclusivity information and intersection information df_plot2 <- inner_join(df_plot2, df_plot3, by = c("region", "sex")) @@ -299,10 +302,9 @@ df_plot2 <- inner_join(df_plot2, tmp7, by = "sex") # Define colors to each intersection cols_intersects <- c( - "2" = "grey80", - "3" = "grey60", - "4" = "grey40", - "5" = "black", + "2" = "grey40", + "3" = "grey80", + "4" = "black", "Exclusive" = "#8a0cb1ff" ) @@ -434,7 +436,7 @@ lapply(c( }) # Create dataframe with gwas infos -df <- data.frame(hgnc_symbol = unique(gwas_intersections$gene_name), gwas = "gwas") +df <- data.frame(hgnc_symbol = unique(gwas_intersections$hgnc_symbol), gwas = "gwas") # Join gwas info with intersections info tmp <- inner_join(genes_by_sex, diff_df, by = c("hgnc_symbol")) @@ -484,35 +486,36 @@ ggsave("results/plots_paper/intersect_sex_by_gwas.png", width = 5, height = 4) load("results/important_variables/ann.rda") ann %>% + rownames_to_column("run") %>% dplyr::select(run, phenotype, gender, region) %>% count(phenotype, gender, region, name = "number_of_samples") %>% arrange(gender, region) %>% - write.xlsx(file = "results/tables/number_of_samples.xlsx", row.names = F) + openxlsx::write.xlsx(file = "results/tables/number_of_samples.xlsx", rowNames = F) ``` ## Supplementary Table 2 ```{r} diff_df %>% - write.xlsx(file = "results/tables/TAG.xlsx", row.names = F) + openxlsx::write.xlsx(file = "results/tables/TAG.xlsx", row.names = F) ``` ## Supplementary Table 3 ```{r} genes_by_group_female %>% - write.xlsx(file = "results/tables/intersection_tables.xlsx", row.names = F, sheetName = "Female_Intersections") + openxlsx::write.xlsx(file = "results/tables/intersection_tables.xlsx", row.names = F, sheetName = "Female_Intersections") genes_by_group_male %>% - write.xlsx(file = "results/tables/intersection_tables.xlsx", row.names = F, sheetName = "Male_Intersections", + openxlsx::write.xlsx(file = "results/tables/intersection_tables.xlsx", row.names = F, sheetName = "Male_Intersections", append = T) genes_by_sex %>% - write.xlsx(file = "results/tables/intersection_tables.xlsx", row.names = F, sheetName = "Sex_Intersections", + openxlsx::write.xlsx(file = "results/tables/intersection_tables.xlsx", row.names = F, sheetName = "Sex_Intersections", append = T) genes_by_regions %>% - write.xlsx(file = "results/tables/intersection_tables.xlsx", row.names = F, sheetName = "Regions_Intersections", + openxlsx::write.xlsx(file = "results/tables/intersection_tables.xlsx", row.names = F, sheetName = "Regions_Intersections", append = T) ``` @@ -530,7 +533,7 @@ tmp %>% # left_join(gene_name, by = c("genes" = "ENSEMBL")) %>% unique() %>% write_csv("results/tables/intersect_by_type_and_gwas.csv", quote_escape = "none") %>% - write.xlsx(file = "results/tables/intersect_by_type_and_gwas.xlsx", row.names = F, showNA = F) + openxlsx::write.xlsx(file = "results/tables/intersect_by_type_and_gwas.xlsx", row.names = F, showNA = F) overlap_list(l_group_female) %>% tibble::rownames_to_column("gene") %>% @@ -539,7 +542,7 @@ overlap_list(l_group_female) %>% arrange(desc(exclusive)) %>% unique() %>% write_csv("results/tables/intersect_regions_by_sex_female.csv", quote_escape = "none") %>% - write.xlsx(file = "results/tables/intersect_regions_by_sex_female.xlsx", row.names = F, showNA = F) + openxlsx::write.xlsx(file = "results/tables/intersect_regions_by_sex_female.xlsx", row.names = F, showNA = F) overlap_list(l_group_male) %>% tibble::rownames_to_column("gene") %>% @@ -548,7 +551,7 @@ overlap_list(l_group_male) %>% arrange(desc(exclusive)) %>% unique() %>% write_csv("results/tables/intersect_regions_by_sex_male.csv", quote_escape = "none") %>% - write.xlsx(file = "results/tables/intersect_regions_by_sex_male.xlsx", row.names = F, showNA = F) + openxlsx::write.xlsx(file = "results/tables/intersect_regions_by_sex_male.xlsx", row.names = F, showNA = F) ``` From c71b8e5bb1d7381e47f81f8c388e269ed3d9c0b2 Mon Sep 17 00:00:00 2001 From: Iara Souza Date: Wed, 3 May 2023 14:20:19 -0300 Subject: [PATCH 06/24] Biotype analysis redone beacuse of the new set TAGs --- scripts/enrichment.R | 1 + scripts/summarise_biotypes.R | 67 +++++++++++++++++++++++------------- 2 files changed, 45 insertions(+), 23 deletions(-) diff --git a/scripts/enrichment.R b/scripts/enrichment.R index 18628b6..4ff7329 100644 --- a/scripts/enrichment.R +++ b/scripts/enrichment.R @@ -84,6 +84,7 @@ transform_to_df <- function(enrichment, padj_cutoff = 0.05){ save_df <- function(enrichment, file){ enrichment %>% bind_rows() %>% + mutate(qvalue = scales::scientific(qvalue)) %>% write_csv(file=file) } diff --git a/scripts/summarise_biotypes.R b/scripts/summarise_biotypes.R index fc025a1..b000aef 100644 --- a/scripts/summarise_biotypes.R +++ b/scripts/summarise_biotypes.R @@ -1,21 +1,23 @@ library(dplyr) library(purrr) library(ggplot2) +library(patchwork) +library(stringr) library(rtracklayer) library(GenomicFeatures) -# 1. Carregando GTF --------------------------------------- -gtf <- "./data/Homo_sapiens.GRCh38.97.chr_patch_hapl_scaff.gtf.gz" +# 1. Load GTF --------------------------------------- +gtf <- "./data/genome/Homo_sapiens.GRCh38.97.gtf.gz" gtf_data <- import(gtf) -# 2. Lendo DGE/DTE e pegando os biotipos --------------------------------------- +# 2. Import DGE and DTE results and get feature biotypes ------------- load("./results/diff_exp/diff_df.rda") dge_genes <- diff_df %>% filter(type == "DGE") -# 2.1. Pegando biotipo dos DGE --------------------------------------- +# 2.1 Get DGE biotypes ----------------------------------------------- dge_w_biotype <- gtf_data[, c("gene_id", "gene_biotype")] %>% as.data.frame() %>% filter(gene_id %in% dge_genes$gene) %>% @@ -26,12 +28,12 @@ dge_w_biotype <- gtf_data[, c("gene_id", "gene_biotype")] %>% readr::write_csv(dge_w_biotype, "results/diff_exp/dge_w_biotype.csv") -# 2.2. Pegando biotipo dos DTE --------------------------------------- +# 2.2. Get DTE biotypes ---------------------------------------------- load("./results/diff_exp/diff_tx_corrected.rda") dte_genes <- df_res_padj_tx %>% dplyr::select(txID, transcript, group) %>% - filter(transcript < 0.01) + filter(transcript < 0.05) dte_w_biotype <- gtf_data[, c("transcript_id", "transcript_biotype")] %>% @@ -43,47 +45,66 @@ dte_w_biotype <- dplyr::select(transcript_id, transcript_biotype, group) readr::write_csv(dte_w_biotype, "results/diff_exp/dte_w_biotype.csv") - -# 2.3. Pegando biotipo dos DTU --------------------------------------- + +# 2.3. Get DTU biotypes --------------------------------------------- dtu_w_biotype <- readr::read_csv("results/ISA/dtu_w_biotype.csv") -# 3. Plotando as porcentagens --------------------------------------- -plot_biotype_bar <- function(data, id_col, n_col) { +# Plot --------------------------------------- +plot_biotype_bar <- function(data, id_col, n_col, color) { id_col <- enquo(id_col) n_col <- enquo(n_col) data %>% ggplot(aes(x = reorder(!!id_col, dplyr::desc(!!n_col)), y = !!n_col)) + - geom_col() + - scale_y_continuous(labels = scales::percent_format(scale = 1)) + + geom_col(fill = color) + + scale_y_continuous(labels = scales::percent_format(scale = 1), name = "", limits = c(0, 100)) + coord_flip() + - labs( - y = "Porcentagem de Genes", - x = "Biotipo", - ) - + theme_bw() + + theme(panel.grid.minor = element_blank(), + plot.margin = margin(-1, 0, -1, 0)) } dge_plot <- dge_w_biotype %>% group_by(gene_biotype) %>% summarise(biotype_n = n() / length(unique(dge_w_biotype$gene_id)) * 100) %>% ungroup() %>% - plot_biotype_bar(. , id_col = gene_biotype, n_col = biotype_n) + mutate(type = "DGE") %>% + dplyr::rename(biotype = gene_biotype) dte_plot <- dte_w_biotype %>% group_by(transcript_biotype) %>% summarise(biotype_n = n() / length(unique(dte_w_biotype$transcript_id))* 100) %>% ungroup() %>% - plot_biotype_bar(., id_col = transcript_biotype, n_col = biotype_n) + mutate(type = "DTE") %>% + dplyr::rename(biotype = transcript_biotype) dtu_plot <- dtu_w_biotype %>% group_by(iso_biotype) %>% summarise(biotype_n = n() / length(unique(dtu_w_biotype$isoform_id))* 100) %>% ungroup() %>% - plot_biotype_bar(., id_col = iso_biotype, n_col = biotype_n) + mutate(type = "DTU") %>% + dplyr::rename(biotype = iso_biotype) + +df_plot <- Reduce(bind_rows, list(dge_plot, dte_plot, dtu_plot)) +df_plot$biotype <- gsub("_", " ", df_plot$biotype) + +# Plot feature biotypes + +color_scale <- c("DGE" = "#0ac80aff", "DTE" = "#4f4affff", "DTU" = "#ff822fff") + +ggplot(df_plot, aes(x = reorder(biotype, dplyr::desc(biotype_n)), y = biotype_n, fill = type)) + + geom_col(show.legend = F) + + scale_y_continuous(labels = scales::percent_format(scale = 1), limits = c(0, 100)) + + facet_wrap(nrow = 3, ncol = 1, facets = vars(type), scales = "free_y", strip.position = "right") + + scale_fill_manual(values = color_scale) + + labs(x = "Feature biotypes", y = "% of feature biotype by the total features") + + coord_flip() + + theme_bw() + + theme(panel.grid.minor = element_blank()) -> biotype_plot + + +# Save +ggsave(biotype_plot, file = "results/plots_paper/biotype_plot.pdf", width = 7, height = 4) -ggsave(dge_plot, filename = "results/diff_exp/dge_biotypes.pdf") -ggsave(dte_plot, filename = "results/diff_exp/dte_biotypes.pdf") -ggsave(dtu_plot, filename = "results/diff_exp/dtu_biotypes.pdf") From 6c7b085742dbc3a702a1ffa588ca006f4544812f Mon Sep 17 00:00:00 2001 From: Iara Souza Date: Fri, 5 May 2023 10:20:54 -0300 Subject: [PATCH 07/24] Added relationship of samples to each patient --- results/tables/patients_metadata.csv | 266 +++++++++++++++++++++++ scripts/create_metadata_patients_table.R | 44 ++++ 2 files changed, 310 insertions(+) create mode 100644 results/tables/patients_metadata.csv create mode 100644 scripts/create_metadata_patients_table.R diff --git a/results/tables/patients_metadata.csv b/results/tables/patients_metadata.csv new file mode 100644 index 0000000..6362dd8 --- /dev/null +++ b/results/tables/patients_metadata.csv @@ -0,0 +1,266 @@ +sample_id,ph,rin,pmi,age,group,gender,region,patients +SRR6443679,6.57,7.2,32,49,MDD,male,nac,40 +SRR6443680,6.91,7.7,33.5,53,MDD,male,nac,51 +SRR5961796,6.49,7.9,12,47,CTRL,male,ofc,14 +SRR5961797,6,6.8,24,41,CTRL,male,ofc,17 +SRR5961798,6.67,7.1,29.5,31,CTRL,male,ofc,20 +SRR5961799,6.74,6.7,27.75,19,CTRL,male,ofc,23 +SRR5961800,6.42,7.7,19.5,46,CTRL,male,ofc,28 +SRR5961801,6.26,5.8,29.75,40,CTRL,male,ofc,32 +SRR5961802,6.57,7,32,49,MDD,male,ofc,40 +SRR5961803,6.68,7.8,18,33,CTRL,male,ofc,43 +SRR5961804,6.84,6.8,44.5,38,CTRL,male,ofc,45 +SRR5961805,6.91,8,33.5,53,MDD,male,ofc,51 +SRR5961806,6,4.8,19,39,MDD,male,ofc,56 +SRR5961807,6.75,7.5,24,55,CTRL,male,ofc,57 +SRR5961808,6.86,7.5,30,38,MDD,male,ofc,61 +SRR5961809,6.73,7.4,20,25,MDD,female,ofc,63 +SRR5961810,6.68,7.4,24,22,MDD,male,ofc,67 +SRR5961811,6.93,6.1,36,28,MDD,male,ofc,68 +SRR5961812,6.53,6.9,15,46,MDD,female,ofc,69 +SRR5961813,6.79,6.9,36,55,MDD,female,ofc,72 +SRR5961814,6.73,7.3,29.5,44,CTRL,female,ofc,74 +SRR5961815,6.96,5.7,27,29,MDD,male,ofc,84 +SRR5961816,6.93,8.8,32,68,MDD,male,ofc,93 +SRR5961817,6.37,6.8,18.5,39,MDD,male,ofc,105 +SRR5961818,6.81,7.8,49.5,40,MDD,female,ofc,111 +SRR5961819,6.95,6.5,50,63,MDD,male,ofc,113 +SRR5961820,6.55,6.2,56,25,MDD,female,ofc,114 +SRR5961821,6.77,8.3,28.5,54,MDD,female,ofc,117 +SRR5961822,6.56,7.9,49,48,MDD,male,ofc,120 +SRR5961823,6.85,6.8,56,67,MDD,male,ofc,124 +SRR5961824,6.83,6.1,59,46,CTRL,male,ofc,128 +SRR5961825,6.89,8.2,41,32,MDD,female,ofc,129 +SRR5961826,6.11,5.7,10,52,CTRL,male,ofc,150 +SRR5961827,6.5,8.5,2.5,55,MDD,female,ofc,153 +SRR5961828,6.4,6.8,7.5,79,CTRL,female,ofc,162 +SRR5961829,6.25,9.1,6.5,64,MDD,male,ofc,183 +SRR5961830,6.1,5.7,17,72,CTRL,female,ofc,189 +SRR5961831,6.7,6.7,12,41,MDD,female,ofc,198 +SRR5961832,6.4,8,4,29,CTRL,male,ofc,199 +SRR5961833,6.5,7.4,44,45,CTRL,female,ofc,201 +SRR5961834,6.5,8,17.5,48,MDD,female,ofc,205 +SRR5961835,7,8,106,82,CTRL,female,ofc,212 +SRR5961836,6.9,7.6,7.5,36,MDD,female,ofc,222 +SRR5961837,6.5,8.3,4.5,52,MDD,female,ofc,235 +SRR5961838,6.7,7.9,38,60,CTRL,female,ofc,236 +SRR5961839,7,6.1,2,22,CTRL,female,ofc,238 +SRR5961840,6.21,8.3,8.5,68,CTRL,female,ofc,242 +SRR5961841,6.27,7.3,3,59,MDD,female,ofc,246 +SRR5961842,6.76,7.4,23.5,59,CTRL,male,ofc,247 +SRR5961843,6.71,8.3,16,51,CTRL,female,ofc,249 +SRR5961844,6.49,7.8,12,47,CTRL,male,dlpfc,14 +SRR5961845,6,7.6,24,41,CTRL,male,dlpfc,17 +SRR5961846,6.67,6.9,29.5,31,CTRL,male,dlpfc,20 +SRR5961847,6.74,7.7,27.75,19,CTRL,male,dlpfc,23 +SRR5961848,6.42,7.7,19.5,46,CTRL,male,dlpfc,28 +SRR5961849,6.26,6.5,29.75,40,CTRL,male,dlpfc,32 +SRR5961850,6.57,7.8,32,49,MDD,male,dlpfc,40 +SRR5961851,6.68,7.2,18,33,CTRL,male,dlpfc,43 +SRR5961852,6.84,7.2,44.5,38,CTRL,male,dlpfc,45 +SRR5961853,6.91,7.7,33.5,53,MDD,male,dlpfc,51 +SRR5961854,6,6.6,19,39,MDD,male,dlpfc,56 +SRR5961855,6.75,7.2,24,55,CTRL,male,dlpfc,57 +SRR5961856,6.86,6.9,30,38,MDD,male,dlpfc,61 +SRR5961857,6.73,7.2,20,25,MDD,female,dlpfc,63 +SRR5961858,6.68,6.8,24,22,MDD,male,dlpfc,67 +SRR5961859,6.93,5.6,36,28,MDD,male,dlpfc,68 +SRR5961860,6.53,7.5,15,46,MDD,female,dlpfc,69 +SRR5961861,6.79,7.5,36,55,MDD,female,dlpfc,72 +SRR5961862,6.73,6.9,29.5,44,CTRL,female,dlpfc,74 +SRR5961863,6.96,7.6,27,29,MDD,male,dlpfc,84 +SRR5961864,6.93,8.8,32,68,MDD,male,dlpfc,93 +SRR5961865,6.37,7.6,18.5,39,MDD,male,dlpfc,105 +SRR5961866,6.81,6.7,49.5,40,MDD,female,dlpfc,111 +SRR5961867,6.95,7.4,50,63,MDD,male,dlpfc,113 +SRR5961868,6.55,7.1,56,25,MDD,female,dlpfc,114 +SRR5961869,6.77,7.7,28.5,54,MDD,female,dlpfc,117 +SRR5961870,6.56,7.7,49,48,MDD,male,dlpfc,120 +SRR5961871,6.85,7.2,56,67,MDD,male,dlpfc,124 +SRR5961872,6.83,8.2,59,46,CTRL,male,dlpfc,128 +SRR5961873,6.89,6.9,41,32,MDD,female,dlpfc,129 +SRR5961874,6.11,6.5,10,52,CTRL,male,dlpfc,150 +SRR5961875,6.5,7.5,2.5,55,MDD,female,dlpfc,153 +SRR5961876,6.4,5.9,7.5,79,CTRL,female,dlpfc,162 +SRR5961877,6.25,7.7,6.5,64,MDD,male,dlpfc,183 +SRR5961878,6.1,6.2,17,72,CTRL,female,dlpfc,189 +SRR5961879,6.7,6.4,12,41,MDD,female,dlpfc,198 +SRR5961880,6.4,7.5,4,29,CTRL,male,dlpfc,199 +SRR5961881,6.5,7.5,44,45,CTRL,female,dlpfc,201 +SRR5961882,6.5,7.3,17.5,48,MDD,female,dlpfc,205 +SRR5961883,7,6.8,106,82,CTRL,female,dlpfc,212 +SRR5961884,6.9,7.8,7.5,36,MDD,female,dlpfc,222 +SRR5961885,6.5,7.2,4.5,52,MDD,female,dlpfc,235 +SRR5961886,6.7,7.5,38,60,CTRL,female,dlpfc,236 +SRR5961887,7,6.4,2,22,CTRL,female,dlpfc,238 +SRR5961888,6.21,7.7,8.5,68,CTRL,female,dlpfc,242 +SRR5961889,6.27,8,3,59,MDD,female,dlpfc,246 +SRR5961890,6.76,8.1,23.5,59,CTRL,male,dlpfc,247 +SRR5961891,6.71,7.2,16,51,CTRL,female,dlpfc,249 +SRR5961892,6.49,8.3,12,47,CTRL,male,cg25,14 +SRR5961893,6,6.9,24,41,CTRL,male,cg25,17 +SRR5961894,6.67,7.9,29.5,31,CTRL,male,cg25,20 +SRR5961895,6.74,6.3,27.75,19,CTRL,male,cg25,23 +SRR5961914,6.81,7.5,49.5,40,MDD,female,cg25,111 +SRR5961915,6.95,7.6,50,63,MDD,male,cg25,113 +SRR5961916,6.55,5.9,56,25,MDD,female,cg25,114 +SRR5961917,6.77,6,28.5,54,MDD,female,cg25,117 +SRR5961918,6.56,6.4,49,48,MDD,male,cg25,120 +SRR5961919,6.85,7.6,56,67,MDD,male,cg25,124 +SRR5961920,6.83,5.6,59,46,CTRL,male,cg25,128 +SRR5961921,6.89,6.4,41,32,MDD,female,cg25,129 +SRR5961922,6.11,5.1,10,52,CTRL,male,cg25,150 +SRR5961923,6.5,6.3,2.5,55,MDD,female,cg25,153 +SRR5961924,6.1,5.3,17,72,CTRL,female,cg25,189 +SRR5961925,6.7,5.8,12,41,MDD,female,cg25,198 +SRR5961926,6.4,5.7,4,29,CTRL,male,cg25,199 +SRR5961927,6.5,7.6,44,45,CTRL,female,cg25,201 +SRR5961928,6.5,6.8,17.5,48,MDD,female,cg25,205 +SRR5961929,7,6.4,106,82,CTRL,female,cg25,212 +SRR5961930,6.9,7.3,7.5,36,MDD,female,cg25,222 +SRR5961931,6.5,5.5,4.5,52,MDD,female,cg25,235 +SRR5961932,6.7,7.3,38,60,CTRL,female,cg25,236 +SRR5961933,7,6.3,2,22,CTRL,female,cg25,238 +SRR5961934,6.21,6.1,8.5,68,CTRL,female,cg25,242 +SRR5961935,6.27,8,3,59,MDD,female,cg25,246 +SRR5961936,6.76,7.7,23.5,59,CTRL,male,cg25,247 +SRR5961937,6.71,6.4,16,51,CTRL,female,cg25,249 +SRR5961938,6.49,6.8,12,47,CTRL,male,ains,14 +SRR5961939,6,6.8,24,41,CTRL,male,ains,17 +SRR5961940,6.67,7.1,29.5,31,CTRL,male,ains,20 +SRR5961941,6.74,6.2,27.75,19,CTRL,male,ains,23 +SRR5961942,6.42,6.8,19.5,46,CTRL,male,ains,28 +SRR5961943,6.26,5.4,29.75,40,CTRL,male,ains,32 +SRR5961944,6.57,7.6,32,49,MDD,male,ains,40 +SRR5961945,6.68,7.9,18,33,CTRL,male,ains,43 +SRR5961946,6.84,6.7,44.5,38,CTRL,male,ains,45 +SRR5961947,6.91,6.2,33.5,53,MDD,male,ains,51 +SRR5961948,6,4.9,19,39,MDD,male,ains,56 +SRR5961949,6.75,5.7,24,55,CTRL,male,ains,57 +SRR5961950,6.86,7.3,30,38,MDD,male,ains,61 +SRR5961951,6.73,5.7,20,25,MDD,female,ains,63 +SRR5961952,6.68,6,24,22,MDD,male,ains,67 +SRR5961953,6.93,5.5,36,28,MDD,male,ains,68 +SRR5961954,6.53,4.3,15,46,MDD,female,ains,69 +SRR5961955,6.79,6.7,36,55,MDD,female,ains,72 +SRR5961956,6.73,6.2,29.5,44,CTRL,female,ains,74 +SRR5961957,6.96,5.7,27,29,MDD,male,ains,84 +SRR5961958,6.93,7.5,32,68,MDD,male,ains,93 +SRR5961959,6.37,7.8,18.5,39,MDD,male,ains,105 +SRR5961960,6.81,6.1,49.5,40,MDD,female,ains,111 +SRR5961961,6.95,4.6,50,63,MDD,male,ains,113 +SRR5961962,6.55,5.9,56,25,MDD,female,ains,114 +SRR5961963,6.77,6.1,28.5,54,MDD,female,ains,117 +SRR5961964,6.56,5.6,49,48,MDD,male,ains,120 +SRR5961965,6.85,5.8,56,67,MDD,male,ains,124 +SRR5961966,6.83,5.1,59,46,CTRL,male,ains,128 +SRR5961967,6.89,5.8,41,32,MDD,female,ains,129 +SRR5961968,6.11,5.5,10,52,CTRL,male,ains,150 +SRR5961969,6.5,7.2,2.5,55,MDD,female,ains,153 +SRR5961970,6.4,5.2,7.5,79,CTRL,female,ains,162 +SRR5961971,6.25,5.8,6.5,64,MDD,male,ains,183 +SRR5961972,6.1,5.6,17,72,CTRL,female,ains,189 +SRR5961973,6.7,6.7,12,41,MDD,female,ains,198 +SRR5961974,6.4,6.1,4,29,CTRL,male,ains,199 +SRR5961975,6.5,6.6,44,45,CTRL,female,ains,201 +SRR5961976,6.5,7.1,17.5,48,MDD,female,ains,205 +SRR5961977,7,6.3,106,82,CTRL,female,ains,212 +SRR5961978,6.9,8,7.5,36,MDD,female,ains,222 +SRR5961979,6.5,8.2,4.5,52,MDD,female,ains,235 +SRR5961980,6.7,8.6,38,60,CTRL,female,ains,236 +SRR5961981,7,7.7,2,22,CTRL,female,ains,238 +SRR5961982,6.21,8.4,8.5,68,CTRL,female,ains,242 +SRR5961983,6.27,8.3,3,59,MDD,female,ains,246 +SRR5961984,6.76,8.1,23.5,59,CTRL,male,ains,247 +SRR5961985,6.71,8.2,16,51,CTRL,female,ains,249 +SRR5961986,6.49,7.6,12,47,CTRL,male,nac,14 +SRR5961987,6,8,24,41,CTRL,male,nac,17 +SRR5961988,6.67,7.1,29.5,31,CTRL,male,nac,20 +SRR5961989,6.74,6.5,27.75,19,CTRL,male,nac,23 +SRR5961990,6.42,7.5,19.5,46,CTRL,male,nac,28 +SRR5961991,6.26,5.6,29.75,40,CTRL,male,nac,32 +SRR5961992,6.57,7.2,32,49,MDD,male,nac,40 +SRR5961993,6.68,7.8,18,33,CTRL,male,nac,43 +SRR5961994,6.84,5.9,44.5,38,CTRL,male,nac,45 +SRR5961995,6.91,7.7,33.5,53,MDD,male,nac,51 +SRR5961996,6,4.9,19,39,MDD,male,nac,56 +SRR5961997,6.75,4.4,24,55,CTRL,male,nac,57 +SRR5961998,6.86,7.7,30,38,MDD,male,nac,61 +SRR5961999,6.73,8.1,20,25,MDD,female,nac,63 +SRR5962000,6.68,8.4,24,22,MDD,male,nac,67 +SRR5962001,6.93,7.5,36,28,MDD,male,nac,68 +SRR5962002,6.53,8.4,15,46,MDD,female,nac,69 +SRR5962003,6.79,8,36,55,MDD,female,nac,72 +SRR5962004,6.73,7.2,29.5,44,CTRL,female,nac,74 +SRR5962005,6.96,7.7,27,29,MDD,male,nac,84 +SRR5962006,6.93,8.2,32,68,MDD,male,nac,93 +SRR5962007,6.37,7.5,18.5,39,MDD,male,nac,105 +SRR5962008,6.81,7.7,49.5,40,MDD,female,nac,111 +SRR5962009,6.95,7.8,50,63,MDD,male,nac,113 +SRR5962010,6.55,7.6,56,25,MDD,female,nac,114 +SRR5962011,6.77,8.7,28.5,54,MDD,female,nac,117 +SRR5962012,6.56,8.5,49,48,MDD,male,nac,120 +SRR5962013,6.85,8.3,56,67,MDD,male,nac,124 +SRR5962014,6.83,8.8,59,46,CTRL,male,nac,128 +SRR5962015,6.89,8.3,41,32,MDD,female,nac,129 +SRR5962016,6.11,6.8,10,52,CTRL,male,nac,150 +SRR5962017,6.5,7.7,2.5,55,MDD,female,nac,153 +SRR5962018,6.4,7.2,7.5,79,CTRL,female,nac,162 +SRR5962019,6.25,8.1,6.5,64,MDD,male,nac,183 +SRR5962020,6.1,7.4,17,72,CTRL,female,nac,189 +SRR5962021,6.7,7.5,12,41,MDD,female,nac,198 +SRR5962022,6.4,7.5,4,29,CTRL,male,nac,199 +SRR5962023,6.5,7.8,44,45,CTRL,female,nac,201 +SRR5962024,6.5,7.3,17.5,48,MDD,female,nac,205 +SRR5962025,7,7.6,106,82,CTRL,female,nac,212 +SRR5962026,6.9,7.8,7.5,36,MDD,female,nac,222 +SRR5962027,6.5,7.8,4.5,52,MDD,female,nac,235 +SRR5962028,6.7,8.3,38,60,CTRL,female,nac,236 +SRR5962029,7,8.2,2,22,CTRL,female,nac,238 +SRR5962030,6.21,8.2,8.5,68,CTRL,female,nac,242 +SRR5962031,6.27,9.1,3,59,MDD,female,nac,246 +SRR5962032,6.76,8.6,23.5,59,CTRL,male,nac,247 +SRR5962033,6.71,7.8,16,51,CTRL,female,nac,249 +SRR5962034,6.49,7.2,12,47,CTRL,male,sub,14 +SRR5962035,6,6.5,24,41,CTRL,male,sub,17 +SRR5962036,6.67,7.3,29.5,31,CTRL,male,sub,20 +SRR5962037,6.74,6.4,27.75,19,CTRL,male,sub,23 +SRR5962038,6.26,5.8,29.75,40,CTRL,male,sub,32 +SRR5962039,6.57,7.5,32,49,MDD,male,sub,40 +SRR5962040,6.68,6.7,18,33,CTRL,male,sub,43 +SRR5962041,6.84,7.4,44.5,38,CTRL,male,sub,45 +SRR5962042,6.91,7.5,33.5,53,MDD,male,sub,51 +SRR5962043,6,6,19,39,MDD,male,sub,56 +SRR5962044,6.75,6.7,24,55,CTRL,male,sub,57 +SRR5962045,6.86,7.3,30,38,MDD,male,sub,61 +SRR5962046,6.68,7.8,24,22,MDD,male,sub,67 +SRR5962047,6.53,7.7,15,46,MDD,female,sub,69 +SRR5962048,6.79,7.1,36,55,MDD,female,sub,72 +SRR5962049,6.73,7.3,29.5,44,CTRL,female,sub,74 +SRR5962050,6.96,8.3,27,29,MDD,male,sub,84 +SRR5962051,6.93,8.2,32,68,MDD,male,sub,93 +SRR5962052,6.37,8.7,18.5,39,MDD,male,sub,105 +SRR5962053,6.81,5.9,49.5,40,MDD,female,sub,111 +SRR5962054,6.95,9.4,50,63,MDD,male,sub,113 +SRR5962055,6.55,6.6,56,25,MDD,female,sub,114 +SRR5962056,6.77,7.4,28.5,54,MDD,female,sub,117 +SRR5962057,6.56,6.7,49,48,MDD,male,sub,120 +SRR5962058,6.85,7,56,67,MDD,male,sub,124 +SRR5962059,6.83,7.6,59,46,CTRL,male,sub,128 +SRR5962060,6.89,7.7,41,32,MDD,female,sub,129 +SRR5962061,6.11,6.3,10,52,CTRL,male,sub,150 +SRR5962062,6.5,6.7,2.5,55,MDD,female,sub,153 +SRR5962063,6.25,7,6.5,64,MDD,male,sub,183 +SRR5962064,6.1,5.1,17,72,CTRL,female,sub,189 +SRR5962065,6.7,7.4,12,41,MDD,female,sub,198 +SRR5962066,6.4,6.4,4,29,CTRL,male,sub,199 +SRR5962067,6.5,6.4,44,45,CTRL,female,sub,201 +SRR5962068,6.5,7.7,17.5,48,MDD,female,sub,205 +SRR5962069,6.9,6.6,7.5,36,MDD,female,sub,222 +SRR5962070,6.5,7.7,4.5,52,MDD,female,sub,235 +SRR5962071,6.7,7.3,38,60,CTRL,female,sub,236 +SRR5962072,7,7.3,2,22,CTRL,female,sub,238 +SRR5962073,6.21,7.6,8.5,68,CTRL,female,sub,242 +SRR5962074,6.27,7.6,3,59,MDD,female,sub,246 +SRR5962075,6.76,7.2,23.5,59,CTRL,male,sub,247 +SRR5962076,6.71,8,16,51,CTRL,female,sub,249 diff --git a/scripts/create_metadata_patients_table.R b/scripts/create_metadata_patients_table.R new file mode 100644 index 0000000..2f255be --- /dev/null +++ b/scripts/create_metadata_patients_table.R @@ -0,0 +1,44 @@ + +# Relate patients to their respective samples ----------------------------- + +library(dplyr) +library(tidyr) +library(janitor) + +# Get organized metadata about each patient ------------------------------- +# This metadata comes from the supplementary material that can be found here: +# http://neuroscience.mssm.edu/nestler/contecenter/Cohort%201%20Metadata.pdf +patients <- read.csv("~/Downloads/Metadata.csv") + +# Organize data for further merge +colnames(patients) <- make_clean_names(colnames(patients)) +patients <- patients %>% + pivot_longer(cg25:sub, names_to = "region", values_to = "rin") %>% + select(patients = samples, gender, region, group, age, pmi, ph, rin) %>% + mutate(across(where(is.numeric), ~ as.character(.)), + gender = tolower(gender)) + +# Get samples metadata ---------------------------------------------------- + +ann <- read.csv("data/meta/SraRunTable.txt", stringsAsFactors = F, header = T) +colnames(ann) <- tolower(colnames(ann)) +ann <- ann %>% + dplyr::select(run, ph, rin, pmi, age, phenotype, gender, tissue, organism) %>% + filter(organism == "Homo sapiens") %>% + mutate(region = case_when( + tissue == "Orbitofrontal (OFC; BA11)" ~ "OFC", + tissue == "Dorsolateral prefrontal cortex (dlPFC; BA8/9)" ~ "dlPFC", + tissue == "Cingulate gyrus 25 (Cg25)" ~ "Cg25", + tissue == "Anterior Insula (aINS)" ~ "aINS", + tissue == "Nucleus Accumbens (Nac)" ~ "Nac", + tissue == "Subiculum (Sub)" ~ "Sub" + ), + region = tolower(region)) %>% + dplyr::rename(sample_id = run) %>% + dplyr::select(sample_id, ph, rin, pmi, age, group = phenotype, gender, region) %>% + mutate(across(where(is.numeric), ~ as.character(.))) + + +patients_metadata_table <- inner_join(ann, patients, by = c("gender", "group", "region", "ph", "rin", "pmi", "age")) + +write.csv(patients_metadata_table, file = "results/tables/patients_metadata.csv", quote = F, row.names = F) From f95495f416c85fba7c0114d26943b5c7f3437260 Mon Sep 17 00:00:00 2001 From: Iara Souza Date: Mon, 8 May 2023 16:40:15 -0300 Subject: [PATCH 08/24] fix: added two genes df --- scripts/build_symreg_df.R | 51 +++++++++++++++++++++++++++++++++++++++ 1 file changed, 51 insertions(+) create mode 100644 scripts/build_symreg_df.R diff --git a/scripts/build_symreg_df.R b/scripts/build_symreg_df.R new file mode 100644 index 0000000..901aa2e --- /dev/null +++ b/scripts/build_symreg_df.R @@ -0,0 +1,51 @@ +library(dplyr) + +load("results/diff_exp/diff_df.rda") + +load("results/txi/txi_gene.rda") + +load("results/important_variables/ann.rda") + +get_expr_from_gene_list <- function(genelist, symbol_list) { + txi$abundance[rownames(txi$abundance) %in% genelist,] %>% + t() %>% + as.data.frame() %>% + tibble::rownames_to_column() %>% + setNames(., c("run", symbol_list)) +} + +metadata <- ann %>% + mutate(phenotype_reg = ifelse(phenotype == "MDD", 1, 0), + run = rownames(.)) %>% + dplyr::select(-c(group)) + +genes_interest <- diff_df %>% + filter(type == "DGE") %>% + dplyr::select(gene, hgnc_symbol) %>% + distinct() + +dge_tpms <- + get_expr_from_gene_list(genes_interest$gene, genes_interest$hgnc_symbol) + +full_data <- dge_tpms %>% + left_join(metadata, by = "run") + +selected_genes <- c("ATAT1", "DDX39B") + +two_genes_df <- diff_df %>% + filter(hgnc_symbol == selected_genes) %>% + dplyr::select(gene, hgnc_symbol) %>% + distinct() + +selected_tpms <- + get_expr_from_gene_list(two_genes_df$gene, selected_genes) + +two_gene_data <- selected_tpms %>% + left_join(metadata, by = "run") + +if(!dir.exists("results/sym_reg/")) { + dir.create("results/sym_reg/") +} + +readr::write_tsv(two_gene_data, "results/sym_reg/selected_genes_for_reg.tsv") +readr::write_tsv(full_data, "results/sym_reg/genes_for_reg.tsv") From 53f5c14a9b82028adbeb20c5d873f85874d3572d Mon Sep 17 00:00:00 2001 From: Iara Souza Date: Tue, 9 May 2023 11:20:48 -0300 Subject: [PATCH 09/24] chore: added new intersection tables, removed files saved in wrong places --- gwas_intersection.csv | 14 -- remaining_samples.sh | 39 ------ results/tables/TAG.xlsx | Bin 46822 -> 46822 bytes .../tables/intersect_by_type_and_gwas.xlsx | Bin 61458 -> 61459 bytes .../intersect_regions_by_sex_female.xlsx | Bin 46004 -> 46004 bytes .../tables/intersect_regions_by_sex_male.xlsx | Bin 33415 -> 33415 bytes results/tables/intersection_tables.xlsx | Bin 32241 -> 32242 bytes results/tables/number_of_samples.xlsx | Bin 6872 -> 6872 bytes scripts/teste | 125 ++++++++++++++++++ 9 files changed, 125 insertions(+), 53 deletions(-) delete mode 100644 gwas_intersection.csv delete mode 100644 remaining_samples.sh create mode 100644 scripts/teste diff --git a/gwas_intersection.csv b/gwas_intersection.csv deleted file mode 100644 index 8359231..0000000 --- a/gwas_intersection.csv +++ /dev/null @@ -1,14 +0,0 @@ -association_id,variant_id,risk_allele,risk_frequency,genome_wide,pvalue,pvalue_description,range,beta_number,beta_direction,chromosome_name,chromosome_position,functional_class,ensembl_gene_name,hgnc_symbol,group,type -41136253,rs58621819,T,0.2097,FALSE,2e-10,NA,[1.01-1.02],NA,NA,11,65547359,intron_variant,ENSG00000168056,LTBP3,OFC_female,DGE -41136409,rs12923444,C,0.4375,FALSE,2e-24,NA,[1.02-1.03],NA,NA,16,21628389,intron_variant,ENSG00000197006,METTL9,OFC_female,DGE -41135995,rs10789214,T,0.5661,FALSE,4e-10,NA,[1.009-1.018],NA,NA,1,66681134,intron_variant,ENSG00000118473,SGIP1,OFC_female,DTE -41136026,rs17641524,C,0.7909,FALSE,8e-20,NA,[1.02-1.03],NA,NA,1,197735587,splice_region_variant,ENSG00000213047,DENND1B,Cg25_male,DTE -41136085,rs45510091,A,0.9472,FALSE,8e-21,NA,[1.037-1.057],NA,NA,4,122265238,intron_variant,ENSG00000138688,BLTP1,Cg25_male,DGE -30547745,rs10127497,T,0.1382,FALSE,1e-08,NA,[0.0064-0.013],0.0097,increase,1,66584461,intron_variant,ENSG00000118473,SGIP1,OFC_female,DTE -30547749,rs6679379,T,0.2875,FALSE,3e-08,NA,[0.0047-0.0097],0.0072,increase,1,66733473,non_coding_transcript_exon_variant,ENSG00000118473,SGIP1,OFC_female,DTE -30547797,rs12118513,A,0.2148,FALSE,1e-07,NA,[0.0049-0.0103],0.0076,decrease,1,197547956,intron_variant,ENSG00000213047,DENND1B,Cg25_male,DTE -30547801,rs17641524,T,0.2086,FALSE,2e-07,NA,[0.0048-0.0102],0.0075,decrease,1,197735587,splice_region_variant,ENSG00000213047,DENND1B,Cg25_male,DTE -30547485,rs10929355,G,0.4558,FALSE,6e-09,NA,[0.005-0.01],0.0075,decrease,2,15258840,intron_variant,ENSG00000151779,NBAS,OFC_female,DGE -64732910,rs2894699,T,0.4305,FALSE,4e-09,NA,[0.017-0.033],0.024859993,decrease,7,114419101,intron_variant,ENSG00000128573,FOXP2,Sub_male,DGE -64733014,rs7146581,T,0.2246,FALSE,2e-08,NA,[0.018-0.037],0.027423386,increase,14,102834735,intron_variant,ENSG00000131323,TRAF3,Nac_female,DTE -64733043,rs2369818,T,0.4386,FALSE,3e-08,NA,[0.015-0.031],0.023054866,increase,16,21602688,intron_variant,ENSG00000197006,METTL9,OFC_female,DGE diff --git a/remaining_samples.sh b/remaining_samples.sh deleted file mode 100644 index a65496c..0000000 --- a/remaining_samples.sh +++ /dev/null @@ -1,39 +0,0 @@ -curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/002/SRR5961862/SRR5961862_2.fastq.gz -o SRR5961862_2.fastq.gz -curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/003/SRR5961863/SRR5961863_2.fastq.gz -o SRR5961863_2.fastq.gz -curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/004/SRR5961864/SRR5961864_1.fastq.gz -o SRR5961864_1.fastq.gz -curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/004/SRR5961864/SRR5961864_2.fastq.gz -o SRR5961864_2.fastq.gz -curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/008/SRR5961938/SRR5961938_2.fastq.gz -o SRR5961938_2.fastq.gz -curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/007/SRR5961937/SRR5961937_1.fastq.gz -o SRR5961937_1.fastq.gz -curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/007/SRR5961937/SRR5961937_2.fastq.gz -o SRR5961937_2.fastq.gz -curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/002/SRR5961942/SRR5961942_1.fastq.gz -o SRR5961942_1.fastq.gz -curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/002/SRR5961942/SRR5961942_2.fastq.gz -o SRR5961942_2.fastq.gz -curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/000/SRR5961940/SRR5961940_1.fastq.gz -o SRR5961940_1.fastq.gz -curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/000/SRR5961940/SRR5961940_2.fastq.gz -o SRR5961940_2.fastq.gz -curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/003/SRR5961943/SRR5961943_1.fastq.gz -o SRR5961943_1.fastq.gz -curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/003/SRR5961943/SRR5961943_2.fastq.gz -o SRR5961943_2.fastq.gz -curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/004/SRR5961944/SRR5961944_1.fastq.gz -o SRR5961944_1.fastq.gz -curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/004/SRR5961944/SRR5961944_2.fastq.gz -o SRR5961944_2.fastq.gz -curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/006/SRR5961946/SRR5961946_1.fastq.gz -o SRR5961946_1.fastq.gz -curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/006/SRR5961946/SRR5961946_2.fastq.gz -o SRR5961946_2.fastq.gz -curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/005/SRR5961945/SRR5961945_1.fastq.gz -o SRR5961945_1.fastq.gz -curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/005/SRR5961945/SRR5961945_2.fastq.gz -o SRR5961945_2.fastq.gz -curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/007/SRR5961947/SRR5961947_1.fastq.gz -o SRR5961947_1.fastq.gz -curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/007/SRR5961947/SRR5961947_2.fastq.gz -o SRR5961947_2.fastq.gz -curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/008/SRR5961948/SRR5961948_1.fastq.gz -o SRR5961948_1.fastq.gz -curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/008/SRR5961948/SRR5961948_2.fastq.gz -o SRR5961948_2.fastq.gz -curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/009/SRR5961949/SRR5961949_1.fastq.gz -o SRR5961949_1.fastq.gz -curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/009/SRR5961949/SRR5961949_2.fastq.gz -o SRR5961949_2.fastq.gz -curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/000/SRR5961950/SRR5961950_1.fastq.gz -o SRR5961950_1.fastq.gz -curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/000/SRR5961950/SRR5961950_2.fastq.gz -o SRR5961950_2.fastq.gz -curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/001/SRR5961951/SRR5961951_1.fastq.gz -o SRR5961951_1.fastq.gz -curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/001/SRR5961951/SRR5961951_2.fastq.gz -o SRR5961951_2.fastq.gz -curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/002/SRR5961952/SRR5961952_1.fastq.gz -o SRR5961952_1.fastq.gz -curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/002/SRR5961952/SRR5961952_2.fastq.gz -o SRR5961952_2.fastq.gz -curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/003/SRR5961953/SRR5961953_2.fastq.gz -o SRR5961953_2.fastq.gz -curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/004/SRR5961954/SRR5961954_1.fastq.gz -o SRR5961954_1.fastq.gz -curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/004/SRR5961954/SRR5961954_2.fastq.gz -o SRR5961954_2.fastq.gz -curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/005/SRR5961955/SRR5961955_1.fastq.gz -o SRR5961955_1.fastq.gz -curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/005/SRR5961955/SRR5961955_2.fastq.gz -o SRR5961955_2.fastq.gz -curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/006/SRR5961956/SRR5961956_1.fastq.gz -o SRR5961956_1.fastq.gz -curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/006/SRR5961956/SRR5961956_2.fastq.gz -o SRR5961956_2.fastq.gz -curl -L ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR596/007/SRR5961957/SRR5961957_1.fastq.gz -o SRR5961957_1.fastq.gz diff --git a/results/tables/TAG.xlsx b/results/tables/TAG.xlsx index edc87b7bd9cd94ecb40c72dc35394a4bf4d281ba..a7eea9861b185bcedd814f8874693ae1f0ee19cb 100644 GIT binary patch delta 519 zcmaF%mg(7BCf)#VW)=|!4h{|m-tH9}c@-F$f%Ikr#uZ@34V2c=kg25>7+ zy%+kVaI=@V%16d6Eyps}oZz&LycQ$T{{37;iQ__lC70h_Z=5&u1nGaf(R6;%n#G$; z*R=}F&vV!92*07I`}t4THVFqOhFh0|tm_}0n0dVAZ}}1temYrm_T`o*znBBO**OlsZ)ucfWMI%?VqicC$;}F^T9BahW$T16 zZn96*1_y4gF$WWvQDNH83TALw?|`T|YNHEbe6>AT3J&<4o6W%Vr_FX?+IWjK2QWgy xKsHY<+hPtD+_1$JO#j#t1g3qr+Jou-trlSV)K-XQ?rm0JzQ;B{FgIJ+@+vSg1L@5Mj4Qy5$+wwafCMHVV>YOFVm$4s z>R=nl*{LM3ed^v^U7_2XVlRFAYN5%ZWKpyw{oC7&c749w$$J)lKJ}tYB+^gl${~-X z+eIs5^e=l)`oR$8lx!0Aq+^~=mR`@{>U5o53ofV&E~<4cQ;cw1DQ=x}Fg@^E;7y6^ zP96T+mx>+H&Y3u^(r&pf+XR7zZ(FYP)ms!jGEDq0t9i6zOZ9ag22BmK8;khniA6f@ z-^&>L`oE0Cl#7)gvPw#0r!)89h5y2Srr!}}Ociq8Sg>W|X8os`WyQPWChaO zV>asSNqH`=|M%0$nzJvrJo&{O;LXkvlCLK%&B(x@!^FUV5|W!0ShXNQ>C4s$VccY& zs0|L>Tw@LpB2pDvfcqvbJRu`!uV=?uoN8dJ2#tw=}(*Oz_jreYYt$9gn?|H uT(-p=EVyBdE13SVB?wIWZnX!~{aY=-^r@{7&D`6pzx!DtMOnWu*|mwo%;=)&Ad*I>Otm2 z(J#lPFKqpHztK^0F8g}7@av_K=F&BWfsXNE-}{|^guMJWfywji(u6~bERVBT`Ieaf z=6~?zy1Do?(+7vO!ZrqKCeuuIg+#mGNlUUAZl*e=t3A=b~o06L;mR-GcYap)(%X^zqRHB#z+|0 z=E;lSLS*l}m1YuVovg9VR=xgJ`dO zC(U?f^3-?AU@LaNleQ@{W?-nu(JwBk%t1H)oz1_oh-sSH~h z8z&3BSBe3-QS)4nbRE#@ZOjY|{3vRKt-;2Z=NDxs<>zN(v!L8P;=_HQrW9b%Dx+vV nH+jN)BYBVoZue^>Ca+^)n0twhK>|h1zsV2ZYqMQ{0}=!PBNPQq delta 728 zcmbRIfO*mbX5IjAW)=|!4h{~6{28-0@+vSg1L@5Mj4Qy5$+wwafCMHVW7e;)3t*i# z*{h*yk&uw9LY{W@?I@LPsk@gveOVa9;ZpD<bCN^8$)#~`HZsq5jdV}V zj$v1{yW1BfuzrJc)U%&WWfBff3|1F{>a8E1n0dVAZ}}1t;Y)Hc)=Wzl+(>G-s)$Nq z{riorWbXgsgb=mo7gwLW`n~pA_+ouEtrwqvy-VbouVpI}q>#Bo#K)o~A!hM`#xKu4 z@Xh)6GI=)@_43=HZF2(YEmezM~`i1w;? z(u}7kPkW~fwqg&ES33E|I~jS9MLje4Sp!)a7#2%2FbE^GGi+&Wm@NEWDF&oQ^IVT~ z9ng+#%nS_tC~AbP85k;Z^vm;$vXk=jv-K)+bI=`F?jG^sK2TE%FbtJZG@qS3@x74( m$O5B8F)+-%#Ks_jqUNvdWGOqT$$#Gquw8otk^un50ugcm diff --git a/results/tables/intersect_regions_by_sex_female.xlsx b/results/tables/intersect_regions_by_sex_female.xlsx index 316c8d103e12240f914d5f95c291d0bbb85bccaf..8804198c8f2fa35da83a007faf33018ab35d712c 100644 GIT binary patch delta 531 zcmdn;oN3E*Cf)#VW)=|!4h{|mzU~zpc@-F$f%Ikr#uZ@3Sgb}YRd#A`p>E5MlISeQJqN`y>t{X>-*S{ei0Q(-X}1L3{cP0U+?*KHBi;emO3EVe7y9jgFFY+1I;;UoVX`m##4kbc_%C-tYV)Gj=A~~h zf30e<^7NiLOMj-$I)DABskVNEW&PXf{?D@gmaAT$AK=Z-k)$nk z61%7s4p_=S>7hLi+|YFnwTy z9hhd^Xw3nPoG_5hlU+8Ng9Yn0x`OFr8-u{K^d@^S9lOZ_OwZT^(R_206__u!*$+&o HZ}tTMARpOe delta 531 zcmdn;oN3E*Cf)#VW)=|!4h{~6h8eRq@+vSg1L@5Mj4Qy5$+wwafCMHVV^*mT^ge7L z()!=)WcBPV($3De8c)rW;qVi=uXpmUSkB}LDP^Cp&n}IU{k7xxlR3Zd9=1)|_x{!! z+1d-&t}M}!IC;Ti^_H7go@8!4vED;WNrH8)X~bk^HlzHOEpqaEN?$BKHbJ$6)AZ)C z7Zyt$^ENgIsN7UZ&8=lOwEf#=H6ee4V^qDN*g_3XnlKf^`i3;kI_BDsz}KDhMUzNybo zzP+2}XfdlRbn+bE&sp2F)?3alIu_S|`usC#$MfEKc8meu>>Nhvv1_Cm85ne!7#L7O zb+ZDi79?1G**YPNo9x22;DCPb!odV){BrAO1v7elc0km)`{_a$<^H^h;7DlSUvfRPghvU#%0Msu)W-9}e1eQaY8n3mpT52j-`S%B#on;@ERZn6UN#Wwqa I>GaLM0Le`3RsaA1 diff --git a/results/tables/intersect_regions_by_sex_male.xlsx b/results/tables/intersect_regions_by_sex_male.xlsx index e5954d91910318201422f8c42e75f25134da4607..1ab8a4150edcfb11e906f706ba5c1661f565c8b6 100644 GIT binary patch delta 531 zcmZo~WomC_;tlX-W)WfF;NW23>t3;uSAmfkNN+Y^TmfcGzRmOkBry3Hvr7G0zrzLs zE%BbCqSiOzD|b5Ja^e&+M=Ek_xIm@dqlc1zIR&qnRd&51!h9=prW zGE8VnYSw-AAakPVm*dhGw*I@{=qNdteZ5=w_0mXl=^Dd8$M~@C{mwr^UjCcF38v`}+`-GpzPpv;{D;S_=D8lV7ZT&lJUi$X( z*QypPPw$zt^k?d<^Vg4>YU@W>*1w(Z|18^Yx$5=#0p9E!N!kLL(u@oYI!p`Xk|2N`b0yDTw`&q$^IaWI$YQk-FA&hq03y$DOh^jXO)06A% z!1R@RYYt%Kgn?|HEZ$%a77T1~1=BMdg242<2754V&}adsvl}6r*ECvz`7ay&z_eA9 FF91CT)^h*= delta 531 zcmZo~WomC_;tlX-W)WfF;NW0rm@#W3uL2`8klt*-xB|?We4FV7NMQ0YW|jIt@52Tn zt^d7FR?prd?d*K3@zgvS4nL9mdMEFSpjGjBv{v)MoeaAGsZ81 zVX@RPZ)0gG1qoJPwoVA+CcCmWIH3Oa3n<4n}O-c z^>$$TO1(7)Fml2`Hcu9BFb4|;Hn@W6nGHc;`dx!Pm^Ns%0Mprx5Y1~Et-$=3jecO- Hs>v4s(iG`5 diff --git a/results/tables/intersection_tables.xlsx b/results/tables/intersection_tables.xlsx index 50c133c737aa60d96d240aafb9a337aeada8c104..d3383122d423a3b1b659bd690b16dcc38b6bc2b7 100644 GIT binary patch delta 780 zcmezPoAJ|cM&1B#W)=|!4h{|m-tH9}c@-F$f%Ikr#uZ@3yMWRbUZk5ao)}Ci)HuOZ1erp zc20Y-c2J6?X8^bI)O(>%3O9R+t9)eK(sC?g%?VE1$ZIhY?cdKulsGQ*S91B?^~QNa zPmun%8%^gIty#RubX}{!{5*Hvj_@0by7iy`bZwJxaALT1Imr6aiJ8Y+{+2HhQNAP> zW6ZE*!HtA&tBR-;*1zA_O4j}_P6%*&esT51tEI8m&a%b(gj{(3_3mK-yU<hmv{~FKu)o3`x5cHsDA&Qe_6F z|5n+7X}fA`PGIDOfo-1LR1J~cT`kQd%sN?*RYp6&n~_PJ86Lf1Yd6Mfm;;?SMUa6( zodE&1G&)R{uQ8Jc8CG~ZUpiZxfq`!UBZCM+3B#7gGm}edl))Cys*$#-G-hC^$k8t@ zsmw_&)~m?PLAR`D20v>cD+9w~X$A&i6oXnOf2>i80avz~d zpe0`QlWk#L0PD2LUJX@?goIob^0cdON2zQ}-M!@L%fcWImx3o5=ih8!EW6L9Eca8} zIqk*SK`EA=0o=+{?_GUTxYYx2=DwA+s)_yv_Bc17#N?X#yl;rgIQ^BRh zyCWx>FFSKu>#Y8zqK%sCBH}h~s*s#^{+YDjb5(Qs0B?4V|8*b4q!<|(beI?zPy%(c z0;?7zRDIbxA&i^stF*!4+-A(d1ZGS$?Pmoul&z0I)V#9Mg)pS-R@i{!;AoW@nEqE~ z2d3?-tvP{l69%?gw;uJv!26YAm z*wSb}S)m4^J+elc@$}@<8fCB*vumVnD~uT!DsuFTODc0xi}fmUbI^_LnZeH*$jZR5 zSek)B7-1^Imd0k&$qP(HCv(*D#DE-nV~JgM7tsDA%nS_tC<;Zb!FH7A7iA~q=VxQH zrQAK@!+oHp6kzx&qiDV}xuDia9%KPK`>GqsHVh1V{xLF0ps3-Qe6UuVZEF=s5CGuj B6&nBm diff --git a/results/tables/number_of_samples.xlsx b/results/tables/number_of_samples.xlsx index 1c42258c225993778748811bb5faa9137f450ac5..e97bd307b4bf5324532217c88f64e119310ef40e 100644 GIT binary patch delta 1737 zcmZ8ic{JPU8vbQLQbiCXMVeMpw?r)+E!9@3EtXWHBEsBeEVZ;0E$$sdmPUz~;R+c+ zs|aeU6}7aq(JIr19%`wb7GtR;(jLAXPL{DXdoOj++(KW6* zxKE&3&dbnBDg2agzdtHvt&@7)uISuBhmEwwv*L8J>FOZ+O>t$(L(2!rh{8x`lT@F< z115~+Kho+^XY7IDUb4-kRQQUs881Q_^kDpt0-`&Ebl!=7(Sj5TwV6=IH19QT1Yj8r;0w*R^+ zF2#mw`Mtr9-5OKD@pFl3i3uf2&2GZLtgB1>LcS^NFesSs3$tTH9!L$zjK~EgHbU=u zhhJVXsQLhpVoHnE%X%QZfH=ccXIl*M37tjt8k^V@D!d|>O-ris1#5)Q4~N8~q&31? zql_9^c#cqB7?+@}x2St`ox%O-yOCAh9T~MLjQy(s04)E%49YgSb4t)~u>6zgDQ76i ziwB6uyZXX3Om_7NHH{e&SM$w~$y<9SH})JeWf`^AnhaCI_+_!Ch5At%_n7~Q&Z~cx zq|?Jzk(tbk9A4;IB|WasFnhfgA3QM{(+Bgt?;kVqM77F7$P0fK!`NE?<4E)^ry8S> z(3a5WGj$<1pPMRZ* zhm@`vOte-Zg<0Q^&hgv@8KJ%9?vl6Pc3R{^C>F8TD&MoBRn#77C3mgqmn>utP4_ir zr9~*C)PO+YweoR>^TdACbHavNkYI&0A8`!FDQeJ?weG9@pereU$5Xx3tlKg9ju17_ zX`y2#92S&(j+{=yK2QpIvakh93h!^J?(N*TpM5;y7o&>}VtgLTrE4270T2wqd=6m$ zT!wyg4snoyhpB_T+?=3AcA2Nu5G#N>nGFM_BA8M_vvLjgS9pL3YHm*tpG(CiNuWFo zos~^z0R#jy*%!Qi(ym7n=K|N@Jbx<=PL59HPkh(`mcA(USos4TH_h^)( znhRp~5{crwwGJ(d>Ntm`yxeHvQ>OV8z8T!R-B!Q(&CMCNK9oJ5UJ=IiN=I=cHQu0e z4%oo8ZwsuZsdPOG)5$byFWglOt7|>%%$~9$&b$qjo@Xmm;7Qixbc0*Xc8nB4DOEt5 zE{0=^?i%f{f$@G?3;BiqPPk09H8HD-%$F&s+#{ zxsZl8a@6djyy_;kSZkpzasq^|-R^aLaM=2xd31hBp6p9}*=lik0sG_lp)K%1ms@K- zW7UG#c<61viaJ6eO^GpR8`D=$2ja-{~CllFfy^oeA;tT>6rP8SsfFL<@83R*!zNywX8mEb3m|SyORwUhuRF=Apjs& z--$R7SO@ao)j^>zj?~R>$AjB;ZYXaf|EUgMzB;CKPRkLGvVm={63R|a@0x%>t0t_>9c delta 1737 zcmZ8ic~H~W7XD>}00k34N!TNcEV2ec7AYu@00CJOfnri1kzmy-F;JyMBWXn_vY1F{ z;{t?5DuD*Hg@m#rg4iMoBqECnh(w@5MUYwuZ{Ey%_n+_F@7y_azcXjPGrV_ruV!cv z1gZnT;cy_LsJKqk1O(YYu>+`585GLFGn+(V7sQP9Fr?i9kx4fHYyYW?P(Rz{V*!yU*W^+;HP5bJ#ZcO^^rPq1jfOa9J4Fi3l2h%EZUE4OkG~}wwYZ!00Cf0>n zp3K#rCUaSx`?W(Y9Cb8s`W|b<>(%n6<$`_A)FVWC2A3y3<9PI&p4%VZ&_5(LPcULm zzf%hhQiYpIif8me0I&xP0RPifu?ft2tF6H*SzB!#QMI%SfnX3S<0Q;8+he6&&Q0=m zmtaD@UhE^yQNgJB1rR!EPM&Q6qu@ zamv_T!=Sf}N2f)78EfhBzkNCw`AU9wY*PmFV!7Ji006xEe;LFLa`Tj;)xgRjG0?aI zQwBANU$^wpx7%*%<7?Zn6eoUk(E08pY>@@i$KMQeI{rgrl&p+C+I>>>rw(gM;!ov@ zC-dGhwYS{-1cQM^t_GhQ^qEo?7jNAcoU2L3^a_LQ(uXFf*4VJOytnh@A>;U=s=YQ? zUT=Z@DDFs;F)6z=GIjZSilSwaDrLNnAziypsyKI~cJ%;Jl9_13ifVQK>`8yMO=t8| zqsW&=%j&`^z*wt16CARMC$jm5S^OwmoB?>SL>(@!7iy} zgd1KLtThB_IXvrW$yzC0Fh;fPS>Kk(V{!-A9^@hH9!isT63LgF#l*oUCEwPK3p#0W zbuDpj*@Tw(WdGbrxo|D(SEIS(tWUUw1nKNO0d4eTndF#?>&O5{{wmweT*se8;KrL65Q-%*+?s-mEO?{n7RMpbn z(~K&a>VH;SOz!z8y1&%Szf+YGbB7>)a-gTQv=~jwt{+($?2|H%p~gfXIjP&k<&Q>= zVojM$Ds8a;DQzc%ubPqy)I)A|U1FuAm;%P9C5w{ zFgY57V6vc?0X72TAWri}=t18Nfl9PY4#XfZ01}Mg+b)oI7oCA(%V5~dmc9Z|>zpFW zVIG*mYfQmg3_wMP4#Q625T>@5kYKFo#n?2%-$yT&nd0+|%-}w3q?vXxP&}Ld()4(3 z8-}xEyAz|})5h4}@?$TxspC-4P7|8P3=5t6JQw=dwDn^WC$TJP^{z2~9?uRapz!M3 z9Q_@HhEglF@<1DBo(zk>v{IZIL8RLg*yzXV-3G`mWbkX8D46}t<_+unyn}HxU8VHe z?$$XvCn3k}yD#;Yo<+UZ40PbcOrT8tJwqm~s!QKnw)!S>5^|w0iYCKlO{}Z&b`5RF z?*&?dkaa5)X|NS7!p7htLZ@SZ&QR${8}_~7Vx@k-Q54}WG?j*0SwwDRp_ccr;tt95 zx$*wO$}k0^lBpLGidJv~9fjeMRZMrVk6;#UkJ}+%oF^!JqdnZl+I;?jq40v|BH3}< zYNkf=iL$4^q@fiP>#Y208dR5JBg{ajRW#oF!q~bZeh2B^WR~ldxZFsvS6DsSf_K84 zOC%&&!q#q>K|eHZUnn1tIJQme+J>iGY1CP`U3tPu)@;or#}YqnSeh#QH9?2=00IED z$W4m_fpsDOT^&TqoV;On!ybY*d_!Xc3njYd%GL2w*Gq}!C=d9?Dj{zAWMLA@RY{hh r{FFG03RfmK-KWqO?XDy*p!X?Jg5IjI{vY05FGTrx^E-ukdiZ|<%zgjg diff --git a/scripts/teste b/scripts/teste new file mode 100644 index 0000000..9bd7ec1 --- /dev/null +++ b/scripts/teste @@ -0,0 +1,125 @@ +import feyn +import pandas as pd +from sklearn.model_selection import train_test_split + + +def get_train_test_types(dataset, random_seed=1024, target="phenotype_reg"): + UNWANTED_COLUMNS_FOR_TRAINING = ["run", "phenotype"] + data = dataset[dataset.columns.difference(UNWANTED_COLUMNS_FOR_TRAINING)].dropna() + + # Let's record the categorical data types in our dataset (note features will be treated as numerical by default). + stypes = {} + for f in data.columns: + if data[f].dtype == "object": + stypes[f] = "c" + + # Split + train, test = train_test_split( + data, test_size=0.33, stratify=data[target], random_state=random_seed + ) + + return train, test, stypes + + +def get_models( + training_data, stypes, priors, target="phenotype_reg", epochs=20, random_seed=1024 +): + + ql = feyn.QLattice(random_seed=random_seed) + ql.update_priors(priors) + + models = ql.auto_run( + data=training_data, + output_name=target, + kind="classification", + stypes=stypes, + n_epochs=epochs, + ) + + return models + + +def save_model(model, train, test, filename): + model.plot(train, test, filename=f"results/sym_reg/{filename}_summary.html") + model.plot_signal(train, filename=f"results/sym_reg/{filename}_signal.svg") + model.save(f"results/sym_reg/{filename}_model.json") + + +# From https://github.com/abzu-ai/QLattice-clinical-omics/blob/main/notebooks/functions.py +def get_models_table(models, train, test, model_name): + model_list = [] + auc_list_train = [] + auc_list_test = [] + bic_list = [] + accuracy_train = [] + accuracy_test = [] + feat_list = [] + function_list = [] + loss_list = [] + i = 0 + for x in models: + model_list.append(str(i)) + auc_list_train.append(str(x.roc_auc_score(train).round(2))) + auc_list_test.append(str(x.roc_auc_score(test).round(2))) + accuracy_train.append(str(x.accuracy_score(train).round(2))) + accuracy_test.append(str(x.accuracy_score(test).round(2))) + bic_list.append(str(x.bic.round(2))) + feat_list.append(len(x.features)) + function_list.append( + x.sympify(symbolic_lr=False, symbolic_cat=True, include_weights=False) + ) + loss_list.append(x.loss_value) + i += 1 + df = pd.DataFrame( + list( + zip( + model_list, + auc_list_train, + auc_list_test, + accuracy_train, + accuracy_test, + bic_list, + feat_list, + function_list, + loss_list, + ) + ), + columns=[ + "Model", + "AUC Train", + "AUC Test", + "Accuracy Train", + "Accuracy Test", + "BIC", + "N. Features", + "Functional form", + "Loss", + ], + ) + + df.to_csv(f"results/sym_reg/{model_name}_table.csv", index=False) + + +def run_models(): + + three_gene_data = pd.read_table("results/sym_reg/selected_genes_for_reg.tsv") + full_data = pd.read_table("results/sym_reg/genes_for_reg.tsv") + + threeg_train, threeg_test, threeg_types = get_train_test_types(three_gene_data) + full_train, full_test, full_types = get_train_test_types(full_data) + + threeg_priors = feyn.tools.estimate_priors(threeg_train, "phenotype_reg", floor=0.1) + full_priors = feyn.tools.estimate_priors(full_train, "phenotype_reg", floor=0.1) + + threeg_models = get_models(threeg_train, threeg_types, threeg_priors) + full_models = get_models(full_train, full_types, full_priors) + + get_models_table(threeg_models, threeg_train, threeg_test, "three_gene") + get_models_table(full_models, full_train, full_test, "all_genes") + + save_model(threeg_models[0], threeg_train, threeg_test, "three_gene") + save_model(full_models[0], full_train, full_test, "all_genes") + + +if __name__ == "__main__": + run_models() From cb0336b503c47cd77ef87e82a7c70e8b557f6d54 Mon Sep 17 00:00:00 2001 From: Iara Souza Date: Tue, 9 May 2023 16:29:59 -0300 Subject: [PATCH 10/24] fix: replaced "gender" by sex on cumulative variance plot --- scripts/rank_variables.R | 44 +++++++++++++++++++++++++++++----------- 1 file changed, 32 insertions(+), 12 deletions(-) diff --git a/scripts/rank_variables.R b/scripts/rank_variables.R index bdea6cc..199701a 100644 --- a/scripts/rank_variables.R +++ b/scripts/rank_variables.R @@ -13,6 +13,9 @@ library(RColorBrewer) # Load predicted metadata load("results/important_variables/ann_complete.rda") +ann_complete <- ann_complete %>% + dplyr::rename(sex = gender) + # Organize predicted metadata ann_regression <- ann_complete ann_pca <- ann_complete @@ -23,7 +26,8 @@ lapply(seq_along(ann_pca), function(i) { }) ann_pca$phenotype <- factor(ann_pca$phenotype, levels = c("1", "2"), labels = c("CTRL", "MDD")) ann_pca$region <- sapply(strsplit(ann_pca$group, split = "_"), "[[", 1) -ann_pca$gender <- factor(ann_pca$gender, levels = c("1", "2"), labels = c("female", "male")) +ann_pca$sex <- factor(ann_pca$sex, levels = c("1", "2"), labels = c("female", "male")) + rm("ann_complete") @@ -77,16 +81,16 @@ p_kallisto <- pca(assay(vds), metadata = ann_regression) df <- data.frame(PC1 = p_kallisto$rotated[,1], PC2 = p_kallisto$rotated[,2], - gender = ann_pca$gender, + sex = ann_pca$sex, group = paste(ann_pca$region, ann_pca$phenotype, sep = "_"), stringsAsFactors = F) cols <- brewer.paired(12) cols[11] <- "#e0e05cf8" names(cols) <- unique(df$group)[order(sapply(strsplit(unique(df$group), split = "_"), "[[", 1))] -ggplot(df, aes(x = PC1, y = PC2, col = group, shape = gender)) + +ggplot(df, aes(x = PC1, y = PC2, col = group, shape = sex)) + geom_point(size = 2.5) + scale_color_manual(values = cols, name = "Group") + - scale_shape_manual(name = "Gender", values = c(15, 17), labels = c("female" = "Female", "male" = "Male")) + + scale_shape_manual(name = "Sex", values = c(15, 17), labels = c("female" = "Female", "male" = "Male")) + labs(x = paste0("PC1", " (", round(p_kallisto$variance[1], 2), "%)"), y = paste0("PC2", " (", round(p_kallisto$variance[2], 2), "%)")) + guides(colour = guide_legend(override.aes = list(size = 3)), @@ -95,19 +99,34 @@ ggplot(df, aes(x = PC1, y = PC2, col = group, shape = gender)) + theme(legend.key.size = unit(10, units = "mm"), legend.text = element_text(size = 12), legend.title = element_text(size = 12)) -ggsave("results/rank_plots/pca_vst.pdf", width = 10, height = 7) + +if(!dir.exists("results/rank_plots/")) { + dir.create("results/rank_plots/") +} + +ggsave(plot = last_plot(), "results/rank_plots/pca_vst.pdf", width = 10, height = 7) +ggsave(plot = last_plot(), "results/rank_plots/pca_vst.png", width = 10, height = 7) # Screeplot -pdf("results/rank_plots/screeplot_pca.pdf", width = 10, height = 7) -screeplot(p_kallisto, vline = findElbowPoint(p_kallisto$variance), components = 1:20) -dev.off() +sc_plot <- screeplot(p_kallisto, vline = findElbowPoint(p_kallisto$variance), components = 1:20) +ggsave(plot = sc_plot, file = "results/rank_plots/screeplot.pdf", width = 10, height = 7) +ggsave(plot = sc_plot, file = "results/rank_plots/screeplot.png", width = 10, height = 7) # Eigenplot - spearman correlation between variables and principal components -pdf("results/rank_plots/eigercorplot_kallisto.pdf", width = 10, height = 7) +pdf(file = "results/rank_plots/eigencorplot.pdf", width = 10, height = 7) +eigencorplot(p_kallisto, corFUN = "spearman", + corUSE = 'pairwise.complete.obs', + metavars = c("age", "alcool", "drugs", + "ph", "medication", "sex", + "region", "pmi", "rin", "phenotype")) +dev.off() + +png(file = "results/rank_plots/eigencorplot.png", width = 20, height = 14, units = "cm", res = 300) eigencorplot(p_kallisto, corFUN = "spearman", corUSE = 'pairwise.complete.obs', - metavars = c("age", "alcool", "drugs", "ph", "medication", - "gender", "region", "pmi", "rin", "phenotype")) + metavars = c("age", "alcool", "drugs", + "ph", "medication", "sex", + "region", "pmi", "rin", "phenotype")) dev.off() # # Poisson distance - See similarities between regions @@ -139,7 +158,7 @@ dev.off() # Rank variables by their correlation to each components ------------------ vars <- c("age", "alcool", "drugs", "ph", "medication", "smoking", - "gender", "region", "pmi", "rin", "phenotype") + "sex", "region", "pmi", "rin", "phenotype") m_cor <- matrix(0, nrow = length(vars), ncol = length(p_kallisto$rotated)) # Create correlation matrix @@ -190,4 +209,5 @@ ggplot(df_vars, aes(x = vars, y = value, fill = factor(component))) + axis.text.y = element_text(size = 14), axis.title.y = element_text(size = 14)) ggsave("results/rank_plots/rank_vars.pdf", width = 10, height = 7) +ggsave("results/rank_plots/rank_vars.png", width = 10, height = 7, dpi = 300) From d6eda291cbaa4f56e6593d674599490fc3db2e69 Mon Sep 17 00:00:00 2001 From: Iara Souza Date: Tue, 9 May 2023 16:40:31 -0300 Subject: [PATCH 11/24] chore: save upset plots as png --- scripts/intersection_analysis.R | 28 ++++++++++++++++++++++++++++ 1 file changed, 28 insertions(+) diff --git a/scripts/intersection_analysis.R b/scripts/intersection_analysis.R index b55520c..f49c9ef 100644 --- a/scripts/intersection_analysis.R +++ b/scripts/intersection_analysis.R @@ -22,19 +22,37 @@ l_type <- lapply(split(diff_df$gene, diff_df$type), unique) upset(fromList(l_type), text.scale = c(1.5, 2, 1, 1.5, 2, 3), point.size = 5, nintersects = NA) dev.off() +png("results/intersects/genes_by_type.png", width = 20, height = 14, units = "cm", res = 300) +l_type <- lapply(split(diff_df$gene, diff_df$type), unique) +upset(fromList(l_type), text.scale = c(1.5, 2, 1, 1.5, 2, 3), point.size = 5, nintersects = NA) +dev.off() + # By groups in each sex + +# Female pdf("results/intersects/genes_by_group_female.pdf", height = 7, width = 15) l_group_female <- lapply(split(diff_df$gene[diff_df$sex == "female"], diff_df$group[diff_df$sex == "female"]), unique) upset(fromList(l_group_female), nsets = length(l_group_female), text.scale = c(1.5, 1.5, 1, 1, 2, 2), point.size = 3, nintersects = NA) dev.off() +png("results/intersects/genes_by_group_female.png", width = 20, height = 14, units = "cm", res = 300) +upset(fromList(l_group_female), nsets = length(l_group_female), text.scale = c(1.5, 1.5, 1, 1, 2, 2), + point.size = 3, nintersects = NA) +dev.off() + +# Male pdf("results/intersects/genes_by_group_male.pdf", height = 7, width = 15) l_group_male <- lapply(split(diff_df$gene[diff_df$sex == "male"], diff_df$group[diff_df$sex == "male"]), unique) upset(fromList(l_group_male), nsets = length(l_group_male), text.scale = c(1.5, 1.5, 1, 1, 2, 2), point.size = 3, nintersects = NA) dev.off() +png("results/intersects/genes_by_group_male.png", width = 20, height = 14, units = "cm", res = 300) +upset(fromList(l_group_male), nsets = length(l_group_male), text.scale = c(1.5, 1.5, 1, 1, 2, 2), + point.size = 3, nintersects = NA) +dev.off() + # By regions pdf("results/intersects/genes_by_regions.pdf", height = 7, width = 15) l_regions <- lapply(split(diff_df$gene, diff_df$region), unique) @@ -42,12 +60,22 @@ upset(fromList(l_regions), nsets = length(l_regions), text.scale = c(1.5, 1.5, 1 point.size = 3, nintersects = NA) dev.off() +png("results/intersects/genes_by_region.png", width = 20, height = 14, units = "cm", res = 300) +upset(fromList(l_regions), nsets = length(l_regions), text.scale = c(1.5, 1.5, 1, 1, 2, 2), + point.size = 3, nintersects = NA) +dev.off() + # By sex pdf("results/intersects/genes_by_sex.pdf", height = 5, width = 10) l_sex <- lapply(split(diff_df$gene, diff_df$sex), unique) upset(fromList(l_sex), nsets = length(l_sex), text.scale = c(1.5, 2, 1, 1.5, 2, 3)) dev.off() +png("results/intersects/genes_by_sex.png", width = 20, height = 14, units = "cm", res = 300) +upset(fromList(l_sex), nsets = length(l_sex), text.scale = c(1.5, 1.5, 1, 1, 2, 2), + point.size = 3, nintersects = NA) +dev.off() + # Get the list of genes for each intersection get_intersect_genes <- function(ls) { tmp <- gplots::venn(ls, show.plot = F) From 272bcfe179109dba3bcddb6e341ccc4059b71ac1 Mon Sep 17 00:00:00 2001 From: Iara Souza Date: Tue, 9 May 2023 16:42:37 -0300 Subject: [PATCH 12/24] chore: added chisq.test and fisher.test to biotype categories --- scripts/summarise_biotypes.R | 124 ++++++++++++++++++++++++++--------- 1 file changed, 94 insertions(+), 30 deletions(-) diff --git a/scripts/summarise_biotypes.R b/scripts/summarise_biotypes.R index b000aef..b73b05d 100644 --- a/scripts/summarise_biotypes.R +++ b/scripts/summarise_biotypes.R @@ -24,7 +24,9 @@ dge_w_biotype <- gtf_data[, c("gene_id", "gene_biotype")] %>% dplyr::select(gene_id, gene_biotype) %>% right_join(dge_genes, by = c("gene_id" = "gene")) %>% distinct() %>% - dplyr::select(gene_id, gene_biotype, group) + dplyr::select(gene_id, gene_biotype, group) %>% + dplyr::rename(biotype = gene_biotype) %>% + mutate(type = "DGE") readr::write_csv(dge_w_biotype, "results/diff_exp/dge_w_biotype.csv") @@ -42,58 +44,47 @@ dte_w_biotype <- dplyr::select(transcript_id, transcript_biotype) %>% right_join(dte_genes, by = c("transcript_id" = "txID")) %>% distinct() %>% - dplyr::select(transcript_id, transcript_biotype, group) + dplyr::select(transcript_id, transcript_biotype, group) %>% + dplyr::rename(biotype = transcript_biotype) %>% + mutate(type = "DTE") readr::write_csv(dte_w_biotype, "results/diff_exp/dte_w_biotype.csv") # 2.3. Get DTU biotypes --------------------------------------------- dtu_w_biotype <- readr::read_csv("results/ISA/dtu_w_biotype.csv") +dtu_w_biotype <- dtu_w_biotype %>% + dplyr::rename(biotype = iso_biotype) %>% + mutate(type = "DTU") -# Plot --------------------------------------- -plot_biotype_bar <- function(data, id_col, n_col, color) { - - id_col <- enquo(id_col) - n_col <- enquo(n_col) - - data %>% - ggplot(aes(x = reorder(!!id_col, dplyr::desc(!!n_col)), y = !!n_col)) + - geom_col(fill = color) + - scale_y_continuous(labels = scales::percent_format(scale = 1), name = "", limits = c(0, 100)) + - coord_flip() + - theme_bw() + - theme(panel.grid.minor = element_blank(), - plot.margin = margin(-1, 0, -1, 0)) -} + +# Plot for both sexes ----------------------------------------------------- dge_plot <- dge_w_biotype %>% - group_by(gene_biotype) %>% + group_by(biotype) %>% summarise(biotype_n = n() / length(unique(dge_w_biotype$gene_id)) * 100) %>% ungroup() %>% - mutate(type = "DGE") %>% - dplyr::rename(biotype = gene_biotype) + mutate(type = "DGE") dte_plot <- dte_w_biotype %>% - group_by(transcript_biotype) %>% + group_by(biotype) %>% summarise(biotype_n = n() / length(unique(dte_w_biotype$transcript_id))* 100) %>% - ungroup() %>% - mutate(type = "DTE") %>% - dplyr::rename(biotype = transcript_biotype) + ungroup() %>% + mutate(type = "DTE") dtu_plot <- dtu_w_biotype %>% - group_by(iso_biotype) %>% + group_by(biotype) %>% summarise(biotype_n = n() / length(unique(dtu_w_biotype$isoform_id))* 100) %>% - ungroup() %>% - mutate(type = "DTU") %>% - dplyr::rename(biotype = iso_biotype) + ungroup() %>% + mutate(type = "DTU") df_plot <- Reduce(bind_rows, list(dge_plot, dte_plot, dtu_plot)) df_plot$biotype <- gsub("_", " ", df_plot$biotype) # Plot feature biotypes - color_scale <- c("DGE" = "#0ac80aff", "DTE" = "#4f4affff", "DTU" = "#ff822fff") +# Female and male together ggplot(df_plot, aes(x = reorder(biotype, dplyr::desc(biotype_n)), y = biotype_n, fill = type)) + geom_col(show.legend = F) + scale_y_continuous(labels = scales::percent_format(scale = 1), limits = c(0, 100)) + @@ -104,7 +95,80 @@ ggplot(df_plot, aes(x = reorder(biotype, dplyr::desc(biotype_n)), y = biotype_n, theme_bw() + theme(panel.grid.minor = element_blank()) -> biotype_plot - # Save ggsave(biotype_plot, file = "results/plots_paper/biotype_plot.pdf", width = 7, height = 4) + +# Plot for feature types for each sex ------------------------------------- + +dge_plot <- dge_w_biotype %>% + separate(group, into = c("region", "sex")) %>% + group_by(biotype, sex) %>% + summarise(biotype_n = n() / length(unique(dge_w_biotype$gene_id)) * 100) %>% + ungroup() %>% + mutate(type = "DGE") + +dte_plot <- dte_w_biotype %>% + separate(group, into = c("region", "sex")) %>% + group_by(biotype, sex) %>% + summarise(biotype_n = n() / length(unique(dte_w_biotype$transcript_id)) * 100) %>% + ungroup() %>% + mutate(type = "DTE") + +dtu_plot <- dtu_w_biotype %>% + separate(group, into = c("region", "sex")) %>% + group_by(biotype, sex) %>% + summarise(biotype_n = n() / length(unique(dtu_w_biotype$isoform_id)) * 100) %>% + ungroup() %>% + mutate(type = "DTU") + +df_plot <- Reduce(bind_rows, list(dge_plot, dte_plot, dtu_plot)) +df_plot$biotype <- gsub("_", " ", df_plot$biotype) + +# Plot feature biotypes +color_scale <- c("DGE" = "#0ac80aff", "DTE" = "#4f4affff", "DTU" = "#ff822fff") + +# Female and male together +ggplot(df_plot, aes(x = reorder(biotype, dplyr::desc(biotype_n)), y = biotype_n, fill = type)) + + geom_col(show.legend = F) + + scale_y_continuous(labels = scales::percent_format(scale = 1), limits = c(0, 100)) + + facet_grid(rows = vars(type), cols = vars(sex), scales = "free_y", + labeller = labeller(sex = as_labeller(c("female" = "Female", "male" = "Male")))) + + scale_fill_manual(values = color_scale) + + labs(x = "Feature biotypes", y = "% of feature biotype by the total features") + + coord_flip() + + theme_bw() + + theme(panel.grid = element_blank()) -> biotype_plot_by_sex + +# Save +ggsave(biotype_plot_by_sex, filename = "results/plots_paper/biotype_by_sexplot.pdf", width = 7, height = 4) + +# Test feature prevalence differences between female and male ------------- + +biotypes_by_sex <- Reduce(bind_rows, list( + dge_w_biotype %>% dplyr::select(-gene_id), + dte_w_biotype %>% dplyr::select(-transcript_id), + dtu_w_biotype %>% dplyr::select(-isoform_id))) + +biotypes_by_sex %>% + separate(group, into = c("region", "sex"), sep = "_") %>% + arrange(type, biotype) %>% + group_by(type) %>% + group_map(~ { + cat(.y$type, sep = "\n") + cont_table <- table(.x$biotype, .x$sex) + return(fisher.test(cont_table)) + }) -> biot_tests_fisher + +biotypes_by_sex %>% + separate(group, into = c("region", "sex"), sep = "_") %>% + arrange(type, biotype) %>% + group_by(type) %>% + group_map(~ { + cat(.y$type, sep = "\n") + cont_table <- table(.x$biotype, .x$sex) + return(chisq.test(cont_table)) + }) -> biot_tests_chisq + +names(biot_tests_fisher) <- c("DGE", "DTE", "DTU") +names(biot_tests_chisq) <- c("DGE", "DTE", "DTU") From 727ac581ac06b7ae1e9ba35a8de155a54934e834 Mon Sep 17 00:00:00 2001 From: Iara Souza Date: Fri, 12 May 2023 19:54:49 -0300 Subject: [PATCH 13/24] feat: add networks by groups --- scripts/network_groups.R | 116 +++++++++++++++++++++++++++++++++++++++ 1 file changed, 116 insertions(+) create mode 100644 scripts/network_groups.R diff --git a/scripts/network_groups.R b/scripts/network_groups.R new file mode 100644 index 0000000..e72f4e3 --- /dev/null +++ b/scripts/network_groups.R @@ -0,0 +1,116 @@ + +# Create individual networks ---------------------------------------------- + +genes <- c("HNRNPA3", "DDX39B") +i <- "aINS_female" + +diff_df_temp <- diff_df %>% + select(hgnc_symbol, type) %>% + filter(hgnc_symbol %in% genes) %>% + distinct() + +int_temp <- int %>% + filter(preferredName_A %in% diff_df_temp$hgnc_symbol, preferredName_B %in% diff_df_temp$hgnc_symbol) + +g <- graph_from_edgelist(as.matrix(int_temp[,c(1,2)])) + +lay <- create_layout(g, layout = "nicely") +V(g)$x <- lay[,"x"] +V(g)$y <- lay[,"y"] +V(g)$a <- ifelse(V(g)$name %in% unique(diff_df$hgnc_symbol[diff_df$type == "DGE"]), 1, 0) +V(g)$b <- ifelse(V(g)$name %in% unique(diff_df$hgnc_symbol[diff_df$type == "DTE"]), 1, 0) +V(g)$c <- ifelse(V(g)$name %in% unique(diff_df$hgnc_symbol[diff_df$type == "DTU"]), 1, 0) + +ggraph(g, x = x, y = y) + + geom_edge_link0(edge_color = "gray", alpha = 0.7, width = 0.2) + + geom_scatterpie( + data = as_data_frame(g, "vertices"), + cols = c("a", "b", "c"), + color = NA, + pie_scale = 4, + show.legend = F) + + geom_node_text(aes(label = name), size = 3, nudge_x = 0.03, nudge_y = 0.03) + + scale_fill_manual(values = c("#0ac80aff", "#4f4affff", "#ff822fff")) + + coord_fixed() + + theme_graph() + + + +# ------------------------------------------------------------------------- + +load("results/networks/graphs_by_group_wo_nbor.rda") + +make_graph_by_group <- function(genes, group_name, diff_df, int) { + + if(!is.null(genes)) { + + diff_df_temp <- diff_df %>% + select(hgnc_symbol, type, group) %>% + filter(hgnc_symbol %in% genes, group %in% group_name) %>% + distinct() + + int_temp <- int %>% + filter(preferredName_A %in% diff_df_temp$hgnc_symbol, preferredName_B %in% diff_df_temp$hgnc_symbol) + + g <- graph_from_edgelist(as.matrix(int_temp[,c(1,2)])) + + lay <- create_layout(g, layout = "nicely") + V(g)$x <- lay[,"x"] + V(g)$y <- lay[,"y"] + V(g)$a <- ifelse(V(g)$name %in% unique(diff_df$hgnc_symbol[diff_df$type == "DGE"]), 1, 0) + V(g)$b <- ifelse(V(g)$name %in% unique(diff_df$hgnc_symbol[diff_df$type == "DTE"]), 1, 0) + V(g)$c <- ifelse(V(g)$name %in% unique(diff_df$hgnc_symbol[diff_df$type == "DTU"]), 1, 0) + + # buffer <- c(-2, 2) + # xlims <- ceiling(range(V(g)$x)) + buffer + # ylims <- ceiling(range(V(g)$y)) + buffer + + xlims <- ylims <- c(-50, 50) + + ggraph(g, x = x, y = y) + + geom_edge_link0(edge_color = "gray", alpha = 0.7, width = 0.2) + + geom_scatterpie( + data = as_data_frame(g, "vertices"), + cols = c("a", "b", "c"), + color = NA, + pie_scale = 0.5, + show.legend = F) + + geom_node_text(aes(label = name), size = 2, nudge_x = 0.03, nudge_y = 0.03) + + scale_fill_manual(values = c("#0ac80aff", "#4f4affff", "#ff822fff")) + + coord_fixed() + + scale_x_continuous(limits = xlims) + + scale_y_continuous(limits = ylims) + + theme_graph() + + theme( + panel.border = element_rect( + colour = "#161616", + fill = NA, + linewidth = 1 + ) + ) -> plot_g + + return(plot_g) + + } else { + + return(NULL) + + } + +} + +imap(graphs_by_group, ~ { + + make_graph_by_group(.x$genes_from_graph, .y, diff_df, int) + +}) %>% + discard(is.null) -> ls_graphs + +design <- "ABCDEFGH" + +wrap_plots( + ls_graphs, + design = design, + nrow = 2, + ncol = 4 +) From 6022dc7aba291b6b68973bf037fc7db5028c20f0 Mon Sep 17 00:00:00 2001 From: Iara Souza Date: Mon, 15 May 2023 09:38:48 -0300 Subject: [PATCH 14/24] fix: added packages to the renv project --- renv.lock | 472 +++++++++++++++++++++++++++++------ scripts/gwas_intersections.R | 6 +- scripts/plots.rmd | 2 +- scripts/teste | 125 ---------- 4 files changed, 397 insertions(+), 208 deletions(-) delete mode 100644 scripts/teste diff --git a/renv.lock b/renv.lock index 5e7a305..ff44fe9 100644 --- a/renv.lock +++ b/renv.lock @@ -232,6 +232,30 @@ "crayon" ] }, + "ComplexHeatmap": { + "Package": "ComplexHeatmap", + "Version": "2.10.0", + "Source": "Bioconductor", + "git_url": "https://git.bioconductor.org/packages/ComplexHeatmap", + "git_branch": "RELEASE_3_14", + "git_last_commit": "170df82", + "git_last_commit_date": "2021-10-26", + "Hash": "964941c376127a2eccfb0d89d43442d2", + "Requirements": [ + "GetoptLong", + "GlobalOptions", + "IRanges", + "RColorBrewer", + "circlize", + "clue", + "colorspace", + "digest", + "doParallel", + "foreach", + "matrixStats", + "png" + ] + }, "DBI": { "Package": "DBI", "Version": "1.1.2", @@ -518,6 +542,26 @@ "XVector" ] }, + "GetoptLong": { + "Package": "GetoptLong", + "Version": "1.0.5", + "Source": "Repository", + "Repository": "CRAN", + "Hash": "61fac01c73abf03ac72e88dc3952c1e3", + "Requirements": [ + "GlobalOptions", + "crayon", + "rjson" + ] + }, + "GlobalOptions": { + "Package": "GlobalOptions", + "Version": "0.1.2", + "Source": "Repository", + "Repository": "CRAN", + "Hash": "c3f7b221e60c28f5f3533d74c6fef024", + "Requirements": [] + }, "HDInterval": { "Package": "HDInterval", "Version": "0.2.2", @@ -737,10 +781,10 @@ }, "Rcpp": { "Package": "Rcpp", - "Version": "1.0.7", + "Version": "1.0.10", "Source": "Repository", "Repository": "CRAN", - "Hash": "dab19adae4440ae55aa8a9d238b246bb", + "Hash": "e749cae40fa9ef469b6050959517453c", "Requirements": [] }, "RcppArmadillo": { @@ -766,10 +810,10 @@ }, "RcppParallel": { "Package": "RcppParallel", - "Version": "5.1.5", + "Version": "5.1.7", "Source": "Repository", "Repository": "CRAN", - "Hash": "f3e94e34ff656a7c8336ce01207bc2b8", + "Hash": "a45594a00f5dbb073d5ec9f48592a08a", "Requirements": [] }, "RedeR": { @@ -1196,19 +1240,27 @@ "Hash": "0baa960e3b49c6176a4f42addcbacc59", "Requirements": [] }, + "brio": { + "Package": "brio", + "Version": "1.1.3", + "Source": "Repository", + "Repository": "CRAN", + "Hash": "976cf154dfb043c012d87cddd8bca363", + "Requirements": [] + }, "broom": { "Package": "broom", - "Version": "0.7.11", + "Version": "1.0.4", "Source": "Repository", "Repository": "CRAN", - "Hash": "e4487657db580ae1fe0f85237a88ff1f", + "Hash": "f62b2504021369a2449c54bbda362d30", "Requirements": [ "backports", "dplyr", "ellipsis", "generics", - "ggplot2", "glue", + "lifecycle", "purrr", "rlang", "stringr", @@ -1330,6 +1382,18 @@ "backports" ] }, + "circlize": { + "Package": "circlize", + "Version": "0.4.15", + "Source": "Repository", + "Repository": "CRAN", + "Hash": "2bb47a2fe6ab009b1dcc5566d8c3a988", + "Requirements": [ + "GlobalOptions", + "colorspace", + "shape" + ] + }, "class": { "Package": "class", "Version": "7.3-19", @@ -1356,6 +1420,37 @@ "Hash": "ebaa97ac99cc2daf04e77eecc7b781d7", "Requirements": [] }, + "clock": { + "Package": "clock", + "Version": "0.6.1", + "Source": "Repository", + "Repository": "CRAN", + "Hash": "db6b0e88fa092982ecf56322b47be0fe", + "Requirements": [ + "cpp11", + "rlang", + "tzdb", + "vctrs" + ] + }, + "clue": { + "Package": "clue", + "Version": "0.3-64", + "Source": "Repository", + "Repository": "CRAN", + "Hash": "f013e45eb656a4bb17b39cb24827a51f", + "Requirements": [ + "cluster" + ] + }, + "cluster": { + "Package": "cluster", + "Version": "2.1.4", + "Source": "Repository", + "Repository": "CRAN", + "Hash": "5edbbabab6ce0bf7900a74fd4358628e", + "Requirements": [] + }, "clusterProfiler": { "Package": "clusterProfiler", "Version": "4.2.1", @@ -1415,6 +1510,14 @@ "Hash": "0f22be39ec1d141fd03683c06f3a6e67", "Requirements": [] }, + "concatenate": { + "Package": "concatenate", + "Version": "1.0.0", + "Source": "Repository", + "Repository": "CRAN", + "Hash": "94b165d30bf16386c2f096409d502463", + "Requirements": [] + }, "conquer": { "Package": "conquer", "Version": "1.2.1", @@ -1531,6 +1634,16 @@ "Hash": "fe1a3788cf243db3eca07ae661860793", "Requirements": [] }, + "diffobj": { + "Package": "diffobj", + "Version": "0.3.5", + "Source": "Repository", + "Repository": "CRAN", + "Hash": "bcaa8b95f8d7d01a5dedfd959ce88ab8", + "Requirements": [ + "crayon" + ] + }, "digest": { "Package": "digest", "Version": "0.6.29", @@ -1591,13 +1704,13 @@ }, "dplyr": { "Package": "dplyr", - "Version": "1.0.7", + "Version": "1.1.2", "Source": "Repository", "Repository": "CRAN", - "Hash": "36f1ae62f026c8ba9f9b5c9a08c03297", + "Hash": "dea6970ff715ca541c387de363ff405e", "Requirements": [ "R6", - "ellipsis", + "cli", "generics", "glue", "lifecycle", @@ -1651,6 +1764,19 @@ "proxy" ] }, + "easylayout": { + "Package": "easylayout", + "Version": "0.1.0", + "Source": "GitHub", + "RemoteType": "github", + "RemoteHost": "api.github.com", + "RemoteRepo": "easylayout", + "RemoteUsername": "daniloimparato", + "RemoteRef": "dadamorais", + "RemoteSha": "fdb800aec4852dddcdaec11a4bae1dc1c5d770b9", + "Hash": "555092182283a7b6537406811f0053a6", + "Requirements": [] + }, "edgeR": { "Package": "edgeR", "Version": "3.36.0", @@ -1991,10 +2117,10 @@ }, "generics": { "Package": "generics", - "Version": "0.1.1", + "Version": "0.1.3", "Source": "Repository", "Repository": "CRAN", - "Hash": "3f6bcfb0ee5d671d9fd1893d2faa79cb", + "Hash": "15e9634c0fcd294799e9b2e929ed1b86", "Requirements": [] }, "ggdist": { @@ -2073,20 +2199,22 @@ }, "ggplot2": { "Package": "ggplot2", - "Version": "3.3.5", + "Version": "3.4.2", "Source": "Repository", "Repository": "CRAN", - "Hash": "d7566c471c7b17e095dd023b9ef155ad", + "Hash": "3a147ee02e85a8941aad9909f1b43b7b", "Requirements": [ "MASS", - "digest", + "cli", "glue", "gtable", "isoband", + "lifecycle", "mgcv", "rlang", "scales", "tibble", + "vctrs", "withr" ] }, @@ -2189,10 +2317,10 @@ }, "glue": { "Package": "glue", - "Version": "1.6.0", + "Version": "1.6.2", "Source": "Repository", "Repository": "CRAN", - "Hash": "b8bb7aaf248e45bac08ebed86f3a0aa4", + "Hash": "4f2596dfb05dac67b9dc558e5c6fba2e", "Requirements": [] }, "googledrive": { @@ -2307,6 +2435,47 @@ "Hash": "2ace6c4a06297d0b364e0444384a2b82", "Requirements": [] }, + "gwasrapidd": { + "Package": "gwasrapidd", + "Version": "0.99.12", + "Source": "Repository", + "Repository": "CRAN", + "Hash": "56be6fbe33e1892fea54591d36881510", + "Requirements": [ + "assertthat", + "concatenate", + "dplyr", + "glue", + "httr", + "jsonlite", + "lubridate", + "magrittr", + "pingr", + "plyr", + "progress", + "purrr", + "rlang", + "stringr", + "testthat", + "tibble", + "tidyr", + "urltools" + ] + }, + "hardhat": { + "Package": "hardhat", + "Version": "1.3.0", + "Source": "Repository", + "Repository": "CRAN", + "Hash": "b56b42c50bb7c76a683e8e61f415d828", + "Requirements": [ + "cli", + "glue", + "rlang", + "tibble", + "vctrs" + ] + }, "haven": { "Package": "haven", "Version": "2.4.3", @@ -2495,6 +2664,27 @@ "Hash": "64778782a89480e9a644f69aad9a2877", "Requirements": [] }, + "janitor": { + "Package": "janitor", + "Version": "2.2.0", + "Source": "Repository", + "Repository": "CRAN", + "Hash": "5baae149f1082f466df9d1442ba7aa65", + "Requirements": [ + "dplyr", + "hms", + "lifecycle", + "lubridate", + "magrittr", + "purrr", + "rlang", + "snakecase", + "stringi", + "stringr", + "tidyr", + "tidyselect" + ] + }, "jquerylib": { "Package": "jquerylib", "Version": "0.1.4", @@ -2599,11 +2789,12 @@ }, "lifecycle": { "Package": "lifecycle", - "Version": "1.0.1", + "Version": "1.0.3", "Source": "Repository", "Repository": "CRAN", - "Hash": "a6b6d352e3ed897373ab19d8395c98d0", + "Hash": "001cecbeac1cff9301bdc3775ee46a86", "Requirements": [ + "cli", "glue", "rlang" ] @@ -2870,6 +3061,18 @@ "askpass" ] }, + "openxlsx": { + "Package": "openxlsx", + "Version": "4.2.5.2", + "Source": "Repository", + "Repository": "CRAN", + "Hash": "c03b4c18d42da881fb8e15a085c2b9d6", + "Requirements": [ + "Rcpp", + "stringi", + "zip" + ] + }, "org.Hs.eg.db": { "Package": "org.Hs.eg.db", "Version": "3.14.0", @@ -2963,21 +3166,30 @@ }, "pillar": { "Package": "pillar", - "Version": "1.6.4", + "Version": "1.9.0", "Source": "Repository", "Repository": "CRAN", - "Hash": "60200b6aa32314ac457d3efbb5ccbd98", + "Hash": "15da5a8412f317beeee6175fbc76f4bb", "Requirements": [ "cli", - "crayon", - "ellipsis", "fansi", + "glue", "lifecycle", "rlang", "utf8", "vctrs" ] }, + "pingr": { + "Package": "pingr", + "Version": "2.0.1", + "Source": "Repository", + "Repository": "CRAN", + "Hash": "e293e79be42ffd336d938937fd3017fb", + "Requirements": [ + "processx" + ] + }, "pkgbuild": { "Package": "pkgbuild", "Version": "1.3.1", @@ -3003,6 +3215,23 @@ "Hash": "01f28d4278f15c76cddbea05899c5d6f", "Requirements": [] }, + "pkgload": { + "Package": "pkgload", + "Version": "1.3.2", + "Source": "Repository", + "Repository": "CRAN", + "Hash": "6b0c222c5071efe0f3baf3dae9aa40e2", + "Requirements": [ + "cli", + "crayon", + "desc", + "fs", + "glue", + "rlang", + "rprojroot", + "withr" + ] + }, "plogr": { "Package": "plogr", "Version": "0.2.0", @@ -3087,6 +3316,14 @@ "tidyr" ] }, + "praise": { + "Package": "praise", + "Version": "1.0.0", + "Source": "Repository", + "Repository": "CRAN", + "Hash": "a555924add98c99d2f411e37e7d25e9f", + "Requirements": [] + }, "prettyunits": { "Package": "prettyunits", "Version": "1.1.1", @@ -3174,13 +3411,16 @@ }, "purrr": { "Package": "purrr", - "Version": "0.3.4", + "Version": "1.0.1", "Source": "Repository", "Repository": "CRAN", - "Hash": "97def703420c8ab10d8f0e6c72101e02", + "Hash": "d71c815267c640f17ddbf7f16144b4bb", "Requirements": [ + "cli", + "lifecycle", "magrittr", - "rlang" + "rlang", + "vctrs" ] }, "quadprog": { @@ -3218,14 +3458,6 @@ "reshape2" ] }, - "rJava": { - "Package": "rJava", - "Version": "1.0-6", - "Source": "Repository", - "Repository": "CRAN", - "Hash": "0415819f6baa75d86d52483f7292b623", - "Requirements": [] - }, "ranger": { "Package": "ranger", "Version": "0.13.1", @@ -3281,17 +3513,20 @@ }, "recipes": { "Package": "recipes", - "Version": "0.1.17", + "Version": "1.0.6", "Source": "Repository", "Repository": "CRAN", - "Hash": "443951ef5d9e72a96405cbb0157bb1d4", + "Hash": "eb53ffc9674dc9a52c3a7e22d96d3f56", "Requirements": [ "Matrix", + "cli", + "clock", "dplyr", "ellipsis", "generics", "glue", "gower", + "hardhat", "ipred", "lifecycle", "lubridate", @@ -3483,10 +3718,10 @@ }, "rstudioapi": { "Package": "rstudioapi", - "Version": "0.13", + "Version": "0.14", "Source": "Repository", "Repository": "CRAN", - "Hash": "06c85365a03fdaf699966cc1d3cf53ea", + "Hash": "690bd2acc42a9166ce34845884459320", "Requirements": [] }, "rsvd": { @@ -3557,10 +3792,10 @@ }, "scales": { "Package": "scales", - "Version": "1.1.1", + "Version": "1.2.1", "Source": "Repository", "Repository": "CRAN", - "Hash": "6f76f71042411426ec8df6c54f34e6dd", + "Hash": "906cb23d2f1c5680b8ce439b44c6fa63", "Requirements": [ "R6", "RColorBrewer", @@ -3568,6 +3803,7 @@ "labeling", "lifecycle", "munsell", + "rlang", "viridisLite" ] }, @@ -3607,6 +3843,14 @@ "scales" ] }, + "shape": { + "Package": "shape", + "Version": "1.4.6", + "Source": "Repository", + "Repository": "CRAN", + "Hash": "9067f962730f58b14d8ae54ca885509f", + "Requirements": [] + }, "shiny": { "Package": "shiny", "Version": "1.7.1", @@ -3646,6 +3890,17 @@ "Rcpp" ] }, + "snakecase": { + "Package": "snakecase", + "Version": "0.11.0", + "Source": "Repository", + "Repository": "CRAN", + "Hash": "4079070fc210c7901c0832a3aeab894f", + "Requirements": [ + "stringi", + "stringr" + ] + }, "snow": { "Package": "snow", "Version": "0.4-4", @@ -3719,14 +3974,18 @@ }, "stringr": { "Package": "stringr", - "Version": "1.4.0", + "Version": "1.5.0", "Source": "Repository", "Repository": "CRAN", - "Hash": "0759e6b6c0957edb1311028a49a35e76", + "Hash": "671a4d384ae9d32fc47a14e98bfa3dc8", "Requirements": [ + "cli", "glue", + "lifecycle", "magrittr", - "stringi" + "rlang", + "stringi", + "vctrs" ] }, "survival": { @@ -3763,14 +4022,40 @@ "Hash": "fd792ceac77f96b647fa8d6e1788969a", "Requirements": [] }, + "testthat": { + "Package": "testthat", + "Version": "3.1.7", + "Source": "Repository", + "Repository": "CRAN", + "Hash": "7eb5fd202a61d2fb78af5869b6c08998", + "Requirements": [ + "R6", + "brio", + "callr", + "cli", + "desc", + "digest", + "ellipsis", + "evaluate", + "jsonlite", + "lifecycle", + "magrittr", + "pkgload", + "praise", + "processx", + "ps", + "rlang", + "waldo", + "withr" + ] + }, "tibble": { "Package": "tibble", - "Version": "3.1.6", + "Version": "3.2.1", "Source": "Repository", "Repository": "CRAN", - "Hash": "8a8f02d1934dfd6431c671361510dd0b", + "Hash": "a84e2cc86d07289b3b6f5069df7a004c", "Requirements": [ - "ellipsis", "fansi", "lifecycle", "magrittr", @@ -3822,19 +4107,20 @@ }, "tidyr": { "Package": "tidyr", - "Version": "1.1.4", + "Version": "1.3.0", "Source": "Repository", "Repository": "CRAN", - "Hash": "c8fbdbd9fcac223d6c6fe8e406f368e1", + "Hash": "e47debdc7ce599b070c8e78e8ac0cfcf", "Requirements": [ + "cli", "cpp11", "dplyr", - "ellipsis", "glue", "lifecycle", "magrittr", "purrr", "rlang", + "stringr", "tibble", "tidyselect", "vctrs" @@ -3842,16 +4128,17 @@ }, "tidyselect": { "Package": "tidyselect", - "Version": "1.1.1", + "Version": "1.2.0", "Source": "Repository", "Repository": "CRAN", - "Hash": "7243004a708d06d4716717fa1ff5b2fe", + "Hash": "79540e5fcd9e0435af547d885f184fd5", "Requirements": [ - "ellipsis", + "cli", "glue", - "purrr", + "lifecycle", "rlang", - "vctrs" + "vctrs", + "withr" ] }, "tidytree": { @@ -3947,6 +4234,16 @@ "tidytree" ] }, + "triebeard": { + "Package": "triebeard", + "Version": "0.3.0", + "Source": "Repository", + "Repository": "CRAN", + "Hash": "847a9d113b78baca4a9a8639609ea228", + "Requirements": [ + "Rcpp" + ] + }, "tweenr": { "Package": "tweenr", "Version": "1.0.2", @@ -4000,14 +4297,25 @@ }, "tzdb": { "Package": "tzdb", - "Version": "0.2.0", + "Version": "0.3.0", "Source": "Repository", "Repository": "CRAN", - "Hash": "5e069fb033daf2317bd628d3100b75c5", + "Hash": "b2e1cbce7c903eaf23ec05c58e59fb5e", "Requirements": [ "cpp11" ] }, + "urltools": { + "Package": "urltools", + "Version": "1.7.3", + "Source": "Repository", + "Repository": "CRAN", + "Hash": "e86a704261a105f4703f653e05defa3e", + "Requirements": [ + "Rcpp", + "triebeard" + ] + }, "utf8": { "Package": "utf8", "Version": "1.2.2", @@ -4038,13 +4346,14 @@ }, "vctrs": { "Package": "vctrs", - "Version": "0.3.8", + "Version": "0.6.2", "Source": "Repository", "Repository": "CRAN", - "Hash": "ecf749a1b39ea72bd9b51b76292261f1", + "Hash": "a745bda7aff4734c17294bb41d4e4607", "Requirements": [ - "ellipsis", + "cli", "glue", + "lifecycle", "rlang" ] }, @@ -4091,6 +4400,22 @@ "withr" ] }, + "waldo": { + "Package": "waldo", + "Version": "0.4.0", + "Source": "Repository", + "Repository": "CRAN", + "Hash": "035fba89d0c86e2113120f93301b98ad", + "Requirements": [ + "cli", + "diffobj", + "fansi", + "glue", + "rematch2", + "rlang", + "tibble" + ] + }, "withr": { "Package": "withr", "Version": "2.5.0", @@ -4107,27 +4432,6 @@ "Hash": "e2e5fb1a74fbb68b27d6efc5372635dc", "Requirements": [] }, - "xlsx": { - "Package": "xlsx", - "Version": "0.6.5", - "Source": "Repository", - "Repository": "CRAN", - "Hash": "d24d579f59a3b6da1e1cf4660425443e", - "Requirements": [ - "rJava", - "xlsxjars" - ] - }, - "xlsxjars": { - "Package": "xlsxjars", - "Version": "0.6.1", - "Source": "Repository", - "Repository": "CRAN", - "Hash": "4c4b3bc29a916f33f1298dd951133351", - "Requirements": [ - "rJava" - ] - }, "xml2": { "Package": "xml2", "Version": "1.3.3", @@ -4160,6 +4464,14 @@ "Hash": "922e11dcf40bb5dfcf3fe5e714d0dc35", "Requirements": [] }, + "zip": { + "Package": "zip", + "Version": "2.3.0", + "Source": "Repository", + "Repository": "CRAN", + "Hash": "d98c94dacb7e0efcf83b0a133a705504", + "Requirements": [] + }, "zlibbioc": { "Package": "zlibbioc", "Version": "1.40.0", diff --git a/scripts/gwas_intersections.R b/scripts/gwas_intersections.R index 91c9733..51f0706 100644 --- a/scripts/gwas_intersections.R +++ b/scripts/gwas_intersections.R @@ -3,13 +3,15 @@ library(dplyr) library(purrr) +library(gwasrapidd) +library(biomaRt) # Get studies related to 'major depressive disorder' and 'unipolar depression'. efo_id <- c( unipolar_depression = "EFO_0003761", major_depressive_disorder = "MONDO_0002009" ) -mdd_results <- get_studies(efo_id = efo_id, set_operation = "intersection") +mdd_results <- get_studies(efo_id = efo_id, set_operation = "intersection") mdd_filtered <- mdd_results@publications %>% filter(publication_date > "2018-01-01") @@ -39,7 +41,7 @@ map_dfr(studies, function(study_id) { assoc_2 <- associations@associations %>% dplyr::select(association_id, pvalue, pvalue_description, range, beta_number, beta_direction) - associations_data <- reduce(list(assoc_1, assoc_2), inner_join, by = "association_id") + associations_data <- purrr::reduce(list(assoc_1, assoc_2), inner_join, by = "association_id") associations_data diff --git a/scripts/plots.rmd b/scripts/plots.rmd index f469e59..4aceaaf 100644 --- a/scripts/plots.rmd +++ b/scripts/plots.rmd @@ -412,7 +412,7 @@ diff_df %>% ) ggsave("results/plots_paper/percentage_gt.pdf", height = 5, width = 10, device = cairo_pdf) -ggsave("results/plots_paper/percentage_gt.png", height = 5, width = 10) +ggsave("results/plots_paper/percentage_gt.png", height = 5, width = 10, dpi = 300) ``` # Supplementary Figure 6 diff --git a/scripts/teste b/scripts/teste deleted file mode 100644 index 9bd7ec1..0000000 --- a/scripts/teste +++ /dev/null @@ -1,125 +0,0 @@ -import feyn -import pandas as pd -from sklearn.model_selection import train_test_split - - -def get_train_test_types(dataset, random_seed=1024, target="phenotype_reg"): - UNWANTED_COLUMNS_FOR_TRAINING = ["run", "phenotype"] - data = dataset[dataset.columns.difference(UNWANTED_COLUMNS_FOR_TRAINING)].dropna() - - # Let's record the categorical data types in our dataset (note features will be treated as numerical by default). - stypes = {} - for f in data.columns: - if data[f].dtype == "object": - stypes[f] = "c" - - # Split - train, test = train_test_split( - data, test_size=0.33, stratify=data[target], random_state=random_seed - ) - - return train, test, stypes - - -def get_models( - training_data, stypes, priors, target="phenotype_reg", epochs=20, random_seed=1024 -): - - ql = feyn.QLattice(random_seed=random_seed) - ql.update_priors(priors) - - models = ql.auto_run( - data=training_data, - output_name=target, - kind="classification", - stypes=stypes, - n_epochs=epochs, - ) - - return models - - -def save_model(model, train, test, filename): - model.plot(train, test, filename=f"results/sym_reg/{filename}_summary.html") - model.plot_signal(train, filename=f"results/sym_reg/{filename}_signal.svg") - model.save(f"results/sym_reg/{filename}_model.json") - - -# From https://github.com/abzu-ai/QLattice-clinical-omics/blob/main/notebooks/functions.py -def get_models_table(models, train, test, model_name): - model_list = [] - auc_list_train = [] - auc_list_test = [] - bic_list = [] - accuracy_train = [] - accuracy_test = [] - feat_list = [] - function_list = [] - loss_list = [] - i = 0 - for x in models: - model_list.append(str(i)) - auc_list_train.append(str(x.roc_auc_score(train).round(2))) - auc_list_test.append(str(x.roc_auc_score(test).round(2))) - accuracy_train.append(str(x.accuracy_score(train).round(2))) - accuracy_test.append(str(x.accuracy_score(test).round(2))) - bic_list.append(str(x.bic.round(2))) - feat_list.append(len(x.features)) - function_list.append( - x.sympify(symbolic_lr=False, symbolic_cat=True, include_weights=False) - ) - loss_list.append(x.loss_value) - i += 1 - df = pd.DataFrame( - list( - zip( - model_list, - auc_list_train, - auc_list_test, - accuracy_train, - accuracy_test, - bic_list, - feat_list, - function_list, - loss_list, - ) - ), - columns=[ - "Model", - "AUC Train", - "AUC Test", - "Accuracy Train", - "Accuracy Test", - "BIC", - "N. Features", - "Functional form", - "Loss", - ], - ) - - df.to_csv(f"results/sym_reg/{model_name}_table.csv", index=False) - - -def run_models(): - - three_gene_data = pd.read_table("results/sym_reg/selected_genes_for_reg.tsv") - full_data = pd.read_table("results/sym_reg/genes_for_reg.tsv") - - threeg_train, threeg_test, threeg_types = get_train_test_types(three_gene_data) - full_train, full_test, full_types = get_train_test_types(full_data) - - threeg_priors = feyn.tools.estimate_priors(threeg_train, "phenotype_reg", floor=0.1) - full_priors = feyn.tools.estimate_priors(full_train, "phenotype_reg", floor=0.1) - - threeg_models = get_models(threeg_train, threeg_types, threeg_priors) - full_models = get_models(full_train, full_types, full_priors) - - get_models_table(threeg_models, threeg_train, threeg_test, "three_gene") - get_models_table(full_models, full_train, full_test, "all_genes") - - save_model(threeg_models[0], threeg_train, threeg_test, "three_gene") - save_model(full_models[0], full_train, full_test, "all_genes") - - -if __name__ == "__main__": - run_models() From 24a193ac33500989e9172f4189ebe5e9b4d5fbcc Mon Sep 17 00:00:00 2001 From: Iara Souza Date: Mon, 15 May 2023 17:25:43 -0300 Subject: [PATCH 15/24] fix: reorder exclusivity on the Fig. 2C --- scripts/plots.rmd | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/scripts/plots.rmd b/scripts/plots.rmd index 4aceaaf..1a6e530 100644 --- a/scripts/plots.rmd +++ b/scripts/plots.rmd @@ -299,11 +299,12 @@ tmp7 <- data.frame(sex = c("Female", "Male"), xmax = c(1.35,2.35)) df_plot2 <- inner_join(df_plot2, tmp7, by = "sex") +df_plot2$exclusive <- factor(df_plot2$exclusive, levels = c("4", "3", "2", "Exclusive")) # Define colors to each intersection cols_intersects <- c( - "2" = "grey40", - "3" = "grey80", + "2" = "grey80", + "3" = "grey40", "4" = "black", "Exclusive" = "#8a0cb1ff" ) From cc1588a593653399f555da196e89fcc6305cc985 Mon Sep 17 00:00:00 2001 From: Iara Souza Date: Mon, 15 May 2023 17:26:23 -0300 Subject: [PATCH 16/24] feat: added biotype graphs for each sex and region --- scripts/summarise_biotypes.R | 65 +++++++++++++++++++++++++++++++++++- 1 file changed, 64 insertions(+), 1 deletion(-) diff --git a/scripts/summarise_biotypes.R b/scripts/summarise_biotypes.R index b73b05d..71ffefa 100644 --- a/scripts/summarise_biotypes.R +++ b/scripts/summarise_biotypes.R @@ -138,7 +138,8 @@ ggplot(df_plot, aes(x = reorder(biotype, dplyr::desc(biotype_n)), y = biotype_n, labs(x = "Feature biotypes", y = "% of feature biotype by the total features") + coord_flip() + theme_bw() + - theme(panel.grid = element_blank()) -> biotype_plot_by_sex + theme(panel.grid = element_blank(), + strip.background = element_rect(fill = "white")) -> biotype_plot_by_sex # Save ggsave(biotype_plot_by_sex, filename = "results/plots_paper/biotype_by_sexplot.pdf", width = 7, height = 4) @@ -172,3 +173,65 @@ biotypes_by_sex %>% names(biot_tests_fisher) <- c("DGE", "DTE", "DTU") names(biot_tests_chisq) <- c("DGE", "DTE", "DTU") + + +# Check biotypes by region in females ------------------------------------- + +biotypes_by_sex %>% + separate(group, into = c("region", "sex"), sep = "_") %>% + arrange(type, biotype) %>% + filter(sex == "female") %>% + group_by(region, type) %>% + mutate(n1 = n()) %>% + ungroup() %>% + group_by(biotype, type,region) %>% + mutate(n2 = n(), + prop_by_region = (n2 / n1) * 100) %>% + arrange(desc(type), desc(region)) %>% + ungroup() %>% + dplyr::select(biotype, region, type, prop_by_region) %>% + distinct() -> biotypes_female + +ggplot(biotypes_female, aes(x = reorder(biotype, dplyr::desc(prop_by_region)), y = prop_by_region, fill = type)) + + geom_col(show.legend = F) + + scale_y_continuous(labels = scales::percent_format(scale = 1), limits = c(0, 100)) + + facet_grid(rows = vars(region), cols = vars(type), scales = "free_y") + + scale_fill_manual(values = color_scale) + + labs(x = "Feature biotypes", y = "% of feature biotype by the total features") + + coord_flip() + + theme_bw() + + theme(panel.grid = element_blank(), + strip.background = element_rect(fill = "white")) -> plot_biotypes_female + +ggsave(plot_biotypes_female, filename = "results/plots_paper/biotype_female.pdf", width = 10, height = 7) + + +# Check biotypes by region male ------------------------------------------- + +biotypes_by_sex %>% + separate(group, into = c("region", "sex"), sep = "_") %>% + arrange(type, biotype) %>% + filter(sex == "male") %>% + group_by(region, type) %>% + mutate(n1 = n()) %>% + ungroup() %>% + group_by(biotype, type,region) %>% + mutate(n2 = n(), + prop_by_region = (n2 / n1) * 100) %>% + arrange(desc(type), desc(region)) %>% + ungroup() %>% + dplyr::select(biotype, region, type, prop_by_region) %>% + distinct() -> biotypes_male + +ggplot(biotypes_male, aes(x = reorder(biotype, dplyr::desc(prop_by_region)), y = prop_by_region, fill = type)) + + geom_col(show.legend = F) + + scale_y_continuous(labels = scales::percent_format(scale = 1), limits = c(0, 100)) + + facet_grid(rows = vars(region), cols = vars(type), scales = "free_y") + + scale_fill_manual(values = color_scale) + + labs(x = "Feature biotypes", y = "% of feature biotype by the total features") + + coord_flip() + + theme_bw() + + theme(panel.grid = element_blank(), + strip.background = element_rect(fill = "white")) -> plot_biotypes_male + +ggsave(plot_biotypes_male, filename = "results/plots_paper/biotype_male.pdf", width = 10, height = 7) From 3ba38ef75f511719b6c78db78677d6e79296b802 Mon Sep 17 00:00:00 2001 From: Iara Souza Date: Tue, 16 May 2023 14:45:30 -0300 Subject: [PATCH 17/24] fix: create network by sex and region --- scripts/network.R | 2 + scripts/network_groups.R | 163 +++++++++++++++++++++++---------------- 2 files changed, 100 insertions(+), 65 deletions(-) diff --git a/scripts/network.R b/scripts/network.R index b73f350..ffde233 100644 --- a/scripts/network.R +++ b/scripts/network.R @@ -64,6 +64,8 @@ s_map %>% combinescores(evidences = c("escore", "ascore", "dscore"), confLevel = 0.4) %>% unique() -> int +save(int, file = "results/networks/int.rda") + # RedeR # Here we select proper coordinates to our network diff --git a/scripts/network_groups.R b/scripts/network_groups.R index e72f4e3..130d56a 100644 --- a/scripts/network_groups.R +++ b/scripts/network_groups.R @@ -1,52 +1,24 @@ -# Create individual networks ---------------------------------------------- - -genes <- c("HNRNPA3", "DDX39B") -i <- "aINS_female" - -diff_df_temp <- diff_df %>% - select(hgnc_symbol, type) %>% - filter(hgnc_symbol %in% genes) %>% - distinct() - -int_temp <- int %>% - filter(preferredName_A %in% diff_df_temp$hgnc_symbol, preferredName_B %in% diff_df_temp$hgnc_symbol) - -g <- graph_from_edgelist(as.matrix(int_temp[,c(1,2)])) +library(dplyr) +library(tidyr) +library(patchwork) +library(ggplot2) +library(ggraph) -lay <- create_layout(g, layout = "nicely") -V(g)$x <- lay[,"x"] -V(g)$y <- lay[,"y"] -V(g)$a <- ifelse(V(g)$name %in% unique(diff_df$hgnc_symbol[diff_df$type == "DGE"]), 1, 0) -V(g)$b <- ifelse(V(g)$name %in% unique(diff_df$hgnc_symbol[diff_df$type == "DTE"]), 1, 0) -V(g)$c <- ifelse(V(g)$name %in% unique(diff_df$hgnc_symbol[diff_df$type == "DTU"]), 1, 0) -ggraph(g, x = x, y = y) + - geom_edge_link0(edge_color = "gray", alpha = 0.7, width = 0.2) + - geom_scatterpie( - data = as_data_frame(g, "vertices"), - cols = c("a", "b", "c"), - color = NA, - pie_scale = 4, - show.legend = F) + - geom_node_text(aes(label = name), size = 3, nudge_x = 0.03, nudge_y = 0.03) + - scale_fill_manual(values = c("#0ac80aff", "#4f4affff", "#ff822fff")) + - coord_fixed() + - theme_graph() - - - -# ------------------------------------------------------------------------- +# Create individual networks ---------------------------------------------- load("results/networks/graphs_by_group_wo_nbor.rda") +load("results/diff_exp/diff_df.rda") +load("results/networks/int.rda") -make_graph_by_group <- function(genes, group_name, diff_df, int) { +make_graph_by_group <- function(genes, group_name, diff_df, int, nx = 0.3, ny = 0.3, ps = 0.5) { if(!is.null(genes)) { diff_df_temp <- diff_df %>% - select(hgnc_symbol, type, group) %>% - filter(hgnc_symbol %in% genes, group %in% group_name) %>% + dplyr::select(hgnc_symbol, type, group) %>% + dplyr::filter(hgnc_symbol %in% genes, group %in% group_name) %>% distinct() int_temp <- int %>% @@ -54,18 +26,23 @@ make_graph_by_group <- function(genes, group_name, diff_df, int) { g <- graph_from_edgelist(as.matrix(int_temp[,c(1,2)])) - lay <- create_layout(g, layout = "nicely") - V(g)$x <- lay[,"x"] - V(g)$y <- lay[,"y"] + # lay <- create_layout(g, layout = "nicely") + # V(g)$x <- lay[,"x"] + # V(g)$y <- lay[,"y"] V(g)$a <- ifelse(V(g)$name %in% unique(diff_df$hgnc_symbol[diff_df$type == "DGE"]), 1, 0) V(g)$b <- ifelse(V(g)$name %in% unique(diff_df$hgnc_symbol[diff_df$type == "DTE"]), 1, 0) V(g)$c <- ifelse(V(g)$name %in% unique(diff_df$hgnc_symbol[diff_df$type == "DTU"]), 1, 0) + layout <- easylayout::vivagraph(graphs_by_group[[group_name]]$graph, pin_nodes = FALSE) + layout <- easylayout::vivagraph(graphs_by_group[[group_name]]$graph, layout = layout, pin_nodes = TRUE, pinned_cols = 10, lcc_margin_left = 500) + V(g)$x <- layout[, 1] + V(g)$y <- layout[, 2] + # buffer <- c(-2, 2) # xlims <- ceiling(range(V(g)$x)) + buffer # ylims <- ceiling(range(V(g)$y)) + buffer - xlims <- ylims <- c(-50, 50) + #xlims <- ylims <- c(-50, 50) ggraph(g, x = x, y = y) + geom_edge_link0(edge_color = "gray", alpha = 0.7, width = 0.2) + @@ -73,44 +50,100 @@ make_graph_by_group <- function(genes, group_name, diff_df, int) { data = as_data_frame(g, "vertices"), cols = c("a", "b", "c"), color = NA, - pie_scale = 0.5, + pie_scale = ps, show.legend = F) + - geom_node_text(aes(label = name), size = 2, nudge_x = 0.03, nudge_y = 0.03) + + geom_node_text(aes(label = name), size = 1, nudge_x = nx, nudge_y = ny) + scale_fill_manual(values = c("#0ac80aff", "#4f4affff", "#ff822fff")) + coord_fixed() + - scale_x_continuous(limits = xlims) + - scale_y_continuous(limits = ylims) + - theme_graph() + - theme( - panel.border = element_rect( - colour = "#161616", - fill = NA, - linewidth = 1 - ) - ) -> plot_g + theme_void() + + theme(plot.margin = margin(3,1,1.5,3, "cm")) -> plot_g return(plot_g) } else { return(NULL) - + } } imap(graphs_by_group, ~ { - make_graph_by_group(.x$genes_from_graph, .y, diff_df, int) - +make_graph_by_group(.x$genes_from_graph, .y, diff_df, int) + }) %>% discard(is.null) -> ls_graphs -design <- "ABCDEFGH" -wrap_plots( - ls_graphs, - design = design, - nrow = 2, - ncol = 4 -) +design_female <- " +AB +CD +EE +EE +" + +wrap_plots(ls_graphs[c(1,2,4,5,7)], design = design_female) +ggsave("results/networks/ppi_female.pdf", height = 10, width = 10) + + +# ------------------------------------------------------------------------- + +make_graph_by_group(graphs_by_group$aINS_female$genes_from_graph, + group_name = "aINS_female", + diff_df = diff_df, + int = int, + nx = 0.1, ny = 0.1) +ggsave(filename = "results/networks/aINS_female.pdf", width = 5, height = 5) + + +make_graph_by_group(graphs_by_group$Cg25_female$genes_from_graph, + group_name = "Cg25_female", + diff_df = diff_df, + int = int, + nx = 0.1, ny = 0.1) +ggsave(filename = "results/networks/Cg25_female.pdf", width = 5, height = 5) + +make_graph_by_group(graphs_by_group$dlPFC_female$genes_from_graph, + group_name = "dlPFC_female", + diff_df = diff_df, + int = int, + nx = 0.1, ny = 0.1) +ggsave(filename = "results/networks/dlPFC_female.pdf", width = 5, height = 5) + +make_graph_by_group(graphs_by_group$Nac_female$genes_from_graph, + group_name = "Nac_female", + diff_df = diff_df, + int = int, + nx = 0.2, ny = 0.2) +ggsave(filename = "results/networks/Nac_female.pdf", width = 5, height = 5) + +make_graph_by_group(graphs_by_group$OFC_female$genes_from_graph, + group_name = "OFC_female", + diff_df = diff_df, + int = int, + nx = 0.2, ny = 0.2, ps = 0.3) +ggsave(filename = "results/networks/OFC_female.pdf", width = 14, height = 14) + +### +make_graph_by_group(graphs_by_group$Nac_male$genes_from_graph, + group_name = "Nac_male", + diff_df = diff_df, + int = int, + nx = 0.2, ny = 0.2) +ggsave(filename = "results/networks/Nac_male.pdf", width = 5, height = 5) + +make_graph_by_group(graphs_by_group$Cg25_male$genes_from_graph, + group_name = "Cg25_male", + diff_df = diff_df, + int = int, + nx = 0.2, ny = 0.2, ps = 0.3) +ggsave(filename = "results/networks/Cg25_male.pdf", width = 10, height = 10) + + +make_graph_by_group(graphs_by_group$Sub_male$genes_from_graph, + group_name = "Sub_male", + diff_df = diff_df, + int = int, + nx = 0.2, ny = 0.2) +ggsave(filename = "results/networks/Sub_male.pdf", width = 7, height = 7) From f153bc759ba32330b2a644ce4a791c2421ac7f09 Mon Sep 17 00:00:00 2001 From: Iara Souza Date: Wed, 17 May 2023 10:48:52 -0300 Subject: [PATCH 18/24] fix: corrected the proportions calculation for by sex plot --- scripts/summarise_biotypes.R | 50 +++++++++++++++++++++++++++++------- 1 file changed, 41 insertions(+), 9 deletions(-) diff --git a/scripts/summarise_biotypes.R b/scripts/summarise_biotypes.R index 71ffefa..a46ca96 100644 --- a/scripts/summarise_biotypes.R +++ b/scripts/summarise_biotypes.R @@ -1,5 +1,6 @@ library(dplyr) library(purrr) +library(tidyr) library(ggplot2) library(patchwork) library(stringr) @@ -104,23 +105,29 @@ ggsave(biotype_plot, file = "results/plots_paper/biotype_plot.pdf", width = 7, h dge_plot <- dge_w_biotype %>% separate(group, into = c("region", "sex")) %>% group_by(biotype, sex) %>% - summarise(biotype_n = n() / length(unique(dge_w_biotype$gene_id)) * 100) %>% + summarise(biotype_n = n()) %>% ungroup() %>% - mutate(type = "DGE") + group_by(sex) %>% + mutate(prop = biotype_n / sum(biotype_n) * 100, + type = "DGE") dte_plot <- dte_w_biotype %>% separate(group, into = c("region", "sex")) %>% group_by(biotype, sex) %>% - summarise(biotype_n = n() / length(unique(dte_w_biotype$transcript_id)) * 100) %>% + summarise(biotype_n = n()) %>% ungroup() %>% - mutate(type = "DTE") + group_by(sex) %>% + mutate(prop = biotype_n / sum(biotype_n) * 100, + type = "DTE") dtu_plot <- dtu_w_biotype %>% separate(group, into = c("region", "sex")) %>% group_by(biotype, sex) %>% - summarise(biotype_n = n() / length(unique(dtu_w_biotype$isoform_id)) * 100) %>% + summarise(biotype_n = n()) %>% ungroup() %>% - mutate(type = "DTU") + group_by(sex) %>% + mutate(prop = biotype_n / sum(biotype_n) * 100, + type = "DTU") df_plot <- Reduce(bind_rows, list(dge_plot, dte_plot, dtu_plot)) df_plot$biotype <- gsub("_", " ", df_plot$biotype) @@ -129,7 +136,7 @@ df_plot$biotype <- gsub("_", " ", df_plot$biotype) color_scale <- c("DGE" = "#0ac80aff", "DTE" = "#4f4affff", "DTU" = "#ff822fff") # Female and male together -ggplot(df_plot, aes(x = reorder(biotype, dplyr::desc(biotype_n)), y = biotype_n, fill = type)) + +ggplot(df_plot, aes(x = reorder(biotype, dplyr::desc(prop)), y = prop, fill = type)) + geom_col(show.legend = F) + scale_y_continuous(labels = scales::percent_format(scale = 1), limits = c(0, 100)) + facet_grid(rows = vars(type), cols = vars(sex), scales = "free_y", @@ -158,7 +165,7 @@ biotypes_by_sex %>% group_map(~ { cat(.y$type, sep = "\n") cont_table <- table(.x$biotype, .x$sex) - return(fisher.test(cont_table)) + return(list(fisher = fisher.test(cont_table), count_table = cont_table)) }) -> biot_tests_fisher biotypes_by_sex %>% @@ -174,6 +181,31 @@ biotypes_by_sex %>% names(biot_tests_fisher) <- c("DGE", "DTE", "DTU") names(biot_tests_chisq) <- c("DGE", "DTE", "DTU") +# Divide plot by protein coding and non-coding ---------------------------- +df_plot %>% + mutate( + coding = case_when( + biotype == "protein coding" ~ "coding", + .default = "non-coding" + )) %>% + group_by(coding, sex, type) %>% + mutate(prop_coding = sum(prop)) %>% + dplyr::select(-biotype_n, -biotype, -prop) %>% + unique() -> df_plot_coding + +ggplot(df_plot_coding, aes(x = reorder(coding, dplyr::desc(prop_coding)), y = prop_coding, fill = type)) + + geom_col(show.legend = F) + + scale_y_continuous(labels = scales::percent_format(scale = 1), limits = c(0, 100)) + + facet_grid(rows = vars(type), cols = vars(sex), scales = "free_y", + labeller = labeller(sex = as_labeller(c("female" = "Female", "male" = "Male")))) + + scale_fill_manual(values = color_scale) + + labs(x = "Feature biotypes", y = "% of feature biotype by the total features") + + coord_flip() + + theme_bw() + + theme(panel.grid = element_blank(), + strip.background = element_rect(fill = "white")) -> biotype_plot_coding + +ggsave(biotype_plot_coding, filename = "results/plots_paper/biotype_sex_coding.pdf", width = 7, height = 4) # Check biotypes by region in females ------------------------------------- @@ -184,7 +216,7 @@ biotypes_by_sex %>% group_by(region, type) %>% mutate(n1 = n()) %>% ungroup() %>% - group_by(biotype, type,region) %>% + group_by(biotype, type, region) %>% mutate(n2 = n(), prop_by_region = (n2 / n1) * 100) %>% arrange(desc(type), desc(region)) %>% From bd2c8945c5e5c665e1c31de9768cc249f617722f Mon Sep 17 00:00:00 2001 From: Iara Souza Date: Tue, 30 May 2023 11:20:07 -0300 Subject: [PATCH 19/24] fix: added final touch --- scripts/summarise_biotypes.R | 3 +++ 1 file changed, 3 insertions(+) diff --git a/scripts/summarise_biotypes.R b/scripts/summarise_biotypes.R index a46ca96..c3aecfd 100644 --- a/scripts/summarise_biotypes.R +++ b/scripts/summarise_biotypes.R @@ -267,3 +267,6 @@ ggplot(biotypes_male, aes(x = reorder(biotype, dplyr::desc(prop_by_region)), y = strip.background = element_rect(fill = "white")) -> plot_biotypes_male ggsave(plot_biotypes_male, filename = "results/plots_paper/biotype_male.pdf", width = 10, height = 7) + + +# ------------------------------------------------------------------------- From 6f90c81f010de6650580efd0c1ce54add3c24fa3 Mon Sep 17 00:00:00 2001 From: Iara Souza Date: Fri, 7 Jul 2023 17:32:00 -0300 Subject: [PATCH 20/24] Added Table 2 (gwas intersections) --- scripts/gwas_intersections.R | 10 ++++++++++ 1 file changed, 10 insertions(+) diff --git a/scripts/gwas_intersections.R b/scripts/gwas_intersections.R index 51f0706..66daf0a 100644 --- a/scripts/gwas_intersections.R +++ b/scripts/gwas_intersections.R @@ -5,6 +5,7 @@ library(dplyr) library(purrr) library(gwasrapidd) library(biomaRt) +library(tidyr) # Get studies related to 'major depressive disorder' and 'unipolar depression'. efo_id <- c( @@ -82,3 +83,12 @@ intersection <- inner_join(risk_alleles, diff_df, by = c("ensembl_gene_name" = " # Save save(intersection, file = "results/diff_exp/gwas_intersections.rda") write.csv(intersection, file = "results/tables/gwas_intersection.csv", row.names = F, quote = F) + +# Create Supplementary Table +intersection %>% + separate(group, into = c("region", "sex"), sep = "_") %>% + dplyr::select(sex, region, hgnc_symbol, type, variant_id, functional_class, pvalue) %>% + mutate(pvalue = as.character(scales::scientific(pvalue))) %>% + arrange(sex, region) %>% + write.csv("results/tables/table2_gwas.csv", row.names = F, quote = F) + From 4c38efedf6a40e42e7ad1a58e7c368082bd16878 Mon Sep 17 00:00:00 2001 From: Iara Souza Date: Tue, 24 Oct 2023 13:28:10 -0300 Subject: [PATCH 21/24] fix: modifications after stageR correction --- scripts/diff_tx_correct.R | 14 ++++++------- scripts/network.R | 15 ++++++++------ scripts/network_layout.R | 6 ++++++ scripts/plots.rmd | 40 +++++++++++++++++------------------- scripts/summarise_biotypes.R | 26 +++++++++++------------ 5 files changed, 54 insertions(+), 47 deletions(-) diff --git a/scripts/diff_tx_correct.R b/scripts/diff_tx_correct.R index dea68a1..aea757d 100644 --- a/scripts/diff_tx_correct.R +++ b/scripts/diff_tx_correct.R @@ -5,7 +5,7 @@ library(stageR) library(GenomicFeatures) # Load TX data from differential expression -load("results/diff_exp/tx_rin_ph_diff.rda") +load("results/diff_exp/edger_tx_rin_ph_diff.rda") df_res <- df_edger_ph_rin_group_tx colnames(df_res)[1] <- "tx" @@ -13,10 +13,10 @@ colnames(df_res)[1] <- "tx" df_res$tx <- gsub("\\.+\\d+", "", rownames(df_res)) # Load transcript-gene info ----------------------------------------------- -# gtf <- "data/genome/Homo_sapiens.GRCh38.97.gtf.gz" -# txdb.filename <- "data/genome/Homo_sapiens.GRCh38.97.gtf.sqlite" -gtf <- "Homo_sapiens.GRCh38.97.gtf.gz" -txdb.filename <- "Homo_sapiens.GRCh38.97.gtf.sqlite" +gtf <- "data/genome/Homo_sapiens.GRCh38.97.gtf.gz" +txdb.filename <- "data/genome/Homo_sapiens.GRCh38.97.gtf.sqlite" +#gtf <- "Homo_sapiens.GRCh38.97.gtf.gz" +#txdb.filename <- "Homo_sapiens.GRCh38.97.gtf.sqlite" # Load db txdb <- loadDb(txdb.filename) @@ -72,7 +72,7 @@ for (i in 1:length(regions)) { # Get the corrected values padj <- getAdjustedPValues(stageRObj, order = TRUE, onlySignificantGenes = T) - padj <- padj[!padj$transcript == 0,] + # padj <- padj[!padj$transcript == 0,] if (nrow(padj) == 0) { ls_temp[[j]] <- NULL @@ -93,7 +93,7 @@ if(!dir.exists("results/diff_exp/")) { } # Save results -save(df_res_padj, file = "results/diff_exp/diff_tx_corrected.rda") +save(df_res_padj_tx, file = "results/diff_exp/diff_tx_corrected.rda") diff --git a/scripts/network.R b/scripts/network.R index ffde233..886be1b 100644 --- a/scripts/network.R +++ b/scripts/network.R @@ -10,7 +10,7 @@ library(ggraph) library(magrittr) library(RedeR) -# ------------------ GET GENES AND INTERACTIONS ------------------------- +# ------------------ GET GENES AND INTERACTIONS --------------------------- # Load diff genes table load("results/diff_exp/diff_df.rda") gwas_intersections <- read_csv("results/tables/gwas_intersection.csv") @@ -82,6 +82,9 @@ addGraph(rdp, g) nodes <- read_tsv("results/networks/model_nodes.txt") edges <- read_delim("results/networks/model_edges.txt") +nodes <- read_tsv("~/model_nodes.txt") +edges <- read_delim("~/model_edges.txt") + # Import nodes coordinates determined by vivagraph layout <- read.csv("results/networks/layout.csv") @@ -115,7 +118,7 @@ ggraph(g, x = x, y = y) + pie_scale = 0.2, show.legend = F ) + - geom_node_text(aes(label = alias), size = 1.1, nudge_x = 2, nudge_y = 4) + + geom_node_text(aes(label = alias), size = 0.9, nudge_x = 2, nudge_y = 4) + #geom_node_label(aes(label = alias)) + scale_fill_manual(values = c("#0ac80aff", "#4f4affff", "#ff822fff")) + coord_fixed() + @@ -131,7 +134,7 @@ svg(filename = "results/plots_paper/network.svg", height = 10, width = 10) print(p) dev.off() -# Percentage of total genes in the network: 51,52%% +# Percentage of total genes in the network: 51,24% n_distinct(nodes$alias) / n_distinct(diff_df$hgnc_symbol) @@ -226,7 +229,7 @@ set_graph_params <- function(g, dict, f_ls) { l_groups <- map(split(diff_df$hgnc_symbol, diff_df$group), unique) -graphs_by_group <- imap(l_groups, function(x, i){ +graphs_by_group <- imap(l_groups, function(x, i) { # CHANGE HERE IF YOU WANT FIRST NEIGHBORS # (also remember to change the path) @@ -241,14 +244,14 @@ graphs_by_group <- imap(l_groups, function(x, i){ # To set all gene labels, set diff_df instead of diff_temp g <- set_graph_params(g, dc, f_ls) - if(include_first_neighbors){ + if(include_first_neighbors) { colors_list <- V(g)$pie degrees <- degree(g,v=V(g)) filter <- !(paste(colors_list) == "c(1, 0, 0, 0)" & degrees == 1) g <- induced_subgraph(g, filter) } - if(length(V(g)$pie.color) != 0){ + if(length(V(g)$pie.color) != 0) { pdf(paste0("results/networks/", i, ".pdf"), width = 10, height = 10) plot(g) dev.off() diff --git a/scripts/network_layout.R b/scripts/network_layout.R index 2f60416..7d90c3a 100644 --- a/scripts/network_layout.R +++ b/scripts/network_layout.R @@ -3,6 +3,12 @@ library(easylayout) +# Read igraph data +load("results/networks/int.rda") + +# Create graph +g <- graph_from_edgelist(as.matrix(int[,1:2]), directed = F) + # Organize main layout layout <- easylayout::vivagraph(g) diff --git a/scripts/plots.rmd b/scripts/plots.rmd index 1a6e530..c79293d 100644 --- a/scripts/plots.rmd +++ b/scripts/plots.rmd @@ -62,7 +62,7 @@ diff_df %>% ggplot(aes(x = col, y = n, fill = type)) + geom_bar(position = "stack", stat = "identity") + labs(x = "", y = "Number of transcriptionally altered genes", fill = "") + - scale_y_continuous(limits = c(0, 1200), breaks = seq(0, 1200, 200)) + + scale_y_continuous(limits = c(0, 1400), breaks = seq(0, 1400, 200)) + scale_fill_manual(values = color_scale) + theme_classic() + theme( @@ -152,7 +152,7 @@ df_plot %>% ggplot(aes(x = as.numeric(x_axis), y = n, fill = type)) + geom_bar(stat = "identity", position = "stack") + facet_grid(cols = vars(region)) + - scale_y_continuous(name = "Number of transcriptionally altered genes", limits = c(0, 460), breaks = seq(0, 460, 50), minor_breaks = F) + + scale_y_continuous(name = "Number of transcriptionally altered genes", limits = c(0, 500), breaks = seq(0, 500, 50), minor_breaks = F) + #facet_zoom(x = x_axis %in% c("Female", "Male", "Intersection")) + scale_fill_manual(name = "", values = color_scale) + scale_x_continuous("", @@ -181,7 +181,7 @@ diff_df %>% )) -> tmp8 # Create list of genes in female, in male, and in both sexes -l_genes <- split(tmp8$gene, tmp8$sex) +l_genes <- split(tmp8$hgnc_symbol, tmp8$sex) # Plot Venn diagram cairo_pdf(file = "results/plots_paper/fig2B.pdf", width = 4, height = 4) @@ -357,11 +357,8 @@ ggsave("results/plots_paper/fig2C_2.png", height = 4, width = 5, dpi = 300) ## Figure 3 -Enrichment plot was built as described in `enrichment.R` in `script` directory. +Figure 3 was produced on the biotype analysis, in the `summarise_biotypes.R` script. -## Figure 4 and 5 - -Figures 4 and 5 were built as described in `plot_dtu.R` in `script` directory. # Supplementary Figures @@ -397,14 +394,15 @@ diff_df %>% ggplot(aes(x = sex, y = p_gt, fill = gt)) + geom_bar(stat = "identity") + facet_grid(.~ region) + - scale_y_continuous(breaks = seq(0,1,0.2), - labels = scales::percent(seq(0,1,0.2))) + + scale_y_continuous(breaks = seq(0,1,0.25), + labels = scales::percent(seq(0,1,0.25))) + scale_x_discrete(labels = c("female" = expression("\u2640"), "male" = expression("\u2642"))) + scale_fill_manual(values = c("G" = "#5E835Fff", "T" = "#85587C"), labels = c("G" = "Genes", "T" = "Transcripts")) + labs(x = "", y = "Pergentage of transcriptionally altered genes", fill = "") + theme_bw() + + geom_hline(yintercept = 0.5, lty = 2, lwd = 0.2) + theme( strip.background = element_rect(fill = "white"), axis.text.x = element_text(size = 15, colour = "black"), @@ -489,7 +487,7 @@ load("results/important_variables/ann.rda") ann %>% rownames_to_column("run") %>% dplyr::select(run, phenotype, gender, region) %>% - count(phenotype, gender, region, name = "number_of_samples") %>% + dplyr::count(phenotype, gender, region, name = "number_of_samples") %>% arrange(gender, region) %>% openxlsx::write.xlsx(file = "results/tables/number_of_samples.xlsx", rowNames = F) ``` @@ -504,21 +502,21 @@ diff_df %>% ## Supplementary Table 3 ```{r} -genes_by_group_female %>% - openxlsx::write.xlsx(file = "results/tables/intersection_tables.xlsx", row.names = F, sheetName = "Female_Intersections") +wb <- createWorkbook() + +addWorksheet(wb, sheetName = "Female_Intersections") +writeData(wb, sheet = "Female_Intersections", genes_by_group_female) -genes_by_group_male %>% - openxlsx::write.xlsx(file = "results/tables/intersection_tables.xlsx", row.names = F, sheetName = "Male_Intersections", - append = T) +addWorksheet(wb, sheetName = "Male_Intersections") +writeData(wb, sheet = "Male_Intersections", genes_by_group_male) -genes_by_sex %>% - openxlsx::write.xlsx(file = "results/tables/intersection_tables.xlsx", row.names = F, sheetName = "Sex_Intersections", - append = T) +addWorksheet(wb, sheetName = "Sex_Intersections") +writeData(wb, sheet = "Sex_Intersections", genes_by_sex) -genes_by_regions %>% - openxlsx::write.xlsx(file = "results/tables/intersection_tables.xlsx", row.names = F, sheetName = "Regions_Intersections", - append = T) +addWorksheet(wb, sheetName = "Regions_Intersections") +writeData(wb, sheet = "Regions_Intersections", genes_by_regions) +saveWorkbook(wb, "results/tables/intersection_tables.xlsx", overwrite = TRUE) ``` diff --git a/scripts/summarise_biotypes.R b/scripts/summarise_biotypes.R index c3aecfd..e190429 100644 --- a/scripts/summarise_biotypes.R +++ b/scripts/summarise_biotypes.R @@ -63,19 +63,19 @@ dtu_w_biotype <- dtu_w_biotype %>% dge_plot <- dge_w_biotype %>% group_by(biotype) %>% - summarise(biotype_n = n() / length(unique(dge_w_biotype$gene_id)) * 100) %>% + dplyr::summarise(biotype_n = dplyr::n() / length(unique(dge_w_biotype$gene_id)) * 100) %>% ungroup() %>% - mutate(type = "DGE") + dplyr::mutate(type = "DGE") dte_plot <- dte_w_biotype %>% group_by(biotype) %>% - summarise(biotype_n = n() / length(unique(dte_w_biotype$transcript_id))* 100) %>% + summarise(biotype_n = dplyr::n() / length(unique(dte_w_biotype$transcript_id))* 100) %>% ungroup() %>% mutate(type = "DTE") dtu_plot <- dtu_w_biotype %>% group_by(biotype) %>% - summarise(biotype_n = n() / length(unique(dtu_w_biotype$isoform_id))* 100) %>% + summarise(biotype_n = dplyr::n() / length(unique(dtu_w_biotype$isoform_id))* 100) %>% ungroup() %>% mutate(type = "DTU") @@ -105,7 +105,7 @@ ggsave(biotype_plot, file = "results/plots_paper/biotype_plot.pdf", width = 7, h dge_plot <- dge_w_biotype %>% separate(group, into = c("region", "sex")) %>% group_by(biotype, sex) %>% - summarise(biotype_n = n()) %>% + summarise(biotype_n = dplyr::n()) %>% ungroup() %>% group_by(sex) %>% mutate(prop = biotype_n / sum(biotype_n) * 100, @@ -114,7 +114,7 @@ dge_plot <- dge_w_biotype %>% dte_plot <- dte_w_biotype %>% separate(group, into = c("region", "sex")) %>% group_by(biotype, sex) %>% - summarise(biotype_n = n()) %>% + summarise(biotype_n = dplyr::n()) %>% ungroup() %>% group_by(sex) %>% mutate(prop = biotype_n / sum(biotype_n) * 100, @@ -123,7 +123,7 @@ dte_plot <- dte_w_biotype %>% dtu_plot <- dtu_w_biotype %>% separate(group, into = c("region", "sex")) %>% group_by(biotype, sex) %>% - summarise(biotype_n = n()) %>% + summarise(biotype_n = dplyr::n()) %>% ungroup() %>% group_by(sex) %>% mutate(prop = biotype_n / sum(biotype_n) * 100, @@ -149,7 +149,7 @@ ggplot(df_plot, aes(x = reorder(biotype, dplyr::desc(prop)), y = prop, fill = ty strip.background = element_rect(fill = "white")) -> biotype_plot_by_sex # Save -ggsave(biotype_plot_by_sex, filename = "results/plots_paper/biotype_by_sexplot.pdf", width = 7, height = 4) +ggsave(biotype_plot_by_sex, filename = "results/plots_paper/fig3.pdf", width = 7, height = 4) # Test feature prevalence differences between female and male ------------- @@ -165,7 +165,7 @@ biotypes_by_sex %>% group_map(~ { cat(.y$type, sep = "\n") cont_table <- table(.x$biotype, .x$sex) - return(list(fisher = fisher.test(cont_table), count_table = cont_table)) + return(list(fisher = fisher.test(cont_table, simulate.p.value = T), count_table = cont_table)) }) -> biot_tests_fisher biotypes_by_sex %>% @@ -214,10 +214,10 @@ biotypes_by_sex %>% arrange(type, biotype) %>% filter(sex == "female") %>% group_by(region, type) %>% - mutate(n1 = n()) %>% + mutate(n1 = dplyr::n()) %>% ungroup() %>% group_by(biotype, type, region) %>% - mutate(n2 = n(), + mutate(n2 = dplyr::n(), prop_by_region = (n2 / n1) * 100) %>% arrange(desc(type), desc(region)) %>% ungroup() %>% @@ -245,10 +245,10 @@ biotypes_by_sex %>% arrange(type, biotype) %>% filter(sex == "male") %>% group_by(region, type) %>% - mutate(n1 = n()) %>% + mutate(n1 = dplyr::n()) %>% ungroup() %>% group_by(biotype, type,region) %>% - mutate(n2 = n(), + mutate(n2 = dplyr::n(), prop_by_region = (n2 / n1) * 100) %>% arrange(desc(type), desc(region)) %>% ungroup() %>% From 22c0b94878c8296964dc95349f1ce6871db67d38 Mon Sep 17 00:00:00 2001 From: Iara Souza Date: Tue, 24 Oct 2023 13:31:19 -0300 Subject: [PATCH 22/24] fix: modified gitignore --- .gitignore | 3 +-- results/tx_enrich/go_terms.csv | 41 +++++++++++++++++----------------- 2 files changed, 21 insertions(+), 23 deletions(-) diff --git a/.gitignore b/.gitignore index 1aaeee8..ee121ee 100644 --- a/.gitignore +++ b/.gitignore @@ -20,5 +20,4 @@ renv/* slurm* run* data/* -results/diff_exp/* -results/ISA/ +results/* diff --git a/results/tx_enrich/go_terms.csv b/results/tx_enrich/go_terms.csv index ddc0a4d..4016f08 100644 --- a/results/tx_enrich/go_terms.csv +++ b/results/tx_enrich/go_terms.csv @@ -1,22 +1,21 @@ ID,Description,GeneRatio,BgRatio,pvalue,p.adjust,qvalue,geneID,Count,group -GO:0030858,positive regulation of epithelial cell differentiation,3/25,64/18723,8.30298595424994e-5,0.04799125881556465,3.75e-02,PRKCH/NME2/PROM1,3,aINS_female -GO:0002181,cytoplasmic translation,9/172,148/18723,9.284720354690927e-6,0.022459738537997355,2.17e-02,RPL27/RPL7/RPL24/RPS27/RPL22/EIF3CL/RPL38/EIF3L/RPS3,9,Cg25_male -GO:0002181,cytoplasmic translation,20/354,148/18723,6.034935546363268e-12,1.8702265258179768e-8,1.78e-08,RPL36A/RPL27/RPS19/RPL39/RPS10/UNK/RPS15A/RPL18/EIF3A/RPL23/RPL10/RPS7/RPS14/RPS23/RPL3/RPS27A/EIF3G/RPL7A/RPL13A/RPL26,20,OFC_female -GO:0000377,"RNA splicing, via transesterification reactions with bulged adenosine as nucleophile",21/354,320/18723,8.527948419500151e-7,7.696906681208437e-4,7.33e-04,HNRNPA2B1/HNRNPA1/HNRNPH3/CASC3/SFPQ/NCL/SART1/DDX46/SF1/RNPS1/HNRNPA3/RBM17/DDX39B/HNRNPM/SRSF5/C1QBP/PNN/ZCRB1/SRPK3/YJU2/RBM10,21,OFC_female -GO:0000398,"mRNA splicing, via spliceosome",21/354,320/18723,8.527948419500151e-7,7.696906681208437e-4,7.33e-04,HNRNPA2B1/HNRNPA1/HNRNPH3/CASC3/SFPQ/NCL/SART1/DDX46/SF1/RNPS1/HNRNPA3/RBM17/DDX39B/HNRNPM/SRSF5/C1QBP/PNN/ZCRB1/SRPK3/YJU2/RBM10,21,OFC_female -GO:0000375,"RNA splicing, via transesterification reactions",21/354,324/18723,1.0422977974782387e-6,7.696906681208437e-4,7.33e-04,HNRNPA2B1/HNRNPA1/HNRNPH3/CASC3/SFPQ/NCL/SART1/DDX46/SF1/RNPS1/HNRNPA3/RBM17/DDX39B/HNRNPM/SRSF5/C1QBP/PNN/ZCRB1/SRPK3/YJU2/RBM10,21,OFC_female -GO:0022900,electron transport chain,15/354,175/18723,1.2418371541155916e-6,7.696906681208437e-4,7.33e-04,COX3/UQCRQ/UQCR11/SDHD/NDUFB2/COX7C/GBA/COX7B2/CHCHD2/GSR/PARK7/SDHB/NDUFB10/ADH5/COX6C,15,OFC_female -GO:0022904,respiratory electron transport chain,12/354,114/18723,1.698069370239057e-6,8.770528297284729e-4,8.35e-04,COX3/UQCRQ/UQCR11/SDHD/NDUFB2/COX7C/GBA/CHCHD2/PARK7/SDHB/NDUFB10/COX6C,12,OFC_female -GO:0009060,aerobic respiration,15/354,189/18723,3.252170243494876e-6,0.0014397822263700888,1.37e-03,COX3/UQCRQ/UQCR11/SDHD/ANTKMT/NDUFB2/COX7C/NNT/COX7B2/CHCHD2/PARK7/PDHB/SDHB/NDUFB10/COX6C,15,OFC_female -GO:0045333,cellular respiration,16/354,230/18723,8.390432950595276e-6,0.0032502439642368448,3.09e-03,COX3/UQCRQ/UQCR11/SDHD/ANTKMT/NDUFB2/COX7C/NNT/GBA/COX7B2/CHCHD2/PARK7/PDHB/SDHB/NDUFB10/COX6C,16,OFC_female -GO:0008380,RNA splicing,23/354,434/18723,9.56260978898458e-6,0.003292725304007024,3.13e-03,HNRNPA2B1/HNRNPA1/HNRNPH3/CASC3/SFPQ/NCL/SART1/DDX46/SF1/RNPS1/HNRNPA3/RBM17/CTNNBL1/DDX39B/HNRNPM/FUS/SRSF5/C1QBP/PNN/ZCRB1/SRPK3/YJU2/RBM10,23,OFC_female -GO:0042773,ATP synthesis coupled electron transport,10/354,95/18723,1.2495335857215579e-5,0.003520276892864644,3.35e-03,COX3/UQCRQ/UQCR11/SDHD/NDUFB2/COX7C/CHCHD2/PARK7/NDUFB10/COX6C,10,OFC_female -GO:0042775,mitochondrial ATP synthesis coupled electron transport,10/354,95/18723,1.2495335857215579e-5,0.003520276892864644,3.35e-03,COX3/UQCRQ/UQCR11/SDHD/NDUFB2/COX7C/CHCHD2/PARK7/NDUFB10/COX6C,10,OFC_female -GO:0006119,oxidative phosphorylation,12/354,141/18723,1.5525975786513112e-5,0.004009583246867011,3.82e-03,COX3/UQCRQ/UQCR11/SDHD/ANTKMT/NDUFB2/COX7C/COX7B2/CHCHD2/PARK7/NDUFB10/COX6C,12,OFC_female -GO:0022618,ribonucleoprotein complex assembly,15/354,220/18723,2.0326057552656432e-5,0.0048454194119755606,4.61e-03,RPS19/SART1/SF1/DHX30/EIF3A/RPL10/DDX39B/RPS14/RPL3/AGO4/EIF3G/SRSF5/RPL13A/SRPK3/YJU2,15,OFC_female -GO:0022613,ribonucleoprotein complex biogenesis,23/354,463/18723,2.6717121336838507e-5,0.0059140256444901815,5.63e-03,RPL27/RPS19/NOP56/SART1/NOLC1/SF1/DHX30/EIF3A/RPL10/DDX39B/RPS7/RPP40/RPS14/RPL3/AGO4/EIF3G/SRSF5/RPL7A/C1QBP/RPL13A/RPL26/SRPK3/YJU2,23,OFC_female -GO:0071826,ribonucleoprotein complex subunit organization,15/354,227/18723,2.9313781484128114e-5,0.006056227254620868,5.76e-03,RPS19/SART1/SF1/DHX30/EIF3A/RPL10/DDX39B/RPS14/RPL3/AGO4/EIF3G/SRSF5/RPL13A/SRPK3/YJU2,15,OFC_female -GO:1903311,regulation of mRNA metabolic process,17/354,288/18723,3.71319720449354e-5,0.0071281511815515786,6.78e-03,SUPT5H/HNRNPA1/LARP1/NCL/SF1/RNPS1/POLR2G/TENT4A/HNRNPM/NBAS/SAFB/FUS/TNRC6B/C1QBP/TBRG4/SRPK3/RBM10,17,OFC_female -GO:0019646,aerobic electron transport chain,9/354,87/18723,3.910247501980537e-5,0.0071281511815515786,6.78e-03,COX3/UQCRQ/UQCR11/SDHD/NDUFB2/COX7C/PARK7/NDUFB10/COX6C,9,OFC_female -GO:2001252,positive regulation of chromosome organization,8/354,82/18723,1.5920489566435716e-4,0.027409776203546822,2.61e-02,HNRNPA2B1/HNRNPA1/DNMT1/SFPQ/SETDB1/GTF2H2/SSBP1/SLX1A,8,OFC_female -GO:1902253,regulation of intrinsic apoptotic signaling pathway by p53 class mediator,5/354,29/18723,1.9198597909498622e-4,0.031313923642913806,2.98e-02,MARCHF7/ARMC10/UBB/RPS7/RPL26,5,OFC_female +GO:0002181,cytoplasmic translation,9/173,148/18723,9.729058041215098e-6,0.02356377857582297,2.28e-02,RPL27/RPL7/RPL24/RPS27/RPL22/EIF3CL/RPL38/EIF3L/RPS3,9,Cg25_male +GO:0002181,cytoplasmic translation,20/356,148/18723,6.686838989923526e-12,2.07492613857327e-8,1.98e-08,RPL36A/RPL27/RPS19/RPL39/RPS10/UNK/RPS15A/RPL18/EIF3A/RPL23/RPL10/RPS7/RPS14/RPS23/RPL3/RPS27A/EIF3G/RPL7A/RPL13A/RPL26,20,OFC_female +GO:0000377,"RNA splicing, via transesterification reactions with bulged adenosine as nucleophile",21/356,320/18723,9.339644344838082e-7,8.266077207553366e-4,7.88e-04,HNRNPA2B1/HNRNPA1/HNRNPH3/CASC3/SFPQ/NCL/SART1/DDX46/SF1/RNPS1/HNRNPA3/RBM17/DDX39B/HNRNPM/SRSF5/C1QBP/PNN/ZCRB1/SRPK3/YJU2/RBM10,21,OFC_female +GO:0000398,"mRNA splicing, via spliceosome",21/356,320/18723,9.339644344838082e-7,8.266077207553366e-4,7.88e-04,HNRNPA2B1/HNRNPA1/HNRNPH3/CASC3/SFPQ/NCL/SART1/DDX46/SF1/RNPS1/HNRNPA3/RBM17/DDX39B/HNRNPM/SRSF5/C1QBP/PNN/ZCRB1/SRPK3/YJU2/RBM10,21,OFC_female +GO:0000375,"RNA splicing, via transesterification reactions",21/356,324/18723,1.1410381691315182e-6,8.266077207553366e-4,7.88e-04,HNRNPA2B1/HNRNPA1/HNRNPH3/CASC3/SFPQ/NCL/SART1/DDX46/SF1/RNPS1/HNRNPA3/RBM17/DDX39B/HNRNPM/SRSF5/C1QBP/PNN/ZCRB1/SRPK3/YJU2/RBM10,21,OFC_female +GO:0022900,electron transport chain,15/356,175/18723,1.3319492761123696e-6,8.266077207553366e-4,7.88e-04,COX3/UQCRQ/UQCR11/SDHD/NDUFB2/COX7C/GBA/COX7B2/CHCHD2/GSR/PARK7/SDHB/NDUFB10/ADH5/COX6C,15,OFC_female +GO:0022904,respiratory electron transport chain,12/356,114/18723,1.8004314065485603e-6,9.31123109086697e-4,8.87e-04,COX3/UQCRQ/UQCR11/SDHD/NDUFB2/COX7C/GBA/CHCHD2/PARK7/SDHB/NDUFB10/COX6C,12,OFC_female +GO:0009060,aerobic respiration,15/356,189/18723,3.4832897535986416e-6,0.0015440925864880835,1.47e-03,COX3/UQCRQ/UQCR11/SDHD/ANTKMT/NDUFB2/COX7C/NNT/COX7B2/CHCHD2/PARK7/PDHB/SDHB/NDUFB10/COX6C,15,OFC_female +GO:0045333,cellular respiration,16/356,230/18723,9.002683148259004e-6,0.003491915726130961,3.33e-03,COX3/UQCRQ/UQCR11/SDHD/ANTKMT/NDUFB2/COX7C/NNT/GBA/COX7B2/CHCHD2/PARK7/PDHB/SDHB/NDUFB10/COX6C,16,OFC_female +GO:0008380,RNA splicing,23/356,434/18723,1.0475791849120676e-5,0.003611820234202384,3.44e-03,HNRNPA2B1/HNRNPA1/HNRNPH3/CASC3/SFPQ/NCL/SART1/DDX46/SF1/RNPS1/HNRNPA3/RBM17/CTNNBL1/DDX39B/HNRNPM/FUS/SRSF5/C1QBP/PNN/ZCRB1/SRPK3/YJU2/RBM10,23,OFC_female +GO:0042773,ATP synthesis coupled electron transport,10/356,95/18723,1.311973119745828e-5,0.003700956900519367,3.53e-03,COX3/UQCRQ/UQCR11/SDHD/NDUFB2/COX7C/CHCHD2/PARK7/NDUFB10/COX6C,10,OFC_female +GO:0042775,mitochondrial ATP synthesis coupled electron transport,10/356,95/18723,1.311973119745828e-5,0.003700956900519367,3.53e-03,COX3/UQCRQ/UQCR11/SDHD/NDUFB2/COX7C/CHCHD2/PARK7/NDUFB10/COX6C,10,OFC_female +GO:0006119,oxidative phosphorylation,12/356,141/18723,1.6418404463433016e-5,0.004245525754169387,4.05e-03,COX3/UQCRQ/UQCR11/SDHD/ANTKMT/NDUFB2/COX7C/COX7B2/CHCHD2/PARK7/NDUFB10/COX6C,12,OFC_female +GO:0022618,ribonucleoprotein complex assembly,15/356,220/18723,2.1703603179094842e-5,0.005180483128056254,4.94e-03,RPS19/SART1/SF1/DHX30/EIF3A/RPL10/DDX39B/RPS14/RPL3/AGO4/EIF3G/SRSF5/RPL13A/SRPK3/YJU2,15,OFC_female +GO:0022613,ribonucleoprotein complex biogenesis,23/356,463/18723,2.9182024528050987e-5,0.006467987293610158,6.16e-03,RPL27/RPS19/NOP56/SART1/NOLC1/SF1/DHX30/EIF3A/RPL10/DDX39B/RPS7/RPP40/RPS14/RPL3/AGO4/EIF3G/SRSF5/RPL7A/C1QBP/RPL13A/RPL26/SRPK3/YJU2,23,OFC_female +GO:0071826,ribonucleoprotein complex subunit organization,15/356,227/18723,3.127877009566171e-5,0.006470534907122553,6.17e-03,RPS19/SART1/SF1/DHX30/EIF3A/RPL10/DDX39B/RPS14/RPL3/AGO4/EIF3G/SRSF5/RPL13A/SRPK3/YJU2,15,OFC_female +GO:1903311,regulation of mRNA metabolic process,17/356,288/18723,3.984445672827929e-5,0.007456575510489551,7.11e-03,SUPT5H/HNRNPA1/LARP1/NCL/SF1/RNPS1/POLR2G/TENT4A/HNRNPM/NBAS/SAFB/FUS/TNRC6B/C1QBP/TBRG4/SRPK3/RBM10,17,OFC_female +GO:0019646,aerobic electron transport chain,9/356,87/18723,4.085136438231465e-5,0.007456575510489551,7.11e-03,COX3/UQCRQ/UQCR11/SDHD/NDUFB2/COX7C/PARK7/NDUFB10/COX6C,9,OFC_female +GO:2001252,positive regulation of chromosome organization,8/356,82/18723,1.6545126184103776e-4,0.02852195919404112,2.72e-02,HNRNPA2B1/HNRNPA1/DNMT1/SFPQ/SETDB1/GTF2H2/SSBP1/SLX1A,8,OFC_female +GO:1902253,regulation of intrinsic apoptotic signaling pathway by p53 class mediator,5/356,29/18723,1.9707873358949942e-4,0.03218606896464299,3.07e-02,MARCHF7/ARMC10/UBB/RPS7/RPL26,5,OFC_female From 3476857a004556e51b6341aae40b726b122b7671 Mon Sep 17 00:00:00 2001 From: Iara Souza Date: Tue, 24 Oct 2023 13:40:06 -0300 Subject: [PATCH 23/24] fix: rebuilt ppi network after stageR correction --- results/networks/model_edges.txt | 5031 ++++++++++++++++-------------- results/networks/model_nodes.txt | 1172 +++---- 2 files changed, 3265 insertions(+), 2938 deletions(-) diff --git a/results/networks/model_edges.txt b/results/networks/model_edges.txt index 493da78..bb85423 100644 --- a/results/networks/model_edges.txt +++ b/results/networks/model_edges.txt @@ -1,2408 +1,2709 @@ node_a node_b weight 0 1 0.0 -0 2 0.0 -0 3 0.0 -0 4 0.0 -5 6 0.0 -5 7 0.0 -8 9 0.0 -8 10 0.0 -8 11 0.0 -8 12 0.0 -8 13 0.0 -8 14 0.0 -8 15 0.0 -8 16 0.0 -8 17 0.0 -8 18 0.0 -8 19 0.0 -8 20 0.0 -8 21 0.0 -22 23 0.0 -22 24 0.0 -22 25 0.0 -26 27 0.0 -28 29 0.0 -25 30 0.0 -25 31 0.0 -2 25 0.0 -25 32 0.0 -23 25 0.0 -25 33 0.0 -25 34 0.0 -25 35 0.0 -24 25 0.0 -7 25 0.0 -36 37 0.0 -36 38 0.0 +2 3 0.0 +2 4 0.0 +2 5 0.0 +2 6 0.0 +2 7 0.0 +2 8 0.0 +2 9 0.0 +2 10 0.0 +11 12 0.0 +11 13 0.0 +11 14 0.0 +11 15 0.0 +11 16 0.0 +11 17 0.0 +11 18 0.0 +11 19 0.0 +11 20 0.0 +11 21 0.0 +11 22 0.0 +11 23 0.0 +11 24 0.0 +25 26 0.0 +5 27 0.0 +27 28 0.0 +27 29 0.0 +27 30 0.0 +7 27 0.0 +27 31 0.0 +27 32 0.0 +6 27 0.0 +27 33 0.0 +27 34 0.0 +8 27 0.0 +27 35 0.0 +27 36 0.0 +37 38 0.0 39 40 0.0 39 41 0.0 39 42 0.0 39 43 0.0 -39 44 0.0 -39 45 0.0 -39 46 0.0 -47 48 0.0 -47 49 0.0 -47 50 0.0 -32 35 0.0 -51 52 0.0 -51 53 0.0 -51 54 0.0 -51 55 0.0 -51 56 0.0 -51 57 0.0 -58 59 0.0 -58 60 0.0 -58 61 0.0 -58 62 0.0 +44 45 0.0 +22 44 0.0 +44 46 0.0 +44 47 0.0 +44 48 0.0 +44 49 0.0 +44 50 0.0 +44 51 0.0 +44 52 0.0 +53 54 0.0 +55 56 0.0 +55 57 0.0 +55 58 0.0 +55 59 0.0 +55 60 0.0 +61 62 0.0 63 64 0.0 63 65 0.0 -66 67 0.0 -66 68 0.0 -7 69 0.0 -70 71 0.0 -70 72 0.0 -70 73 0.0 -74 75 0.0 -74 76 0.0 +63 66 0.0 +63 67 0.0 +63 68 0.0 +63 69 0.0 +63 70 0.0 +63 71 0.0 +63 72 0.0 +63 73 0.0 +63 74 0.0 +63 75 0.0 +26 76 0.0 +18 76 0.0 +17 76 0.0 77 78 0.0 -79 80 0.0 -9 81 0.0 -81 82 0.0 -81 83 0.0 -33 81 0.0 -81 84 0.0 -81 85 0.0 -16 81 0.0 -17 81 0.0 -81 86 0.0 -81 87 0.0 -81 88 0.0 -19 81 0.0 -13 81 0.0 -81 89 0.0 -81 90 0.0 -81 91 0.0 -81 92 0.0 -12 81 0.0 -15 81 0.0 -14 81 0.0 -81 93 0.0 -10 81 0.0 -81 94 0.0 -81 95 0.0 -81 96 0.0 -81 97 0.0 -81 98 0.0 -81 99 0.0 -3 81 0.0 -81 100 0.0 -101 102 0.0 -90 103 0.0 -98 103 0.0 -96 103 0.0 -95 103 0.0 -91 103 0.0 -16 103 0.0 -93 103 0.0 -104 105 0.0 -104 106 0.0 -104 107 0.0 -104 108 0.0 -104 109 0.0 -104 110 0.0 -104 111 0.0 -104 112 0.0 -104 113 0.0 -104 114 0.0 -104 115 0.0 -104 116 0.0 -104 117 0.0 -118 119 0.0 -120 121 0.0 -120 122 0.0 -24 123 0.0 -123 124 0.0 -123 125 0.0 -11 123 0.0 -123 126 0.0 -61 127 0.0 -127 128 0.0 -129 130 0.0 -129 131 0.0 -129 132 0.0 -129 133 0.0 -87 129 0.0 -129 134 0.0 -129 135 0.0 -136 137 0.0 -136 138 0.0 -136 139 0.0 -136 140 0.0 -136 141 0.0 -136 142 0.0 -136 143 0.0 -18 144 0.0 -18 21 0.0 -18 20 0.0 -145 146 0.0 -30 31 0.0 -86 147 0.0 -82 147 0.0 -92 147 0.0 -147 148 0.0 -14 147 0.0 -84 147 0.0 -93 147 0.0 -89 147 0.0 -83 147 0.0 -29 147 0.0 -17 147 0.0 -87 147 0.0 -147 149 0.0 -16 147 0.0 -147 150 0.0 -147 151 0.0 -147 152 0.0 -147 153 0.0 -147 154 0.0 -11 155 0.0 -72 156 0.0 -156 157 0.0 +77 79 0.0 +77 80 0.0 +77 81 0.0 +77 82 0.0 +77 83 0.0 +77 84 0.0 +85 86 0.0 +85 87 0.0 +85 88 0.0 +85 89 0.0 +90 91 0.0 +92 93 0.0 +92 94 0.0 +92 95 0.0 +96 97 0.0 +98 99 0.0 +98 100 0.0 +98 101 0.0 +98 102 0.0 +103 104 0.0 +103 105 0.0 +103 106 0.0 +107 108 0.0 +107 109 0.0 +110 111 0.0 +47 48 0.0 +47 112 0.0 +47 51 0.0 +64 113 0.0 +113 114 0.0 +113 115 0.0 +29 113 0.0 +24 113 0.0 +113 116 0.0 +113 117 0.0 +113 118 0.0 +17 113 0.0 +113 119 0.0 +113 120 0.0 +113 121 0.0 +28 113 0.0 +34 113 0.0 +32 113 0.0 +113 122 0.0 +113 123 0.0 +113 124 0.0 +113 125 0.0 +6 113 0.0 +8 113 0.0 +7 113 0.0 +113 126 0.0 +113 127 0.0 +113 128 0.0 +30 113 0.0 +113 129 0.0 +113 130 0.0 +113 131 0.0 +113 132 0.0 +31 113 0.0 +5 113 0.0 +113 133 0.0 +134 135 0.0 +123 136 0.0 +130 136 0.0 +133 136 0.0 +126 136 0.0 +34 136 0.0 +128 136 0.0 +131 136 0.0 +137 138 0.0 +64 137 0.0 +137 139 0.0 +59 137 0.0 +40 137 0.0 +137 140 0.0 +137 141 0.0 +137 142 0.0 +137 143 0.0 +137 144 0.0 +137 145 0.0 +146 147 0.0 +148 149 0.0 +148 150 0.0 +29 151 0.0 +9 151 0.0 +86 152 0.0 +153 154 0.0 +153 155 0.0 +153 156 0.0 +18 153 0.0 +17 153 0.0 +153 157 0.0 158 159 0.0 158 160 0.0 158 161 0.0 -71 158 0.0 -87 162 0.0 -133 162 0.0 -162 163 0.0 -162 164 0.0 -162 165 0.0 +158 162 0.0 +158 163 0.0 +158 164 0.0 +158 165 0.0 33 166 0.0 -167 168 0.0 -3 167 0.0 -169 170 0.0 -54 171 0.0 -171 172 0.0 +33 167 0.0 +33 36 0.0 +33 35 0.0 +168 169 0.0 +168 170 0.0 +168 171 0.0 +38 168 0.0 +168 172 0.0 +18 173 0.0 +131 173 0.0 +28 173 0.0 +64 173 0.0 173 174 0.0 +118 173 0.0 +124 173 0.0 +125 173 0.0 +32 173 0.0 +122 173 0.0 +119 173 0.0 +34 173 0.0 +17 173 0.0 +120 173 0.0 173 175 0.0 173 176 0.0 +121 173 0.0 173 177 0.0 -178 179 0.0 -43 178 0.0 -86 178 0.0 -178 180 0.0 -178 181 0.0 -121 178 0.0 -178 182 0.0 -42 178 0.0 -41 178 0.0 -178 183 0.0 -178 184 0.0 -178 185 0.0 -114 178 0.0 -178 186 0.0 -178 187 0.0 -178 188 0.0 -116 178 0.0 -178 189 0.0 -178 190 0.0 -178 191 0.0 -99 192 0.0 -192 193 0.0 -98 192 0.0 -91 192 0.0 -92 192 0.0 -139 192 0.0 -38 192 0.0 -192 194 0.0 -144 192 0.0 -192 195 0.0 -140 192 0.0 -192 196 0.0 -192 197 0.0 -102 192 0.0 -192 198 0.0 -38 199 0.0 -191 200 0.0 -41 191 0.0 -114 191 0.0 -182 191 0.0 -185 191 0.0 -42 191 0.0 -187 191 0.0 -45 191 0.0 -186 191 0.0 -121 191 0.0 -191 201 0.0 -191 202 0.0 -179 191 0.0 -116 191 0.0 -190 191 0.0 -189 191 0.0 -88 203 0.0 -88 204 0.0 -88 205 0.0 -88 117 0.0 -88 206 0.0 -88 207 0.0 -208 209 0.0 -157 208 0.0 -208 210 0.0 -208 211 0.0 -208 212 0.0 -56 208 0.0 -208 213 0.0 -214 215 0.0 -31 62 0.0 -31 76 0.0 -31 204 0.0 -31 216 0.0 -31 128 0.0 -31 217 0.0 -31 218 0.0 -31 163 0.0 -7 31 0.0 -219 220 0.0 -205 221 0.0 -221 222 0.0 -221 223 0.0 -221 224 0.0 -221 225 0.0 +173 178 0.0 +173 179 0.0 +180 181 0.0 +104 180 0.0 +182 183 0.0 +184 185 0.0 +181 184 0.0 +184 186 0.0 +105 184 0.0 +18 187 0.0 +17 187 0.0 +187 188 0.0 +187 189 0.0 +187 190 0.0 +46 191 0.0 +24 46 0.0 +46 192 0.0 +46 193 0.0 +194 195 0.0 +83 194 0.0 +196 197 0.0 +196 198 0.0 +196 199 0.0 +196 200 0.0 +8 73 0.0 +73 201 0.0 +73 202 0.0 +73 203 0.0 +70 73 0.0 +73 204 0.0 +69 73 0.0 +73 149 0.0 +73 205 0.0 +73 206 0.0 +73 207 0.0 +71 73 0.0 +73 181 0.0 +73 208 0.0 +67 73 0.0 +73 209 0.0 +73 210 0.0 +73 211 0.0 +73 212 0.0 +73 75 0.0 +73 213 0.0 +73 214 0.0 +73 215 0.0 +73 216 0.0 +73 217 0.0 +64 73 0.0 +66 73 0.0 +68 73 0.0 +218 219 0.0 +160 218 0.0 +218 220 0.0 +218 221 0.0 +161 218 0.0 +218 222 0.0 +218 223 0.0 +135 218 0.0 +218 224 0.0 +218 225 0.0 226 227 0.0 -52 228 0.0 -52 57 0.0 -52 54 0.0 -229 230 0.0 -154 231 0.0 -105 154 0.0 -154 205 0.0 -116 154 0.0 -98 154 0.0 -154 232 0.0 -9 154 0.0 -10 154 0.0 -154 233 0.0 -94 154 0.0 -42 154 0.0 -154 234 0.0 -85 154 0.0 -154 185 0.0 -154 235 0.0 -114 154 0.0 -29 154 0.0 -12 154 0.0 -19 154 0.0 -97 154 0.0 -13 154 0.0 -95 154 0.0 -91 154 0.0 -90 154 0.0 -15 154 0.0 -99 154 0.0 -82 154 0.0 -83 154 0.0 -92 154 0.0 -154 236 0.0 -87 154 0.0 -14 154 0.0 -86 154 0.0 -17 154 0.0 -84 154 0.0 -16 154 0.0 -89 154 0.0 -151 154 0.0 -150 154 0.0 -149 154 0.0 -148 154 0.0 -152 154 0.0 -153 154 0.0 -161 237 0.0 -237 238 0.0 -237 239 0.0 -237 240 0.0 -237 241 0.0 -90 237 0.0 -237 242 0.0 -106 237 0.0 -117 237 0.0 -17 237 0.0 -236 237 0.0 -105 237 0.0 -237 243 0.0 -187 237 0.0 -237 244 0.0 -41 237 0.0 -42 237 0.0 -185 237 0.0 -180 237 0.0 -188 237 0.0 -107 245 0.0 -107 240 0.0 -246 247 0.0 -53 246 0.0 -246 248 0.0 -246 249 0.0 -239 246 0.0 -246 250 0.0 -246 251 0.0 -246 252 0.0 -122 246 0.0 -246 253 0.0 -246 254 0.0 -246 255 0.0 -244 246 0.0 -246 256 0.0 -65 246 0.0 -257 258 0.0 -161 257 0.0 -250 257 0.0 -53 257 0.0 -55 259 0.0 -53 55 0.0 -55 57 0.0 -55 260 0.0 -55 261 0.0 -11 98 0.0 -11 86 0.0 -11 82 0.0 -11 235 0.0 -11 91 0.0 -11 99 0.0 -11 96 0.0 -11 85 0.0 -11 94 0.0 -11 92 0.0 -9 11 0.0 -10 11 0.0 -11 97 0.0 -11 84 0.0 -11 13 0.0 -11 20 0.0 -11 16 0.0 -11 14 0.0 -11 17 0.0 -11 83 0.0 -11 15 0.0 -11 89 0.0 -11 93 0.0 -11 90 0.0 -11 19 0.0 -11 150 0.0 -11 105 0.0 -172 262 0.0 -56 263 0.0 -56 264 0.0 -56 265 0.0 -56 266 0.0 -56 87 0.0 -56 267 0.0 -56 268 0.0 -56 269 0.0 -56 133 0.0 -56 270 0.0 -56 271 0.0 -56 224 0.0 -53 56 0.0 -56 272 0.0 -56 273 0.0 -56 57 0.0 -56 274 0.0 -56 275 0.0 -56 215 0.0 -56 276 0.0 -61 277 0.0 -61 278 0.0 -12 279 0.0 -95 279 0.0 -16 279 0.0 -247 279 0.0 -10 279 0.0 -9 279 0.0 -86 279 0.0 -94 279 0.0 -91 279 0.0 -93 279 0.0 -92 279 0.0 -17 279 0.0 -82 279 0.0 -19 279 0.0 -99 279 0.0 -90 279 0.0 -83 279 0.0 -89 279 0.0 -87 279 0.0 -150 279 0.0 -213 279 0.0 -279 280 0.0 -281 282 0.0 -72 281 0.0 -283 284 0.0 -285 286 0.0 -1 285 0.0 -3 285 0.0 -113 287 0.0 -288 289 0.0 +179 226 0.0 +226 228 0.0 +41 226 0.0 +226 229 0.0 +221 226 0.0 +226 230 0.0 +142 226 0.0 +57 226 0.0 +60 226 0.0 +67 216 0.0 +216 231 0.0 +216 232 0.0 +181 216 0.0 +71 216 0.0 +212 216 0.0 +211 216 0.0 +213 216 0.0 +74 216 0.0 +210 216 0.0 +207 216 0.0 +149 216 0.0 +206 216 0.0 +216 233 0.0 +214 216 0.0 +208 216 0.0 +66 216 0.0 +64 216 0.0 +68 216 0.0 +216 217 0.0 +234 235 0.0 +234 236 0.0 +234 237 0.0 +234 238 0.0 +145 234 0.0 +230 239 0.0 +104 230 0.0 +230 240 0.0 +230 241 0.0 +242 243 0.0 +244 245 0.0 +50 88 0.0 +50 246 0.0 +50 247 0.0 +50 188 0.0 +50 248 0.0 +50 86 0.0 +249 250 0.0 +18 251 0.0 +17 251 0.0 +154 251 0.0 +251 252 0.0 +251 253 0.0 +251 254 0.0 +41 255 0.0 +255 256 0.0 +255 257 0.0 +255 258 0.0 +259 260 0.0 +78 80 0.0 +78 81 0.0 +78 84 0.0 +78 261 0.0 +78 83 0.0 +62 262 0.0 +40 179 0.0 +156 179 0.0 +129 179 0.0 +41 179 0.0 +138 179 0.0 +166 179 0.0 +179 263 0.0 +64 179 0.0 +30 179 0.0 +42 179 0.0 +179 211 0.0 +6 179 0.0 +179 213 0.0 +71 179 0.0 +130 179 0.0 +127 179 0.0 +43 179 0.0 +132 179 0.0 +5 179 0.0 +131 179 0.0 +7 179 0.0 +118 179 0.0 +17 179 0.0 +28 179 0.0 +125 179 0.0 +32 179 0.0 +124 179 0.0 +120 179 0.0 +119 179 0.0 +122 179 0.0 +34 179 0.0 +175 179 0.0 +179 264 0.0 +177 179 0.0 +121 179 0.0 +178 179 0.0 +174 179 0.0 +176 179 0.0 +69 130 0.0 +32 69 0.0 +69 265 0.0 +69 266 0.0 +69 203 0.0 +69 267 0.0 +69 210 0.0 +69 268 0.0 +69 269 0.0 +69 202 0.0 +69 270 0.0 +69 219 0.0 +69 209 0.0 +67 69 0.0 +69 211 0.0 +69 215 0.0 +69 71 0.0 +58 228 0.0 +228 266 0.0 +26 80 0.0 +26 81 0.0 +4 26 0.0 +26 271 0.0 +26 272 0.0 +82 273 0.0 +82 274 0.0 +81 82 0.0 +80 82 0.0 +82 275 0.0 +82 84 0.0 +29 210 0.0 +29 133 0.0 +29 129 0.0 +29 131 0.0 +29 64 0.0 +28 29 0.0 +29 132 0.0 +29 125 0.0 +29 123 0.0 +29 122 0.0 +29 114 0.0 +29 127 0.0 +29 118 0.0 +29 124 0.0 +29 276 0.0 +29 128 0.0 +29 32 0.0 +5 29 0.0 +29 31 0.0 +7 29 0.0 +6 29 0.0 +29 119 0.0 +29 130 0.0 +29 126 0.0 +29 34 0.0 +29 35 0.0 +29 120 0.0 +8 29 0.0 +29 121 0.0 +29 40 0.0 +195 277 0.0 +79 89 0.0 +79 80 0.0 +79 81 0.0 +79 125 0.0 +79 278 0.0 +79 279 0.0 +79 280 0.0 +79 281 0.0 +79 84 0.0 +17 79 0.0 +18 79 0.0 +79 282 0.0 +79 283 0.0 +79 284 0.0 +79 186 0.0 +79 285 0.0 +79 286 0.0 +79 287 0.0 +79 288 0.0 +79 289 0.0 +28 290 0.0 +64 290 0.0 +127 290 0.0 +30 290 0.0 +133 290 0.0 +17 290 0.0 +31 290 0.0 +131 290 0.0 +129 290 0.0 +123 290 0.0 +118 290 0.0 +122 290 0.0 +5 290 0.0 290 291 0.0 -211 290 0.0 -290 292 0.0 -87 293 0.0 -133 293 0.0 -293 294 0.0 -100 293 0.0 -293 295 0.0 -293 296 0.0 -29 297 0.0 -144 297 0.0 -195 297 0.0 -84 298 0.0 +132 290 0.0 +6 290 0.0 +7 290 0.0 +34 290 0.0 +130 290 0.0 +125 290 0.0 +124 290 0.0 +32 290 0.0 +119 290 0.0 +8 290 0.0 +121 290 0.0 +128 290 0.0 +126 290 0.0 +120 290 0.0 +292 293 0.0 +181 292 0.0 +193 294 0.0 +21 94 0.0 +24 94 0.0 +227 245 0.0 +59 227 0.0 +57 227 0.0 +295 296 0.0 +235 297 0.0 +236 297 0.0 298 299 0.0 -216 298 0.0 -133 298 0.0 +18 298 0.0 +17 298 0.0 +115 298 0.0 298 300 0.0 -87 298 0.0 -284 298 0.0 +263 298 0.0 298 301 0.0 -21 110 0.0 -20 21 0.0 +223 229 0.0 +122 302 0.0 +18 302 0.0 302 303 0.0 -268 275 0.0 -266 268 0.0 -87 210 0.0 -133 210 0.0 -210 304 0.0 -210 305 0.0 -210 306 0.0 -210 258 0.0 -210 307 0.0 -210 212 0.0 -7 210 0.0 -161 308 0.0 -53 308 0.0 +17 302 0.0 +193 302 0.0 +302 304 0.0 +302 305 0.0 +30 36 0.0 +36 258 0.0 +34 36 0.0 +36 166 0.0 +36 142 0.0 +35 36 0.0 +306 307 0.0 308 309 0.0 -133 308 0.0 -160 308 0.0 -87 308 0.0 -250 308 0.0 -159 270 0.0 -105 207 0.0 -207 310 0.0 -207 311 0.0 -139 142 0.0 -140 142 0.0 -142 143 0.0 -80 142 0.0 -141 142 0.0 -138 142 0.0 -194 312 0.0 -133 212 0.0 -212 313 0.0 -87 212 0.0 -212 305 0.0 -54 212 0.0 -212 306 0.0 -7 212 0.0 -275 314 0.0 -275 315 0.0 -275 316 0.0 -109 275 0.0 -260 275 0.0 -263 275 0.0 -266 275 0.0 -234 275 0.0 -87 275 0.0 -205 275 0.0 -133 275 0.0 -275 317 0.0 -274 275 0.0 -7 275 0.0 -244 275 0.0 -83 311 0.0 -90 311 0.0 -82 311 0.0 -150 311 0.0 -19 311 0.0 -89 311 0.0 -93 311 0.0 -310 311 0.0 -121 318 0.0 -45 121 0.0 +17 308 0.0 +18 308 0.0 +308 310 0.0 +281 311 0.0 +281 312 0.0 +17 281 0.0 +18 281 0.0 +281 313 0.0 +52 281 0.0 +281 286 0.0 +281 314 0.0 +281 315 0.0 +240 316 0.0 +81 316 0.0 +80 316 0.0 +217 316 0.0 +18 316 0.0 +272 316 0.0 +316 317 0.0 +17 316 0.0 +273 316 0.0 +316 318 0.0 319 320 0.0 -128 319 0.0 -7 319 0.0 -106 321 0.0 -242 321 0.0 321 322 0.0 -62 323 0.0 -62 232 0.0 -62 324 0.0 -62 153 0.0 -34 62 0.0 -62 325 0.0 -35 62 0.0 -62 278 0.0 -206 326 0.0 -87 326 0.0 -133 326 0.0 -326 327 0.0 -326 328 0.0 -168 326 0.0 -326 329 0.0 -326 330 0.0 -114 200 0.0 -188 200 0.0 -187 200 0.0 -183 200 0.0 -41 200 0.0 -205 331 0.0 -164 332 0.0 -164 165 0.0 -164 292 0.0 -164 291 0.0 -164 333 0.0 -163 164 0.0 -133 164 0.0 -164 218 0.0 -7 164 0.0 +40 237 0.0 +237 323 0.0 +162 324 0.0 +162 164 0.0 +162 165 0.0 +162 163 0.0 +154 315 0.0 +155 315 0.0 +156 315 0.0 +18 315 0.0 +315 325 0.0 +315 326 0.0 +312 315 0.0 +17 315 0.0 +83 315 0.0 +52 315 0.0 +313 315 0.0 +155 186 0.0 +186 327 0.0 +186 328 0.0 +154 186 0.0 +186 329 0.0 +156 186 0.0 +138 186 0.0 +186 275 0.0 +186 330 0.0 +42 186 0.0 +18 186 0.0 +17 186 0.0 +41 186 0.0 +186 283 0.0 +186 219 0.0 +64 331 0.0 +131 331 0.0 +276 331 0.0 +122 331 0.0 +114 331 0.0 +127 331 0.0 +129 331 0.0 +6 331 0.0 +7 331 0.0 +132 331 0.0 +34 331 0.0 +123 331 0.0 +32 331 0.0 +118 331 0.0 +124 331 0.0 +31 331 0.0 +125 331 0.0 +5 331 0.0 +119 331 0.0 +130 331 0.0 +121 331 0.0 +126 331 0.0 +8 331 0.0 +120 331 0.0 +128 331 0.0 +323 331 0.0 +149 217 0.0 +149 208 0.0 +74 149 0.0 +332 333 0.0 +86 332 0.0 334 335 0.0 -224 334 0.0 +104 334 0.0 +291 334 0.0 334 336 0.0 -334 337 0.0 -335 338 0.0 -45 230 0.0 -45 339 0.0 -45 340 0.0 -45 114 0.0 -45 46 0.0 -224 335 0.0 -335 336 0.0 -335 337 0.0 -258 341 0.0 -87 258 0.0 -84 258 0.0 -35 320 0.0 -320 342 0.0 -128 320 0.0 -187 289 0.0 -289 343 0.0 -344 345 0.0 -43 116 0.0 -43 241 0.0 -43 114 0.0 -43 180 0.0 -41 43 0.0 -42 43 0.0 -43 185 0.0 -150 346 0.0 -72 346 0.0 +240 334 0.0 +185 334 0.0 +105 334 0.0 +181 334 0.0 +88 337 0.0 +14 88 0.0 +49 88 0.0 +51 88 0.0 +206 232 0.0 +232 270 0.0 +215 232 0.0 +207 232 0.0 +67 232 0.0 +217 232 0.0 +66 232 0.0 +71 232 0.0 +211 232 0.0 +64 232 0.0 +68 232 0.0 +57 232 0.0 +213 232 0.0 +210 232 0.0 +232 233 0.0 +141 338 0.0 +138 141 0.0 +40 141 0.0 +141 339 0.0 +141 340 0.0 +122 141 0.0 +141 142 0.0 +41 141 0.0 +95 141 0.0 +189 341 0.0 +189 342 0.0 +189 343 0.0 +189 344 0.0 +52 189 0.0 +345 346 0.0 +284 345 0.0 +345 347 0.0 +345 348 0.0 +345 349 0.0 +74 208 0.0 +74 217 0.0 +62 74 0.0 +74 268 0.0 +74 350 0.0 +74 213 0.0 +74 75 0.0 346 347 0.0 -190 346 0.0 -348 349 0.0 -41 179 0.0 -42 179 0.0 -179 184 0.0 -179 185 0.0 -179 183 0.0 -114 179 0.0 -179 202 0.0 -179 190 0.0 -116 179 0.0 -179 189 0.0 -133 350 0.0 -87 350 0.0 -300 350 0.0 -350 351 0.0 -350 352 0.0 -350 353 0.0 -269 350 0.0 -350 354 0.0 -100 350 0.0 +284 347 0.0 +347 348 0.0 +347 349 0.0 +122 351 0.0 +351 352 0.0 +86 333 0.0 +51 333 0.0 +333 353 0.0 +210 354 0.0 355 356 0.0 -355 357 0.0 -29 144 0.0 -144 358 0.0 -37 144 0.0 -117 144 0.0 -144 359 0.0 -144 360 0.0 -144 361 0.0 -144 362 0.0 -67 144 0.0 -38 144 0.0 -144 198 0.0 -144 363 0.0 -144 197 0.0 -144 364 0.0 -144 195 0.0 -102 144 0.0 -144 196 0.0 -341 365 0.0 -17 366 0.0 -366 367 0.0 -256 366 0.0 -80 366 0.0 -53 366 0.0 -366 368 0.0 -106 366 0.0 -366 369 0.0 -366 370 0.0 -366 371 0.0 -190 372 0.0 -286 373 0.0 -304 374 0.0 -304 375 0.0 -304 376 0.0 -168 304 0.0 -377 378 0.0 -247 253 0.0 -248 253 0.0 -253 368 0.0 -87 234 0.0 -54 87 0.0 -87 185 0.0 -87 198 0.0 -87 247 0.0 -48 87 0.0 -87 379 0.0 -87 380 0.0 -87 381 0.0 -87 382 0.0 -87 220 0.0 -87 383 0.0 -87 330 0.0 -87 384 0.0 -87 109 0.0 -87 385 0.0 -87 165 0.0 -87 386 0.0 -87 100 0.0 -29 87 0.0 -87 124 0.0 -87 370 0.0 -87 265 0.0 -72 87 0.0 -87 360 0.0 -87 352 0.0 -87 151 0.0 -87 387 0.0 -87 351 0.0 -87 388 0.0 -87 353 0.0 -7 87 0.0 -87 269 0.0 -87 105 0.0 -87 116 0.0 -87 389 0.0 -87 254 0.0 -87 343 0.0 -87 300 0.0 -87 264 0.0 -87 354 0.0 -87 236 0.0 -87 135 0.0 -87 390 0.0 -87 391 0.0 -87 209 0.0 -87 160 0.0 -87 306 0.0 -87 392 0.0 -87 393 0.0 -87 163 0.0 -87 295 0.0 -53 87 0.0 -87 232 0.0 -87 294 0.0 -87 213 0.0 -87 130 0.0 -87 296 0.0 -87 284 0.0 -87 132 0.0 -9 87 0.0 -87 301 0.0 -87 148 0.0 -87 149 0.0 -87 152 0.0 -87 394 0.0 -87 153 0.0 -87 131 0.0 -10 87 0.0 -87 133 0.0 -87 96 0.0 -82 87 0.0 -12 87 0.0 -13 87 0.0 -87 92 0.0 -87 94 0.0 -85 87 0.0 -87 150 0.0 -15 87 0.0 -83 87 0.0 -87 89 0.0 -19 87 0.0 -17 87 0.0 -87 95 0.0 -87 90 0.0 -87 91 0.0 -87 98 0.0 -87 99 0.0 -16 87 0.0 -87 93 0.0 -14 87 0.0 -87 97 0.0 -84 87 0.0 -86 87 0.0 -76 204 0.0 -76 163 0.0 -76 313 0.0 -7 76 0.0 -292 390 0.0 -291 292 0.0 -211 292 0.0 -218 292 0.0 -84 292 0.0 -292 395 0.0 -278 396 0.0 -396 397 0.0 -396 398 0.0 -175 396 0.0 -396 399 0.0 -396 400 0.0 -401 402 0.0 -401 403 0.0 -49 50 0.0 -404 405 0.0 -117 406 0.0 -29 150 0.0 -42 150 0.0 -114 150 0.0 -150 360 0.0 -150 407 0.0 -150 238 0.0 -150 343 0.0 -150 408 0.0 -150 340 0.0 -111 150 0.0 -150 185 0.0 -133 150 0.0 -105 150 0.0 -150 235 0.0 -109 150 0.0 -150 389 0.0 -150 205 0.0 -150 236 0.0 -116 150 0.0 -150 151 0.0 -20 150 0.0 -150 234 0.0 -149 150 0.0 -9 150 0.0 -10 150 0.0 -96 150 0.0 -150 152 0.0 -148 150 0.0 -82 150 0.0 -150 153 0.0 -16 150 0.0 -19 150 0.0 -93 150 0.0 -12 150 0.0 -14 150 0.0 -17 150 0.0 -97 150 0.0 -84 150 0.0 -90 150 0.0 -86 150 0.0 -95 150 0.0 -92 150 0.0 -91 150 0.0 -94 150 0.0 -85 150 0.0 -13 150 0.0 -98 150 0.0 -83 150 0.0 -15 150 0.0 -99 150 0.0 -89 150 0.0 -409 410 0.0 -296 411 0.0 -294 296 0.0 -133 296 0.0 -271 412 0.0 -53 271 0.0 -271 272 0.0 -271 276 0.0 -271 273 0.0 -286 413 0.0 -168 375 0.0 -247 414 0.0 -415 416 0.0 -415 417 0.0 -374 418 0.0 -418 419 0.0 -418 420 0.0 -177 421 0.0 -176 177 0.0 -175 177 0.0 -172 422 0.0 -205 423 0.0 -416 417 0.0 -86 234 0.0 -60 234 0.0 -41 234 0.0 -114 234 0.0 -234 424 0.0 -234 386 0.0 -16 234 0.0 -153 234 0.0 -185 234 0.0 -17 234 0.0 -48 234 0.0 -42 234 0.0 -83 234 0.0 -234 236 0.0 -15 234 0.0 -14 234 0.0 -116 234 0.0 -234 314 0.0 -234 316 0.0 -90 234 0.0 -89 234 0.0 -234 315 0.0 -19 234 0.0 -12 234 0.0 -95 234 0.0 -234 260 0.0 -109 234 0.0 -85 234 0.0 -97 234 0.0 -13 234 0.0 -105 234 0.0 -99 234 0.0 -84 234 0.0 -29 234 0.0 -205 234 0.0 -75 425 0.0 +64 70 0.0 +70 215 0.0 +70 213 0.0 +70 209 0.0 +67 70 0.0 +70 71 0.0 +70 211 0.0 +121 357 0.0 +267 357 0.0 +217 357 0.0 +357 358 0.0 +359 360 0.0 +359 361 0.0 +205 208 0.0 +71 208 0.0 +206 208 0.0 +208 211 0.0 +207 208 0.0 +208 213 0.0 +208 214 0.0 +208 217 0.0 +64 208 0.0 +66 208 0.0 +68 208 0.0 +18 362 0.0 +17 362 0.0 +362 363 0.0 +364 365 0.0 +364 366 0.0 +223 367 0.0 +223 238 0.0 +223 368 0.0 +223 369 0.0 +100 223 0.0 +57 223 0.0 +223 370 0.0 +60 223 0.0 +223 371 0.0 +223 372 0.0 +222 223 0.0 +223 225 0.0 +135 223 0.0 +223 224 0.0 +223 373 0.0 +223 374 0.0 +339 375 0.0 +375 376 0.0 +375 377 0.0 +324 375 0.0 +375 378 0.0 +81 375 0.0 +80 375 0.0 +139 375 0.0 +375 379 0.0 +380 381 0.0 +217 231 0.0 +382 383 0.0 +307 382 0.0 +382 384 0.0 +382 385 0.0 +314 386 0.0 +314 387 0.0 +314 388 0.0 +191 314 0.0 +389 390 0.0 +66 389 0.0 +203 389 0.0 +350 391 0.0 +220 391 0.0 +391 392 0.0 +391 393 0.0 +391 394 0.0 +17 273 0.0 +17 71 0.0 +17 395 0.0 +17 396 0.0 +17 89 0.0 +17 301 0.0 +17 397 0.0 +17 253 0.0 +17 211 0.0 +17 393 0.0 +17 291 0.0 +17 225 0.0 +17 398 0.0 +17 399 0.0 +17 400 0.0 +17 401 0.0 +17 402 0.0 +17 403 0.0 +17 404 0.0 +17 405 0.0 +17 406 0.0 +17 252 0.0 +17 83 0.0 +17 157 0.0 +17 190 0.0 +17 407 0.0 +17 313 0.0 +17 20 0.0 +17 185 0.0 +17 188 0.0 +17 340 0.0 +17 286 0.0 +17 408 0.0 +17 254 0.0 +17 339 0.0 +17 181 0.0 +17 19 0.0 +17 409 0.0 +17 410 0.0 +17 109 0.0 +17 411 0.0 +17 115 0.0 +17 412 0.0 +17 263 0.0 +17 413 0.0 +17 300 0.0 +17 414 0.0 +17 241 0.0 +17 415 0.0 +17 240 0.0 +17 155 0.0 +17 154 0.0 +17 52 0.0 +17 416 0.0 +17 193 0.0 +17 40 0.0 +17 279 0.0 +17 304 0.0 +17 220 0.0 +17 417 0.0 +17 175 0.0 +17 117 0.0 +17 264 0.0 +17 418 0.0 +9 17 0.0 +17 271 0.0 +17 138 0.0 +17 174 0.0 +17 305 0.0 +17 64 0.0 +17 392 0.0 +17 156 0.0 +17 282 0.0 +17 419 0.0 +17 22 0.0 +17 81 0.0 +17 176 0.0 +17 80 0.0 +17 178 0.0 +17 177 0.0 +17 197 0.0 +17 363 0.0 +17 303 0.0 +17 31 0.0 +17 118 0.0 +17 129 0.0 +6 17 0.0 +17 127 0.0 +17 30 0.0 +17 18 0.0 +17 133 0.0 +17 130 0.0 +17 124 0.0 +17 131 0.0 +17 122 0.0 +8 17 0.0 +17 120 0.0 +17 119 0.0 +5 17 0.0 +17 126 0.0 +17 125 0.0 +17 28 0.0 +17 32 0.0 +17 34 0.0 +7 17 0.0 +17 128 0.0 +17 132 0.0 +17 123 0.0 +17 121 0.0 +246 247 0.0 +40 246 0.0 +246 326 0.0 +296 420 0.0 +238 370 0.0 +399 421 0.0 +239 421 0.0 +343 421 0.0 +18 185 0.0 +185 409 0.0 +185 304 0.0 +185 422 0.0 +104 185 0.0 +185 254 0.0 +185 339 0.0 +181 185 0.0 +105 185 0.0 +401 423 0.0 +18 401 0.0 +424 425 0.0 +145 426 0.0 426 427 0.0 -426 428 0.0 -426 429 0.0 -405 426 0.0 -426 430 0.0 -359 362 0.0 -113 362 0.0 -115 362 0.0 +121 396 0.0 +121 258 0.0 +121 225 0.0 +121 428 0.0 +43 121 0.0 +121 429 0.0 +121 415 0.0 +121 213 0.0 +71 121 0.0 +121 411 0.0 +121 220 0.0 +41 121 0.0 +121 408 0.0 +121 161 0.0 +18 121 0.0 +121 138 0.0 +121 211 0.0 +121 166 0.0 +42 121 0.0 +121 276 0.0 +40 121 0.0 +117 121 0.0 +121 175 0.0 +64 121 0.0 +114 121 0.0 +121 174 0.0 +121 264 0.0 +121 176 0.0 +121 177 0.0 +121 178 0.0 +121 123 0.0 +31 121 0.0 +118 121 0.0 +121 129 0.0 +121 133 0.0 +5 121 0.0 +121 126 0.0 +35 121 0.0 +119 121 0.0 +30 121 0.0 +121 122 0.0 +120 121 0.0 +8 121 0.0 +121 131 0.0 +121 124 0.0 +121 127 0.0 +121 130 0.0 +121 132 0.0 +34 121 0.0 +121 128 0.0 +7 121 0.0 +28 121 0.0 +32 121 0.0 +6 121 0.0 +121 125 0.0 +427 430 0.0 +18 300 0.0 +263 300 0.0 +285 288 0.0 +285 287 0.0 +285 286 0.0 +285 289 0.0 +81 285 0.0 +271 285 0.0 +322 346 0.0 +346 348 0.0 +284 346 0.0 +346 349 0.0 +346 385 0.0 +191 387 0.0 +339 431 0.0 431 432 0.0 +388 433 0.0 433 434 0.0 -12 236 0.0 -205 236 0.0 -91 236 0.0 -109 236 0.0 -19 236 0.0 -42 236 0.0 -236 435 0.0 -90 236 0.0 -15 236 0.0 -85 236 0.0 -185 236 0.0 -97 236 0.0 -95 236 0.0 -105 236 0.0 -13 236 0.0 -99 236 0.0 -235 236 0.0 -92 236 0.0 -14 236 0.0 -17 236 0.0 -16 236 0.0 -148 236 0.0 -86 236 0.0 -89 236 0.0 -83 236 0.0 -84 236 0.0 -152 236 0.0 -153 236 0.0 -149 236 0.0 -138 140 0.0 -138 139 0.0 -138 143 0.0 -294 323 0.0 -126 294 0.0 -294 354 0.0 -133 294 0.0 -294 436 0.0 -3 168 0.0 -3 437 0.0 +433 435 0.0 +200 436 0.0 +198 200 0.0 +199 200 0.0 +195 437 0.0 +41 438 0.0 +42 124 0.0 +28 42 0.0 +34 42 0.0 +42 89 0.0 +8 42 0.0 +32 42 0.0 +42 64 0.0 +7 42 0.0 +42 67 0.0 +42 119 0.0 +42 178 0.0 +42 120 0.0 +42 213 0.0 +42 71 0.0 +30 42 0.0 +42 327 0.0 +42 211 0.0 +42 329 0.0 +42 130 0.0 +42 264 0.0 +42 328 0.0 +42 286 0.0 +5 42 0.0 +42 398 0.0 +42 166 0.0 +6 42 0.0 +42 138 0.0 +42 132 0.0 +42 131 0.0 +42 275 0.0 +42 127 0.0 +42 122 0.0 +40 42 0.0 +42 51 0.0 +42 43 0.0 +41 42 0.0 +59 367 0.0 +144 367 0.0 +91 435 0.0 +439 440 0.0 +356 439 0.0 +31 264 0.0 +166 264 0.0 +30 264 0.0 +41 264 0.0 +71 264 0.0 +8 264 0.0 +132 264 0.0 +264 270 0.0 +6 264 0.0 +131 264 0.0 +130 264 0.0 +5 264 0.0 +40 264 0.0 +211 264 0.0 +264 276 0.0 +127 264 0.0 +7 264 0.0 +125 264 0.0 +124 264 0.0 +119 264 0.0 +120 264 0.0 +32 264 0.0 +28 264 0.0 +174 264 0.0 +34 264 0.0 +122 264 0.0 +178 264 0.0 +176 264 0.0 +177 264 0.0 +160 165 0.0 +161 165 0.0 +163 165 0.0 +263 441 0.0 +263 418 0.0 +263 404 0.0 +18 263 0.0 +263 442 0.0 +111 263 0.0 +13 24 0.0 +24 191 0.0 +24 115 0.0 +24 385 0.0 +23 24 0.0 +443 444 0.0 +41 178 0.0 +41 71 0.0 +41 120 0.0 +41 127 0.0 +41 286 0.0 +5 41 0.0 +41 211 0.0 +41 131 0.0 +41 327 0.0 +41 174 0.0 +6 41 0.0 +41 329 0.0 +41 398 0.0 +41 276 0.0 +41 132 0.0 +41 166 0.0 +41 328 0.0 +41 145 0.0 +41 122 0.0 +41 138 0.0 +41 275 0.0 +40 41 0.0 +41 51 0.0 +41 43 0.0 +445 446 0.0 +325 445 0.0 +240 445 0.0 +445 447 0.0 +336 445 0.0 +425 448 0.0 +8 449 0.0 +40 449 0.0 +30 35 0.0 +28 35 0.0 +35 114 0.0 +35 127 0.0 +31 35 0.0 +5 35 0.0 +6 35 0.0 +32 35 0.0 +7 35 0.0 +34 35 0.0 +8 35 0.0 +100 450 0.0 +101 450 0.0 +381 450 0.0 +89 287 0.0 +34 67 0.0 +34 71 0.0 +34 211 0.0 +34 161 0.0 +34 429 0.0 +34 40 0.0 +34 258 0.0 +34 225 0.0 +34 408 0.0 +34 276 0.0 +18 34 0.0 +34 166 0.0 +34 142 0.0 +34 451 0.0 +34 117 0.0 +34 114 0.0 +34 175 0.0 +34 174 0.0 +34 417 0.0 +34 176 0.0 +34 177 0.0 +34 178 0.0 +9 34 0.0 +34 138 0.0 +31 34 0.0 +34 118 0.0 +34 64 0.0 +34 120 0.0 +8 34 0.0 +34 122 0.0 +30 34 0.0 +34 127 0.0 +34 130 0.0 +34 131 0.0 +34 124 0.0 +34 126 0.0 +5 34 0.0 +34 119 0.0 +6 34 0.0 +34 125 0.0 +34 129 0.0 +34 132 0.0 +34 123 0.0 +32 34 0.0 +28 34 0.0 +34 128 0.0 +34 133 0.0 +7 34 0.0 +313 395 0.0 +161 164 0.0 +160 164 0.0 +163 164 0.0 +452 453 0.0 +452 454 0.0 +378 452 0.0 +138 452 0.0 +62 452 0.0 +64 452 0.0 +452 455 0.0 +456 457 0.0 +117 458 0.0 +100 458 0.0 +60 458 0.0 +370 458 0.0 +145 458 0.0 +459 460 0.0 +304 459 0.0 +461 462 0.0 +111 463 0.0 +111 147 0.0 +18 400 0.0 +241 400 0.0 +325 335 0.0 +335 447 0.0 +240 335 0.0 +335 336 0.0 +181 409 0.0 +83 181 0.0 +18 181 0.0 +181 304 0.0 +181 211 0.0 +67 181 0.0 +80 181 0.0 +81 181 0.0 +105 181 0.0 +104 181 0.0 +58 464 0.0 +370 464 0.0 +464 465 0.0 +464 466 0.0 +60 464 0.0 +325 446 0.0 +446 447 0.0 +336 446 0.0 +80 240 0.0 +80 379 0.0 +52 80 0.0 +80 83 0.0 +80 317 0.0 +80 336 0.0 +80 377 0.0 +80 84 0.0 +80 273 0.0 +80 320 0.0 +80 467 0.0 +80 394 0.0 +80 282 0.0 +80 95 0.0 +80 378 0.0 +80 220 0.0 +80 415 0.0 +80 104 0.0 +80 271 0.0 +80 468 0.0 +18 80 0.0 +80 393 0.0 +80 81 0.0 +80 392 0.0 +18 414 0.0 +154 279 0.0 +197 279 0.0 +155 279 0.0 +156 279 0.0 +279 418 0.0 +279 286 0.0 +18 279 0.0 +109 279 0.0 +279 416 0.0 +18 301 0.0 +117 210 0.0 +117 118 0.0 +32 117 0.0 +117 122 0.0 +117 125 0.0 +117 120 0.0 +117 123 0.0 +31 117 0.0 +117 119 0.0 +117 124 0.0 +5 117 0.0 +28 117 0.0 +117 133 0.0 +117 128 0.0 +30 117 0.0 +117 132 0.0 +117 130 0.0 +7 117 0.0 +8 117 0.0 +6 117 0.0 +117 126 0.0 +117 129 0.0 +117 127 0.0 +117 131 0.0 +116 117 0.0 +381 419 0.0 +469 470 0.0 +296 469 0.0 +469 471 0.0 +405 472 0.0 +403 472 0.0 +472 473 0.0 +472 474 0.0 +472 475 0.0 +105 272 0.0 +139 272 0.0 +272 317 0.0 +217 272 0.0 +272 273 0.0 +272 318 0.0 +476 477 0.0 +100 145 0.0 +100 336 0.0 +100 135 0.0 +60 100 0.0 +100 460 0.0 +18 273 0.0 +240 273 0.0 +81 273 0.0 +217 273 0.0 +273 317 0.0 +273 318 0.0 +9 453 0.0 +9 270 0.0 +9 340 0.0 +9 10 0.0 +9 131 0.0 +4 9 0.0 +3 9 0.0 +9 451 0.0 +9 28 0.0 +9 125 0.0 +9 120 0.0 +9 32 0.0 +9 119 0.0 +9 64 0.0 +9 417 0.0 +9 138 0.0 +478 479 0.0 +478 480 0.0 +128 396 0.0 +43 128 0.0 +128 408 0.0 +128 166 0.0 +128 225 0.0 +128 481 0.0 +18 128 0.0 +64 128 0.0 +116 128 0.0 +3 128 0.0 +114 128 0.0 +128 276 0.0 +118 128 0.0 +31 128 0.0 +127 128 0.0 +128 130 0.0 +124 128 0.0 +128 131 0.0 +122 128 0.0 +8 128 0.0 +120 128 0.0 +30 128 0.0 +119 128 0.0 +5 128 0.0 +126 128 0.0 +6 128 0.0 +125 128 0.0 +28 128 0.0 +32 128 0.0 +128 133 0.0 +7 128 0.0 +128 129 0.0 +128 132 0.0 +123 128 0.0 +68 215 0.0 +68 104 0.0 +68 268 0.0 +68 131 0.0 +68 75 0.0 +68 233 0.0 +68 210 0.0 +68 212 0.0 +66 68 0.0 +64 68 0.0 +68 217 0.0 +254 482 0.0 +18 254 0.0 +252 254 0.0 +254 340 0.0 +254 339 0.0 +247 352 0.0 +423 483 0.0 +197 423 0.0 +404 423 0.0 +423 484 0.0 +75 423 0.0 +253 485 0.0 +305 340 0.0 +18 340 0.0 +119 340 0.0 +340 417 0.0 +64 340 0.0 +241 340 0.0 +138 340 0.0 +289 340 0.0 +339 340 0.0 +138 328 0.0 +275 328 0.0 +327 328 0.0 +328 329 0.0 +18 398 0.0 +56 318 0.0 +318 486 0.0 +240 318 0.0 +317 318 0.0 +318 392 0.0 +318 393 0.0 +217 318 0.0 +18 188 0.0 +188 487 0.0 +188 342 0.0 +188 344 0.0 +188 343 0.0 +52 188 0.0 +403 411 0.0 +40 403 0.0 +18 403 0.0 +403 405 0.0 +4 270 0.0 +176 270 0.0 +119 270 0.0 +174 270 0.0 +122 270 0.0 +32 270 0.0 +213 270 0.0 +67 270 0.0 +6 270 0.0 +64 270 0.0 +215 270 0.0 +209 270 0.0 +127 270 0.0 +131 270 0.0 +211 270 0.0 +178 270 0.0 +270 453 0.0 +138 270 0.0 +71 270 0.0 +410 444 0.0 +444 488 0.0 +444 489 0.0 +444 490 0.0 +324 491 0.0 +163 324 0.0 +324 379 0.0 +106 324 0.0 +28 429 0.0 +18 28 0.0 +28 166 0.0 +28 211 0.0 +28 175 0.0 +28 213 0.0 +28 40 0.0 +28 408 0.0 +28 43 0.0 +28 276 0.0 +28 114 0.0 +28 225 0.0 +28 174 0.0 +28 177 0.0 +28 417 0.0 +28 176 0.0 +28 178 0.0 +28 118 0.0 +28 31 0.0 +28 138 0.0 +28 64 0.0 +28 123 0.0 +28 129 0.0 +6 28 0.0 +28 130 0.0 +28 127 0.0 +28 30 0.0 +7 28 0.0 +28 126 0.0 +28 32 0.0 +28 133 0.0 +28 132 0.0 +28 125 0.0 +28 119 0.0 +5 28 0.0 +28 131 0.0 +28 124 0.0 +28 122 0.0 +28 120 0.0 +8 28 0.0 +287 492 0.0 +284 287 0.0 +287 288 0.0 +287 289 0.0 +479 493 0.0 +269 494 0.0 +51 269 0.0 +269 393 0.0 +219 269 0.0 +495 496 0.0 +40 497 0.0 +6 497 0.0 +7 497 0.0 +305 498 0.0 +303 498 0.0 +499 500 0.0 +337 499 0.0 +84 383 0.0 +81 84 0.0 +83 84 0.0 +84 138 0.0 +64 84 0.0 +275 329 0.0 +275 327 0.0 +274 275 0.0 +138 275 0.0 +303 501 0.0 +501 502 0.0 +501 503 0.0 +501 504 0.0 +51 501 0.0 +67 132 0.0 +67 286 0.0 +64 67 0.0 +67 201 0.0 +67 217 0.0 +67 206 0.0 +67 203 0.0 +67 210 0.0 +67 75 0.0 +52 67 0.0 +67 202 0.0 +67 205 0.0 +67 213 0.0 +67 207 0.0 +67 268 0.0 +67 209 0.0 +67 215 0.0 +67 71 0.0 +67 211 0.0 +313 325 0.0 +325 447 0.0 +325 336 0.0 +240 325 0.0 +325 393 0.0 +325 392 0.0 +83 325 0.0 +307 384 0.0 +383 384 0.0 +384 405 0.0 +224 369 0.0 +135 369 0.0 +369 505 0.0 +31 481 0.0 +7 481 0.0 +6 481 0.0 +5 481 0.0 +64 481 0.0 +129 481 0.0 +130 481 0.0 +138 481 0.0 +114 481 0.0 +127 481 0.0 +8 481 0.0 +3 481 0.0 +276 481 0.0 +190 343 0.0 +203 209 0.0 +203 268 0.0 +71 203 0.0 +203 206 0.0 +203 211 0.0 +203 210 0.0 +283 289 0.0 +239 506 0.0 +506 507 0.0 +392 468 0.0 +18 252 0.0 +239 507 0.0 +239 342 0.0 +18 176 0.0 +8 176 0.0 +138 176 0.0 +30 176 0.0 +6 176 0.0 +64 176 0.0 +127 176 0.0 +7 176 0.0 +118 176 0.0 +131 176 0.0 +176 276 0.0 +32 176 0.0 +175 176 0.0 +124 176 0.0 +125 176 0.0 +120 176 0.0 +119 176 0.0 +122 176 0.0 +176 178 0.0 +174 176 0.0 +176 177 0.0 +296 508 0.0 +296 509 0.0 +296 510 0.0 +296 511 0.0 +296 512 0.0 +296 513 0.0 +143 296 0.0 +296 514 0.0 +349 515 0.0 +192 515 0.0 +516 517 0.0 +81 95 0.0 +95 219 0.0 +71 95 0.0 +95 392 0.0 +95 393 0.0 +95 394 0.0 +386 518 0.0 +191 386 0.0 +427 519 0.0 +83 520 0.0 +81 394 0.0 +282 394 0.0 +222 372 0.0 +372 374 0.0 +224 372 0.0 +57 372 0.0 +135 372 0.0 +371 372 0.0 +60 372 0.0 +3 106 0.0 +3 213 0.0 +3 133 0.0 +3 10 0.0 +3 451 0.0 +3 417 0.0 +3 7 0.0 +3 31 0.0 +3 114 0.0 +3 129 0.0 +3 453 0.0 +3 64 0.0 +3 5 0.0 +3 6 0.0 3 4 0.0 -3 100 0.0 -438 439 0.0 -42 205 0.0 -185 205 0.0 -205 386 0.0 -83 205 0.0 -205 235 0.0 -114 205 0.0 -85 205 0.0 -117 205 0.0 -90 205 0.0 -153 205 0.0 -15 205 0.0 -48 205 0.0 -205 408 0.0 -12 205 0.0 -89 205 0.0 -19 205 0.0 -97 205 0.0 -205 314 0.0 -205 316 0.0 -95 205 0.0 -99 205 0.0 -205 315 0.0 -13 205 0.0 -84 205 0.0 -205 260 0.0 -109 205 0.0 -105 205 0.0 -29 205 0.0 -345 440 0.0 -440 441 0.0 -209 440 0.0 -440 442 0.0 -255 440 0.0 -242 440 0.0 -405 430 0.0 -405 428 0.0 +3 132 0.0 +3 127 0.0 +3 8 0.0 +3 138 0.0 +3 276 0.0 +3 130 0.0 +3 131 0.0 +330 521 0.0 +457 522 0.0 +236 457 0.0 +235 457 0.0 +457 523 0.0 +337 457 0.0 +195 377 0.0 +195 378 0.0 +195 330 0.0 +195 524 0.0 +83 195 0.0 +52 195 0.0 +378 525 0.0 +377 525 0.0 +336 525 0.0 +127 166 0.0 +127 178 0.0 +127 429 0.0 +127 408 0.0 +127 211 0.0 +4 127 0.0 +40 127 0.0 +18 127 0.0 +127 138 0.0 +127 145 0.0 +64 127 0.0 +116 127 0.0 +127 276 0.0 +118 127 0.0 +31 127 0.0 +123 127 0.0 +127 133 0.0 +125 127 0.0 +124 127 0.0 +127 132 0.0 +127 129 0.0 +7 127 0.0 +32 127 0.0 +6 127 0.0 +126 127 0.0 +5 127 0.0 +119 127 0.0 +30 127 0.0 +120 127 0.0 +8 127 0.0 +122 127 0.0 +127 131 0.0 +127 130 0.0 +405 411 0.0 +7 411 0.0 +303 411 0.0 +18 411 0.0 +122 411 0.0 +8 411 0.0 +60 411 0.0 +40 411 0.0 +303 305 0.0 +197 303 0.0 +109 303 0.0 +18 303 0.0 +303 418 0.0 +126 408 0.0 +125 408 0.0 +32 408 0.0 +124 408 0.0 +120 408 0.0 +130 408 0.0 +8 408 0.0 +5 408 0.0 +132 408 0.0 +6 408 0.0 +131 408 0.0 +119 408 0.0 +129 408 0.0 +123 408 0.0 +7 408 0.0 +30 408 0.0 +133 408 0.0 +32 220 0.0 +139 220 0.0 +18 220 0.0 +8 220 0.0 +81 220 0.0 +161 220 0.0 +220 282 0.0 +220 379 0.0 +43 211 0.0 +132 211 0.0 +211 526 0.0 +32 211 0.0 +211 286 0.0 +5 211 0.0 +211 266 0.0 +119 211 0.0 +64 211 0.0 +6 211 0.0 +211 350 0.0 +211 217 0.0 +40 211 0.0 +75 211 0.0 +207 211 0.0 +210 211 0.0 +205 211 0.0 +122 211 0.0 +52 211 0.0 +202 211 0.0 +211 268 0.0 +209 211 0.0 +211 213 0.0 +211 215 0.0 +71 211 0.0 +4 10 0.0 +6 10 0.0 +5 10 0.0 +7 10 0.0 +8 10 0.0 +161 163 0.0 +163 257 0.0 +163 473 0.0 +160 163 0.0 +8 221 0.0 +7 221 0.0 +160 221 0.0 +161 221 0.0 +145 219 0.0 +219 415 0.0 +219 271 0.0 +81 219 0.0 +219 304 0.0 +83 219 0.0 +51 219 0.0 +219 393 0.0 +219 392 0.0 +219 494 0.0 +52 219 0.0 +122 523 0.0 +197 416 0.0 +197 363 0.0 +197 418 0.0 +197 436 0.0 +197 199 0.0 +197 198 0.0 +18 197 0.0 +155 399 0.0 +154 399 0.0 +156 399 0.0 +18 399 0.0 +120 350 0.0 +210 350 0.0 +139 350 0.0 +215 350 0.0 +268 350 0.0 +213 350 0.0 +75 350 0.0 +62 350 0.0 +527 528 0.0 +213 529 0.0 +6 258 0.0 +4 6 0.0 +6 214 0.0 +6 429 0.0 +6 177 0.0 +6 213 0.0 +6 178 0.0 +6 161 0.0 +6 142 0.0 +6 18 0.0 +6 174 0.0 +6 166 0.0 +6 138 0.0 +6 40 0.0 +6 64 0.0 +6 114 0.0 +6 116 0.0 +6 123 0.0 +6 118 0.0 +6 276 0.0 +6 31 0.0 +6 133 0.0 +6 125 0.0 +6 124 0.0 +6 129 0.0 +6 132 0.0 +6 32 0.0 +6 7 0.0 +6 120 0.0 +6 8 0.0 +6 122 0.0 +6 30 0.0 +6 130 0.0 +6 131 0.0 +6 126 0.0 +5 6 0.0 +6 119 0.0 +18 129 0.0 +129 174 0.0 +64 129 0.0 +114 129 0.0 +116 129 0.0 +31 129 0.0 +129 276 0.0 +118 129 0.0 +129 133 0.0 +30 129 0.0 +123 129 0.0 +124 129 0.0 +119 129 0.0 +125 129 0.0 +5 129 0.0 +126 129 0.0 +129 130 0.0 +129 131 0.0 +122 129 0.0 +8 129 0.0 +120 129 0.0 +32 129 0.0 +7 129 0.0 +129 132 0.0 +52 530 0.0 +71 119 0.0 +71 286 0.0 +43 71 0.0 +71 418 0.0 +64 71 0.0 +71 75 0.0 +71 120 0.0 +71 217 0.0 +71 122 0.0 +71 202 0.0 +40 71 0.0 +71 207 0.0 +52 71 0.0 +71 213 0.0 +71 268 0.0 +71 205 0.0 +71 215 0.0 +71 209 0.0 +130 531 0.0 +4 531 0.0 +193 532 0.0 +132 410 0.0 +225 410 0.0 +409 410 0.0 +410 533 0.0 +410 484 0.0 +410 534 0.0 +18 410 0.0 +133 410 0.0 +410 412 0.0 +304 410 0.0 +105 422 0.0 +104 105 0.0 +57 535 0.0 +536 537 0.0 +215 418 0.0 +215 538 0.0 +72 215 0.0 +215 286 0.0 +202 215 0.0 +215 268 0.0 +205 215 0.0 +207 215 0.0 +213 215 0.0 +209 215 0.0 +210 215 0.0 +539 540 0.0 +418 526 0.0 +209 526 0.0 +167 245 0.0 +236 245 0.0 +235 245 0.0 +12 245 0.0 +40 245 0.0 +22 245 0.0 +16 245 0.0 +19 245 0.0 +20 245 0.0 +317 541 0.0 +81 317 0.0 +282 317 0.0 +317 542 0.0 +172 309 0.0 +309 543 0.0 +309 544 0.0 +309 545 0.0 +155 407 0.0 +155 157 0.0 +155 404 0.0 +155 313 0.0 +155 304 0.0 +155 500 0.0 +155 193 0.0 +155 428 0.0 +155 528 0.0 +155 415 0.0 +155 397 0.0 +18 155 0.0 +155 156 0.0 +20 167 0.0 +20 502 0.0 +20 235 0.0 +20 236 0.0 +20 191 0.0 +18 20 0.0 12 20 0.0 -20 85 0.0 -9 20 0.0 -10 20 0.0 -13 20 0.0 -20 97 0.0 -17 20 0.0 -14 20 0.0 16 20 0.0 -15 20 0.0 +20 22 0.0 19 20 0.0 -68 443 0.0 -16 41 0.0 -16 29 0.0 -16 435 0.0 -16 111 0.0 -16 133 0.0 -16 235 0.0 -16 151 0.0 -16 389 0.0 -16 444 0.0 -16 343 0.0 -9 16 0.0 -16 148 0.0 -16 124 0.0 -16 149 0.0 -16 152 0.0 -16 109 0.0 -10 16 0.0 -16 116 0.0 -16 153 0.0 -16 82 0.0 -15 16 0.0 -16 83 0.0 -16 89 0.0 -16 99 0.0 -16 92 0.0 -16 98 0.0 -13 16 0.0 -16 96 0.0 -16 85 0.0 -16 94 0.0 -16 91 0.0 -16 97 0.0 -16 86 0.0 -16 95 0.0 -16 90 0.0 -16 84 0.0 -16 93 0.0 -16 19 0.0 -12 16 0.0 -14 16 0.0 -16 17 0.0 -306 445 0.0 -139 141 0.0 -140 141 0.0 -141 143 0.0 -189 446 0.0 -23 447 0.0 -116 447 0.0 -109 447 0.0 -389 447 0.0 -163 397 0.0 -245 448 0.0 -363 448 0.0 -38 448 0.0 -117 448 0.0 -111 449 0.0 -449 450 0.0 -388 449 0.0 -84 282 0.0 -282 386 0.0 -224 282 0.0 -451 452 0.0 -119 436 0.0 -322 442 0.0 -255 322 0.0 -242 322 0.0 -72 161 0.0 -29 72 0.0 -72 453 0.0 -53 72 0.0 -72 220 0.0 -72 242 0.0 -72 180 0.0 -54 72 0.0 -72 133 0.0 -72 347 0.0 -42 72 0.0 -72 185 0.0 -41 72 0.0 -72 190 0.0 -72 388 0.0 -72 383 0.0 -71 72 0.0 -72 157 0.0 -245 454 0.0 -363 454 0.0 -454 455 0.0 -454 456 0.0 -38 454 0.0 -457 458 0.0 -255 441 0.0 -441 442 0.0 -242 441 0.0 -256 270 0.0 -42 256 0.0 -53 256 0.0 -249 256 0.0 -256 367 0.0 -254 256 0.0 -459 460 0.0 -269 386 0.0 -133 269 0.0 -269 385 0.0 -269 353 0.0 -269 352 0.0 -100 269 0.0 -269 354 0.0 -269 351 0.0 -269 300 0.0 -133 295 0.0 -97 133 0.0 -133 247 0.0 -12 133 0.0 -10 133 0.0 -9 133 0.0 -98 133 0.0 -94 133 0.0 -86 133 0.0 -82 133 0.0 -19 133 0.0 -95 133 0.0 -90 133 0.0 -91 133 0.0 -83 133 0.0 -17 133 0.0 -89 133 0.0 -85 133 0.0 -99 133 0.0 -96 133 0.0 -93 133 0.0 -133 379 0.0 -48 133 0.0 -133 380 0.0 -133 381 0.0 -133 382 0.0 -133 383 0.0 -133 384 0.0 -133 385 0.0 -133 220 0.0 -133 370 0.0 -133 149 0.0 -92 133 0.0 -133 165 0.0 -133 265 0.0 -133 386 0.0 -133 330 0.0 -133 360 0.0 -13 133 0.0 +388 434 0.0 +388 435 0.0 +81 282 0.0 +52 282 0.0 +282 392 0.0 +18 282 0.0 +160 473 0.0 +160 161 0.0 +378 546 0.0 +377 546 0.0 +256 257 0.0 +305 547 0.0 +135 505 0.0 +371 505 0.0 +14 337 0.0 +236 337 0.0 +337 548 0.0 +337 549 0.0 +235 337 0.0 +371 427 0.0 +368 371 0.0 +57 371 0.0 +371 550 0.0 +371 374 0.0 +224 371 0.0 +60 371 0.0 +222 371 0.0 +135 371 0.0 +225 371 0.0 +207 286 0.0 +206 207 0.0 +202 207 0.0 +207 210 0.0 +205 207 0.0 +207 213 0.0 +207 217 0.0 +40 207 0.0 +133 222 0.0 +18 133 0.0 +43 133 0.0 +114 133 0.0 +64 133 0.0 +58 133 0.0 +133 225 0.0 +116 133 0.0 +118 133 0.0 +133 276 0.0 +31 133 0.0 +119 133 0.0 +30 133 0.0 +32 133 0.0 +125 133 0.0 7 133 0.0 -133 353 0.0 -133 388 0.0 -133 352 0.0 -133 300 0.0 -133 387 0.0 -100 133 0.0 -133 461 0.0 -15 133 0.0 -133 351 0.0 -105 133 0.0 -133 354 0.0 -133 301 0.0 -133 254 0.0 -133 135 0.0 -133 209 0.0 -130 133 0.0 -133 390 0.0 -133 160 0.0 -133 213 0.0 -133 306 0.0 -133 163 0.0 -133 392 0.0 -133 393 0.0 -53 133 0.0 -133 391 0.0 -133 284 0.0 -133 264 0.0 -132 133 0.0 -133 232 0.0 -133 394 0.0 131 133 0.0 -29 343 0.0 -187 343 0.0 -17 343 0.0 -98 343 0.0 -90 343 0.0 -96 343 0.0 -82 343 0.0 -15 343 0.0 -84 343 0.0 -10 343 0.0 -12 343 0.0 -89 343 0.0 -94 343 0.0 -14 343 0.0 -86 343 0.0 -83 343 0.0 -99 343 0.0 -93 343 0.0 -13 343 0.0 -91 343 0.0 -95 343 0.0 -97 343 0.0 -92 343 0.0 -19 343 0.0 -343 462 0.0 -78 463 0.0 -307 464 0.0 -303 430 0.0 -303 428 0.0 -303 427 0.0 -303 402 0.0 -303 403 0.0 -303 460 0.0 -303 465 0.0 -332 466 0.0 -332 467 0.0 -332 381 0.0 -332 382 0.0 -332 468 0.0 -332 469 0.0 -71 161 0.0 -161 244 0.0 -161 309 0.0 -160 161 0.0 -161 250 0.0 -273 412 0.0 -276 412 0.0 -67 117 0.0 -67 102 0.0 -67 363 0.0 -38 67 0.0 -67 242 0.0 -67 450 0.0 -53 160 0.0 -160 190 0.0 -160 309 0.0 -160 250 0.0 -428 470 0.0 -336 428 0.0 -428 429 0.0 -428 471 0.0 -427 428 0.0 -428 430 0.0 -402 428 0.0 -95 124 0.0 -124 472 0.0 -124 265 0.0 -124 473 0.0 -124 474 0.0 -124 151 0.0 -124 152 0.0 -124 475 0.0 -89 124 0.0 -124 476 0.0 -124 477 0.0 -124 424 0.0 -23 124 0.0 -17 124 0.0 -124 435 0.0 -83 124 0.0 -116 124 0.0 -92 124 0.0 -14 124 0.0 -124 444 0.0 -109 124 0.0 -478 479 0.0 -478 480 0.0 -93 111 0.0 -93 424 0.0 -93 462 0.0 -93 149 0.0 -93 116 0.0 -9 93 0.0 -93 235 0.0 -10 93 0.0 -82 93 0.0 -92 93 0.0 -91 93 0.0 -93 94 0.0 -93 96 0.0 -85 93 0.0 -93 98 0.0 -13 93 0.0 -83 93 0.0 -15 93 0.0 -93 99 0.0 -89 93 0.0 -19 93 0.0 -12 93 0.0 -17 93 0.0 -14 93 0.0 -93 97 0.0 -84 93 0.0 -90 93 0.0 -86 93 0.0 -93 95 0.0 -187 189 0.0 -182 189 0.0 -189 190 0.0 -116 189 0.0 -220 383 0.0 -220 379 0.0 -220 481 0.0 -220 370 0.0 -220 265 0.0 -7 204 0.0 -204 482 0.0 -391 483 0.0 -483 484 0.0 -393 485 0.0 -57 485 0.0 -105 265 0.0 -265 444 0.0 -116 265 0.0 -83 265 0.0 -109 265 0.0 -211 265 0.0 -213 265 0.0 -265 370 0.0 -315 316 0.0 -190 250 0.0 -250 309 0.0 -170 486 0.0 -163 333 0.0 -163 291 0.0 -163 218 0.0 -163 487 0.0 -7 163 0.0 -360 382 0.0 -105 382 0.0 -381 382 0.0 -90 435 0.0 -324 435 0.0 -435 477 0.0 -180 435 0.0 -340 435 0.0 -188 435 0.0 -153 435 0.0 -148 435 0.0 -41 435 0.0 -114 435 0.0 -42 435 0.0 -85 435 0.0 -185 435 0.0 -91 435 0.0 -13 435 0.0 -83 435 0.0 -17 435 0.0 -116 435 0.0 -109 435 0.0 -439 488 0.0 -365 439 0.0 -80 371 0.0 -80 143 0.0 -14 185 0.0 -14 105 0.0 -14 102 0.0 -14 151 0.0 -14 198 0.0 -14 29 0.0 -14 444 0.0 -14 389 0.0 -14 149 0.0 -9 14 0.0 -14 235 0.0 -14 148 0.0 -14 152 0.0 -10 14 0.0 -14 153 0.0 -14 109 0.0 -14 82 0.0 -14 96 0.0 -14 116 0.0 -13 14 0.0 -14 98 0.0 -14 85 0.0 -14 94 0.0 -14 91 0.0 -14 92 0.0 -14 89 0.0 -14 99 0.0 +120 133 0.0 +122 133 0.0 +5 133 0.0 +123 133 0.0 +132 133 0.0 +124 133 0.0 +130 133 0.0 +8 133 0.0 +126 133 0.0 +156 407 0.0 +156 313 0.0 +156 157 0.0 +156 500 0.0 +156 404 0.0 +156 528 0.0 +156 193 0.0 +156 304 0.0 +156 428 0.0 +156 415 0.0 +156 397 0.0 +18 156 0.0 +278 286 0.0 +166 551 0.0 +258 551 0.0 +154 407 0.0 +18 407 0.0 +150 407 0.0 +304 407 0.0 +407 552 0.0 +58 406 0.0 +18 406 0.0 +147 258 0.0 +147 166 0.0 +18 393 0.0 +392 393 0.0 +271 393 0.0 +393 553 0.0 +393 467 0.0 +150 393 0.0 +393 542 0.0 +58 466 0.0 +58 60 0.0 +58 554 0.0 +60 465 0.0 +154 404 0.0 +18 404 0.0 +404 484 0.0 +313 404 0.0 +18 402 0.0 +212 217 0.0 +217 555 0.0 +43 217 0.0 +206 217 0.0 +213 217 0.0 +210 217 0.0 +217 358 0.0 +217 233 0.0 +64 217 0.0 +66 217 0.0 +214 217 0.0 +5 258 0.0 +7 258 0.0 +8 258 0.0 +32 258 0.0 +258 490 0.0 +258 556 0.0 +258 489 0.0 +166 258 0.0 +489 557 0.0 +489 556 0.0 +489 490 0.0 +40 558 0.0 +545 559 0.0 +286 418 0.0 +213 286 0.0 +125 286 0.0 +75 286 0.0 +18 286 0.0 +307 342 0.0 +307 560 0.0 +462 475 0.0 +5 178 0.0 +178 453 0.0 +132 178 0.0 +8 178 0.0 +138 178 0.0 +30 178 0.0 +64 178 0.0 +118 178 0.0 +116 178 0.0 +131 178 0.0 +7 178 0.0 +124 178 0.0 +32 178 0.0 +125 178 0.0 +120 178 0.0 +119 178 0.0 +122 178 0.0 +177 178 0.0 +174 178 0.0 +175 178 0.0 +157 561 0.0 +154 157 0.0 +18 157 0.0 +201 268 0.0 +339 379 0.0 +339 409 0.0 +18 339 0.0 +339 562 0.0 +563 564 0.0 +312 563 0.0 +15 66 0.0 14 15 0.0 -14 83 0.0 -12 14 0.0 -14 17 0.0 -14 19 0.0 -14 86 0.0 -14 95 0.0 -14 90 0.0 -14 84 0.0 -14 97 0.0 -272 489 0.0 -272 273 0.0 -272 276 0.0 -479 490 0.0 -233 239 0.0 -239 276 0.0 -239 255 0.0 -232 239 0.0 -239 491 0.0 -35 239 0.0 -213 239 0.0 -239 492 0.0 -239 242 0.0 -239 244 0.0 -254 354 0.0 -53 254 0.0 -301 493 0.0 -300 493 0.0 -57 276 0.0 -53 57 0.0 -54 57 0.0 -57 386 0.0 -260 261 0.0 -460 494 0.0 -232 495 0.0 -247 495 0.0 -24 300 0.0 -24 126 0.0 -24 475 0.0 -24 496 0.0 -24 35 0.0 -23 24 0.0 -7 24 0.0 -41 95 0.0 -41 386 0.0 -41 99 0.0 -41 190 0.0 -41 497 0.0 -41 241 0.0 -41 116 0.0 -41 46 0.0 -41 187 0.0 -41 340 0.0 -41 184 0.0 -41 243 0.0 -41 183 0.0 -41 114 0.0 -41 180 0.0 -41 188 0.0 -41 42 0.0 -41 185 0.0 -255 442 0.0 -209 255 0.0 -255 492 0.0 -242 255 0.0 -54 255 0.0 -444 473 0.0 -109 473 0.0 -424 473 0.0 -427 471 0.0 -165 291 0.0 -339 378 0.0 -186 378 0.0 -187 378 0.0 -157 383 0.0 -383 388 0.0 -370 383 0.0 -71 383 0.0 -274 276 0.0 -498 499 0.0 -152 387 0.0 -152 238 0.0 -82 152 0.0 -19 152 0.0 -12 152 0.0 -152 408 0.0 -15 152 0.0 -152 477 0.0 -85 152 0.0 -13 152 0.0 -95 152 0.0 -109 152 0.0 -152 235 0.0 -151 152 0.0 -17 152 0.0 -92 152 0.0 -86 152 0.0 -89 152 0.0 -83 152 0.0 -84 152 0.0 -148 152 0.0 -152 153 0.0 -149 152 0.0 -500 501 0.0 -460 502 0.0 -460 503 0.0 -460 504 0.0 -108 460 0.0 -54 460 0.0 -460 465 0.0 -437 505 0.0 -65 247 0.0 -65 185 0.0 -53 65 0.0 -42 65 0.0 -65 244 0.0 -65 248 0.0 -153 238 0.0 -148 238 0.0 -17 238 0.0 -86 238 0.0 -402 403 0.0 -168 376 0.0 -410 506 0.0 -54 507 0.0 -53 248 0.0 -247 248 0.0 -248 264 0.0 -83 424 0.0 -424 463 0.0 -42 424 0.0 -9 424 0.0 -10 424 0.0 -15 424 0.0 -114 424 0.0 -94 424 0.0 -91 424 0.0 -90 424 0.0 -97 424 0.0 -19 424 0.0 -424 475 0.0 -99 424 0.0 -13 424 0.0 -95 424 0.0 -424 474 0.0 -85 424 0.0 -424 508 0.0 -116 424 0.0 -424 444 0.0 -23 424 0.0 -235 424 0.0 -109 424 0.0 -424 477 0.0 -317 509 0.0 -83 185 0.0 -83 111 0.0 -83 151 0.0 -83 389 0.0 -83 444 0.0 -9 83 0.0 -83 149 0.0 -83 148 0.0 -83 116 0.0 -10 83 0.0 -83 109 0.0 -83 153 0.0 -83 96 0.0 -82 83 0.0 -83 92 0.0 -83 91 0.0 -83 94 0.0 -83 85 0.0 -83 98 0.0 -13 83 0.0 -15 83 0.0 -83 99 0.0 -83 89 0.0 -19 83 0.0 -17 83 0.0 -12 83 0.0 -83 97 0.0 -83 84 0.0 -83 90 0.0 -83 95 0.0 -83 86 0.0 -400 510 0.0 -400 511 0.0 -206 400 0.0 -278 400 0.0 -242 512 0.0 -512 513 0.0 -512 514 0.0 -85 185 0.0 -29 85 0.0 -85 117 0.0 -85 477 0.0 -85 105 0.0 -85 153 0.0 -85 116 0.0 -85 109 0.0 -9 85 0.0 -10 85 0.0 -85 96 0.0 -85 235 0.0 -82 85 0.0 -15 85 0.0 -85 99 0.0 -85 89 0.0 -85 92 0.0 -13 85 0.0 -85 98 0.0 -85 91 0.0 -85 94 0.0 -85 97 0.0 -85 90 0.0 -85 95 0.0 -85 86 0.0 -84 85 0.0 -19 85 0.0 -17 85 0.0 -12 85 0.0 -125 300 0.0 -300 360 0.0 -300 385 0.0 -300 301 0.0 -216 300 0.0 -100 300 0.0 -300 351 0.0 -300 352 0.0 -300 354 0.0 -300 353 0.0 -151 408 0.0 -84 408 0.0 -114 408 0.0 -153 408 0.0 -139 368 0.0 -53 368 0.0 -264 368 0.0 -185 241 0.0 -29 185 0.0 -95 185 0.0 -116 185 0.0 -97 185 0.0 -99 185 0.0 -13 185 0.0 -105 185 0.0 -185 240 0.0 -185 190 0.0 -46 185 0.0 -184 185 0.0 -84 185 0.0 -185 187 0.0 -7 185 0.0 -183 185 0.0 -180 185 0.0 -114 185 0.0 -185 243 0.0 -185 188 0.0 -42 185 0.0 -99 462 0.0 -91 462 0.0 -98 462 0.0 -95 462 0.0 -97 462 0.0 -19 462 0.0 -13 462 0.0 -143 195 0.0 -139 143 0.0 -140 143 0.0 -143 467 0.0 -194 247 0.0 -140 194 0.0 -139 194 0.0 -84 510 0.0 -174 352 0.0 -174 421 0.0 -174 175 0.0 -174 176 0.0 -7 323 0.0 -7 515 0.0 -7 516 0.0 -7 276 0.0 -7 517 0.0 -7 53 0.0 -7 242 0.0 -7 218 0.0 -7 305 0.0 -7 213 0.0 -7 165 0.0 -7 170 0.0 -7 306 0.0 -7 172 0.0 -7 244 0.0 -216 301 0.0 -132 390 0.0 -130 390 0.0 -131 390 0.0 -106 339 0.0 -339 340 0.0 -46 339 0.0 -230 339 0.0 -518 519 0.0 -518 520 0.0 -13 29 0.0 -13 105 0.0 -13 153 0.0 -13 109 0.0 -13 116 0.0 -13 148 0.0 -9 13 0.0 -10 13 0.0 -13 82 0.0 -13 96 0.0 -13 235 0.0 -13 98 0.0 -13 94 0.0 -13 91 0.0 -13 92 0.0 -13 89 0.0 -13 99 0.0 -13 15 0.0 -13 17 0.0 -12 13 0.0 -13 19 0.0 -13 95 0.0 -13 86 0.0 -13 90 0.0 -13 84 0.0 -13 97 0.0 -94 116 0.0 -94 148 0.0 -9 94 0.0 -94 235 0.0 -10 94 0.0 -94 96 0.0 -82 94 0.0 -91 94 0.0 -94 98 0.0 -92 94 0.0 -94 99 0.0 -89 94 0.0 -15 94 0.0 -17 94 0.0 -12 94 0.0 -19 94 0.0 -84 94 0.0 -90 94 0.0 -94 95 0.0 -86 94 0.0 -94 97 0.0 -29 42 0.0 -42 386 0.0 -42 116 0.0 -42 46 0.0 -42 84 0.0 -42 105 0.0 -42 190 0.0 -42 184 0.0 -42 187 0.0 -42 243 0.0 -42 183 0.0 -42 188 0.0 -42 114 0.0 -42 180 0.0 -384 484 0.0 -384 521 0.0 -384 522 0.0 -384 388 0.0 -384 387 0.0 -71 184 0.0 -44 188 0.0 -188 354 0.0 -188 244 0.0 -188 386 0.0 -188 340 0.0 -188 243 0.0 -187 188 0.0 -184 188 0.0 -180 188 0.0 -114 188 0.0 -183 188 0.0 -244 523 0.0 -180 241 0.0 -206 329 0.0 -2 329 0.0 -105 329 0.0 -329 330 0.0 -264 309 0.0 -53 309 0.0 -466 524 0.0 -132 233 0.0 -132 232 0.0 -130 132 0.0 -132 135 0.0 -132 461 0.0 +154 500 0.0 +193 500 0.0 +500 528 0.0 +205 213 0.0 +202 205 0.0 +124 205 0.0 +205 206 0.0 +139 205 0.0 +205 210 0.0 +12 16 0.0 +16 22 0.0 +16 19 0.0 +60 427 0.0 +288 565 0.0 +288 492 0.0 +284 288 0.0 +288 289 0.0 +18 418 0.0 +57 370 0.0 +57 222 0.0 +57 368 0.0 +57 266 0.0 +57 60 0.0 +57 145 0.0 +57 225 0.0 +57 224 0.0 +57 566 0.0 +57 135 0.0 +289 492 0.0 +131 486 0.0 +131 429 0.0 +131 166 0.0 +131 177 0.0 +131 417 0.0 +18 131 0.0 +40 131 0.0 +131 174 0.0 +131 175 0.0 +114 131 0.0 +131 138 0.0 +116 131 0.0 +131 276 0.0 +118 131 0.0 +31 131 0.0 +125 131 0.0 +32 131 0.0 +7 131 0.0 +123 131 0.0 131 132 0.0 -330 437 0.0 -206 330 0.0 -327 330 0.0 -168 330 0.0 -328 330 0.0 -2 330 0.0 -374 419 0.0 -374 420 0.0 -53 264 0.0 -140 323 0.0 -140 467 0.0 -139 140 0.0 -514 525 0.0 -513 525 0.0 -222 223 0.0 -193 526 0.0 -526 527 0.0 -278 325 0.0 -206 278 0.0 -37 193 0.0 -193 528 0.0 -193 195 0.0 -102 193 0.0 -193 197 0.0 -193 198 0.0 -183 386 0.0 -180 183 0.0 -183 186 0.0 -183 243 0.0 -183 184 0.0 -183 187 0.0 -114 183 0.0 -105 183 0.0 -98 463 0.0 -98 245 0.0 -98 102 0.0 -98 116 0.0 -98 198 0.0 -9 98 0.0 -98 235 0.0 -82 98 0.0 -10 98 0.0 -86 98 0.0 -12 98 0.0 -97 98 0.0 -90 98 0.0 -95 98 0.0 -84 98 0.0 -19 98 0.0 -17 98 0.0 -15 98 0.0 -98 99 0.0 -89 98 0.0 -92 98 0.0 -96 98 0.0 -91 98 0.0 -131 232 0.0 -131 233 0.0 130 131 0.0 -131 135 0.0 -131 461 0.0 -225 529 0.0 -111 529 0.0 -217 530 0.0 -380 388 0.0 -380 531 0.0 -122 380 0.0 -50 245 0.0 -119 225 0.0 -111 119 0.0 -245 456 0.0 -38 245 0.0 -245 532 0.0 -38 455 0.0 -391 484 0.0 -306 391 0.0 -180 190 0.0 -190 533 0.0 -186 190 0.0 -114 190 0.0 -29 190 0.0 -190 347 0.0 -190 201 0.0 -190 202 0.0 -116 190 0.0 -111 225 0.0 -126 323 0.0 -126 352 0.0 -365 488 0.0 -534 535 0.0 -524 536 0.0 -92 111 0.0 -92 151 0.0 -92 389 0.0 -92 444 0.0 -29 92 0.0 -92 198 0.0 -9 92 0.0 -92 149 0.0 -92 148 0.0 -92 153 0.0 -10 92 0.0 -92 109 0.0 -92 116 0.0 -82 92 0.0 -92 96 0.0 -15 92 0.0 -92 99 0.0 -89 92 0.0 -91 92 0.0 -92 97 0.0 -90 92 0.0 -86 92 0.0 -92 95 0.0 -84 92 0.0 -19 92 0.0 -12 92 0.0 -17 92 0.0 -114 386 0.0 -46 386 0.0 -333 537 0.0 -153 323 0.0 -116 153 0.0 -97 153 0.0 -153 233 0.0 -153 232 0.0 -99 153 0.0 -15 153 0.0 -12 153 0.0 -19 153 0.0 -95 153 0.0 -109 153 0.0 -82 153 0.0 -17 153 0.0 -86 153 0.0 -89 153 0.0 -84 153 0.0 -151 153 0.0 -148 153 0.0 -149 153 0.0 -130 135 0.0 -340 497 0.0 -475 477 0.0 -109 475 0.0 -116 475 0.0 -370 538 0.0 -370 387 0.0 -370 371 0.0 -539 540 0.0 -305 539 0.0 -399 519 0.0 -284 399 0.0 -541 542 0.0 -89 184 0.0 -184 243 0.0 -84 184 0.0 -114 184 0.0 -86 184 0.0 -184 186 0.0 -184 187 0.0 -327 328 0.0 -186 273 0.0 -224 273 0.0 -273 543 0.0 -267 273 0.0 -273 276 0.0 -323 354 0.0 -352 354 0.0 -100 354 0.0 -351 354 0.0 -353 354 0.0 -37 198 0.0 -37 38 0.0 -37 102 0.0 -37 463 0.0 -37 117 0.0 -267 276 0.0 -95 148 0.0 -95 117 0.0 -95 477 0.0 -95 444 0.0 -95 151 0.0 -95 105 0.0 -95 116 0.0 -95 109 0.0 -9 95 0.0 -95 235 0.0 -10 95 0.0 -82 95 0.0 -84 95 0.0 -90 95 0.0 -86 95 0.0 -95 97 0.0 -12 95 0.0 -17 95 0.0 -19 95 0.0 -95 99 0.0 -89 95 0.0 -15 95 0.0 -91 95 0.0 -95 96 0.0 -172 544 0.0 -203 388 0.0 -23 508 0.0 -109 508 0.0 -444 508 0.0 -545 546 0.0 -105 514 0.0 -242 514 0.0 -389 514 0.0 -230 514 0.0 -53 514 0.0 -172 514 0.0 -513 514 0.0 -96 463 0.0 -117 235 0.0 -151 235 0.0 -17 235 0.0 -109 235 0.0 -10 235 0.0 -9 235 0.0 -89 235 0.0 -116 235 0.0 -12 235 0.0 -96 235 0.0 -99 235 0.0 -90 235 0.0 -15 235 0.0 -97 235 0.0 -84 235 0.0 -91 235 0.0 -19 235 0.0 -113 547 0.0 -38 548 0.0 -38 115 0.0 -38 456 0.0 -38 195 0.0 -38 197 0.0 -38 102 0.0 -38 363 0.0 -284 519 0.0 -549 550 0.0 -89 551 0.0 -113 551 0.0 -84 551 0.0 -97 551 0.0 -10 407 0.0 -9 407 0.0 -109 407 0.0 -84 407 0.0 -15 407 0.0 -105 407 0.0 -187 243 0.0 -180 187 0.0 -187 340 0.0 -114 187 0.0 -186 187 0.0 -53 242 0.0 -53 54 0.0 -53 371 0.0 -53 232 0.0 -53 513 0.0 -53 209 0.0 -23 552 0.0 -165 333 0.0 -211 333 0.0 -102 111 0.0 -86 102 0.0 -102 115 0.0 -102 117 0.0 -29 102 0.0 -97 102 0.0 -102 361 0.0 -102 528 0.0 -102 527 0.0 -99 102 0.0 -102 196 0.0 -102 197 0.0 -102 198 0.0 -102 195 0.0 -305 306 0.0 -306 540 0.0 -23 389 0.0 -116 389 0.0 -109 389 0.0 -86 389 0.0 -17 389 0.0 -89 389 0.0 -230 389 0.0 -157 247 0.0 -247 553 0.0 -247 442 0.0 -244 247 0.0 -82 151 0.0 -17 151 0.0 -86 151 0.0 -151 477 0.0 -89 151 0.0 -109 151 0.0 -84 151 0.0 -149 151 0.0 -148 151 0.0 -73 492 0.0 -213 492 0.0 -242 492 0.0 -54 492 0.0 -244 492 0.0 -109 316 0.0 -109 554 0.0 -109 113 0.0 -19 109 0.0 -15 109 0.0 -109 474 0.0 -84 109 0.0 -109 114 0.0 -90 109 0.0 -89 109 0.0 -109 477 0.0 -17 109 0.0 -109 444 0.0 -23 109 0.0 -109 116 0.0 -444 476 0.0 -91 444 0.0 -89 444 0.0 -444 474 0.0 -23 444 0.0 -17 444 0.0 -444 477 0.0 -116 444 0.0 -168 437 0.0 -186 555 0.0 -15 360 0.0 -15 148 0.0 -15 105 0.0 -15 111 0.0 -15 116 0.0 -9 15 0.0 -10 15 0.0 -15 82 0.0 -15 96 0.0 -15 19 0.0 -15 17 0.0 -15 90 0.0 -15 89 0.0 -12 15 0.0 -15 97 0.0 -15 84 0.0 -15 86 0.0 -15 91 0.0 -15 99 0.0 -233 387 0.0 -387 388 0.0 -116 180 0.0 -46 180 0.0 -105 180 0.0 -114 180 0.0 -522 556 0.0 -175 421 0.0 -175 176 0.0 -419 420 0.0 -89 111 0.0 -84 111 0.0 -111 450 0.0 -90 111 0.0 -105 111 0.0 -99 111 0.0 -86 111 0.0 -111 360 0.0 -91 111 0.0 -19 111 0.0 -2 105 0.0 -29 91 0.0 -91 360 0.0 -91 116 0.0 -91 198 0.0 -9 91 0.0 -10 91 0.0 -82 91 0.0 -91 96 0.0 -89 91 0.0 -91 99 0.0 -19 91 0.0 -12 91 0.0 -17 91 0.0 -91 97 0.0 -86 91 0.0 -90 91 0.0 -84 91 0.0 -211 499 0.0 -84 211 0.0 -557 558 0.0 -54 450 0.0 -206 209 0.0 -206 559 0.0 -115 197 0.0 -388 560 0.0 -402 429 0.0 -402 427 0.0 -402 430 0.0 -99 114 0.0 -105 114 0.0 -29 114 0.0 -114 116 0.0 -114 243 0.0 -84 114 0.0 -114 340 0.0 -46 114 0.0 -195 528 0.0 -198 528 0.0 -353 385 0.0 -352 353 0.0 -351 353 0.0 -100 353 0.0 -351 352 0.0 -100 351 0.0 -477 554 0.0 -305 540 0.0 -360 381 0.0 -105 381 0.0 -68 561 0.0 -73 562 0.0 -176 421 0.0 -100 352 0.0 -116 477 0.0 -46 116 0.0 -9 116 0.0 -10 116 0.0 -86 116 0.0 -12 116 0.0 -96 116 0.0 -84 116 0.0 -90 116 0.0 -97 116 0.0 -82 116 0.0 -19 116 0.0 -99 116 0.0 -110 116 0.0 -23 116 0.0 -89 116 0.0 -17 116 0.0 -209 563 0.0 -209 442 0.0 -209 242 0.0 -54 209 0.0 -195 361 0.0 -197 361 0.0 -198 361 0.0 -361 388 0.0 -17 23 0.0 -23 477 0.0 -172 317 0.0 -172 513 0.0 -54 172 0.0 -17 29 0.0 -17 110 0.0 -17 198 0.0 -9 17 0.0 -17 148 0.0 -17 149 0.0 -10 17 0.0 -17 82 0.0 -17 96 0.0 -17 99 0.0 -17 89 0.0 -12 17 0.0 -17 19 0.0 -17 84 0.0 -17 90 0.0 -17 86 0.0 -17 97 0.0 -213 280 0.0 -263 266 0.0 -564 565 0.0 -242 491 0.0 -35 491 0.0 -244 491 0.0 -186 202 0.0 -29 566 0.0 -106 371 0.0 -356 357 0.0 -323 567 0.0 -165 218 0.0 -224 336 0.0 -224 337 0.0 -224 276 0.0 -27 54 0.0 -148 568 0.0 -233 244 0.0 -29 244 0.0 -35 244 0.0 -244 276 0.0 -54 244 0.0 -244 388 0.0 -117 244 0.0 -232 244 0.0 -213 244 0.0 -242 244 0.0 -218 562 0.0 -336 337 0.0 -427 429 0.0 -429 430 0.0 -1 213 0.0 -242 513 0.0 -9 96 0.0 -10 96 0.0 -82 96 0.0 -86 96 0.0 -84 96 0.0 -12 96 0.0 -96 97 0.0 -19 96 0.0 -96 99 0.0 -89 96 0.0 -90 96 0.0 -54 105 0.0 -54 243 0.0 -168 336 0.0 -84 113 0.0 -113 117 0.0 -105 215 0.0 -105 276 0.0 -12 105 0.0 -9 12 0.0 -10 12 0.0 -12 82 0.0 +124 131 0.0 +8 131 0.0 +120 131 0.0 +122 131 0.0 +30 131 0.0 +119 131 0.0 +126 131 0.0 +5 131 0.0 +304 567 0.0 +568 569 0.0 +81 378 0.0 +378 379 0.0 +336 378 0.0 +83 378 0.0 +378 570 0.0 +378 455 0.0 +62 378 0.0 +377 378 0.0 +145 276 0.0 +114 276 0.0 +64 276 0.0 +120 276 0.0 +31 276 0.0 +30 276 0.0 +123 276 0.0 +122 276 0.0 +7 276 0.0 +5 276 0.0 +132 276 0.0 +130 276 0.0 +126 276 0.0 +8 276 0.0 +59 571 0.0 +60 572 0.0 +60 466 0.0 +60 222 0.0 +60 225 0.0 +60 224 0.0 +60 135 0.0 +60 370 0.0 +222 370 0.0 +135 370 0.0 +66 233 0.0 +66 75 0.0 +66 210 0.0 +66 213 0.0 +64 66 0.0 +392 542 0.0 +154 528 0.0 +193 528 0.0 +214 573 0.0 +488 557 0.0 +327 329 0.0 +138 327 0.0 +138 574 0.0 +7 486 0.0 +40 486 0.0 +52 540 0.0 +540 548 0.0 +104 210 0.0 +64 210 0.0 +210 268 0.0 +210 213 0.0 +210 233 0.0 +206 210 0.0 +210 214 0.0 +392 553 0.0 +150 392 0.0 +18 392 0.0 +271 392 0.0 +81 392 0.0 +81 240 0.0 +81 379 0.0 +52 81 0.0 +81 377 0.0 +81 336 0.0 +81 83 0.0 +81 415 0.0 +81 104 0.0 +18 81 0.0 +81 271 0.0 +453 575 0.0 +138 575 0.0 +190 342 0.0 +135 144 0.0 +132 135 0.0 +135 368 0.0 +135 550 0.0 +135 374 0.0 +135 222 0.0 +135 224 0.0 +135 225 0.0 +154 313 0.0 +18 313 0.0 +312 313 0.0 +313 564 0.0 +52 313 0.0 +453 455 0.0 +125 455 0.0 +64 455 0.0 +138 455 0.0 +119 455 0.0 +32 455 0.0 +62 455 0.0 +18 291 0.0 +138 175 0.0 +64 175 0.0 +32 175 0.0 +124 175 0.0 +118 175 0.0 +125 175 0.0 +119 175 0.0 +122 175 0.0 +120 175 0.0 +175 177 0.0 +174 175 0.0 +106 576 0.0 +138 383 0.0 +138 577 0.0 +8 138 0.0 +114 138 0.0 +7 138 0.0 +138 266 0.0 +138 329 0.0 +130 138 0.0 +4 138 0.0 +138 451 0.0 +125 138 0.0 +120 138 0.0 +32 138 0.0 +119 138 0.0 +138 453 0.0 +138 417 0.0 +64 138 0.0 +12 13 0.0 +12 22 0.0 12 19 0.0 -12 97 0.0 -12 84 0.0 -12 86 0.0 -12 90 0.0 -12 89 0.0 -12 99 0.0 -474 477 0.0 -201 202 0.0 -82 232 0.0 -35 232 0.0 -232 442 0.0 -232 233 0.0 -64 232 0.0 -97 360 0.0 -84 360 0.0 -99 360 0.0 -19 360 0.0 -105 360 0.0 -196 364 0.0 -427 430 0.0 -99 196 0.0 -196 197 0.0 -196 198 0.0 -195 196 0.0 -29 149 0.0 -82 149 0.0 -86 149 0.0 -148 149 0.0 -84 149 0.0 -89 149 0.0 -242 442 0.0 -19 29 0.0 -9 19 0.0 -10 19 0.0 -19 82 0.0 -19 99 0.0 -19 89 0.0 -19 84 0.0 -19 90 0.0 -19 86 0.0 -19 97 0.0 -139 467 0.0 -86 198 0.0 -29 198 0.0 -97 198 0.0 -99 198 0.0 -195 198 0.0 -197 198 0.0 -84 323 0.0 -29 84 0.0 -84 301 0.0 -84 105 0.0 -9 84 0.0 -84 148 0.0 -10 84 0.0 -82 84 0.0 -84 388 0.0 -84 90 0.0 -84 89 0.0 -84 97 0.0 -84 86 0.0 -84 99 0.0 -34 35 0.0 -33 34 0.0 -195 197 0.0 -97 105 0.0 -99 105 0.0 -105 117 0.0 -105 517 0.0 -517 569 0.0 -46 230 0.0 -230 340 0.0 -570 571 0.0 -369 371 0.0 -117 532 0.0 -195 527 0.0 -9 90 0.0 -10 90 0.0 -82 90 0.0 -89 90 0.0 -90 99 0.0 -90 97 0.0 -86 90 0.0 -29 86 0.0 -29 97 0.0 -29 99 0.0 -46 340 0.0 -213 284 0.0 -157 572 0.0 -10 82 0.0 -10 86 0.0 -10 89 0.0 -10 99 0.0 -10 97 0.0 -9 97 0.0 -82 97 0.0 -86 97 0.0 -89 97 0.0 -97 99 0.0 -9 86 0.0 -9 82 0.0 -9 89 0.0 -9 99 0.0 -99 117 0.0 -99 148 0.0 -82 99 0.0 -86 99 0.0 -89 99 0.0 -301 550 0.0 -157 388 0.0 -89 148 0.0 -82 89 0.0 -86 89 0.0 -213 301 0.0 -130 461 0.0 -82 148 0.0 -82 86 0.0 -388 521 0.0 -86 148 0.0 +4 417 0.0 +417 451 0.0 +120 417 0.0 +125 417 0.0 +32 417 0.0 +119 417 0.0 +64 417 0.0 +52 578 0.0 +4 7 0.0 +7 225 0.0 +7 43 0.0 +7 429 0.0 +7 142 0.0 +7 40 0.0 +7 166 0.0 +7 18 0.0 +7 64 0.0 +7 114 0.0 +7 174 0.0 +7 116 0.0 +7 118 0.0 +7 31 0.0 +7 123 0.0 +7 130 0.0 +7 124 0.0 +7 8 0.0 +7 120 0.0 +7 122 0.0 +7 30 0.0 +7 119 0.0 +7 126 0.0 +5 7 0.0 +7 125 0.0 +7 32 0.0 +7 132 0.0 +397 409 0.0 +18 409 0.0 +304 409 0.0 +209 268 0.0 +209 213 0.0 +484 533 0.0 +533 579 0.0 +154 193 0.0 +18 193 0.0 +193 305 0.0 +193 241 0.0 +434 435 0.0 +43 166 0.0 +119 166 0.0 +120 166 0.0 +126 166 0.0 +30 166 0.0 +130 166 0.0 +8 166 0.0 +40 166 0.0 +32 166 0.0 +132 166 0.0 +122 166 0.0 +5 166 0.0 +22 40 0.0 +19 22 0.0 +18 22 0.0 +126 222 0.0 +43 126 0.0 +126 429 0.0 +18 126 0.0 +126 225 0.0 +64 126 0.0 +116 126 0.0 +114 126 0.0 +118 126 0.0 +31 126 0.0 +5 126 0.0 +119 126 0.0 +30 126 0.0 +122 126 0.0 +8 126 0.0 +120 126 0.0 +124 126 0.0 +126 130 0.0 +123 126 0.0 +126 132 0.0 +32 126 0.0 +125 126 0.0 +40 326 0.0 +213 538 0.0 +18 413 0.0 +32 235 0.0 +235 240 0.0 +19 235 0.0 +235 236 0.0 +59 144 0.0 +224 550 0.0 +225 550 0.0 +222 550 0.0 +109 416 0.0 +18 416 0.0 +150 453 0.0 +18 363 0.0 +312 564 0.0 +556 580 0.0 +580 581 0.0 +40 405 0.0 +18 405 0.0 +537 581 0.0 +490 556 0.0 +101 102 0.0 +198 436 0.0 +199 436 0.0 +72 268 0.0 +18 115 0.0 +64 383 0.0 +64 174 0.0 +64 233 0.0 +4 64 0.0 +64 451 0.0 +64 177 0.0 +64 142 0.0 +30 64 0.0 +64 114 0.0 +64 123 0.0 +31 64 0.0 +64 213 0.0 +64 118 0.0 +5 64 0.0 +64 75 0.0 +64 132 0.0 +64 124 0.0 +64 122 0.0 +64 453 0.0 +8 64 0.0 +64 130 0.0 +64 125 0.0 +32 64 0.0 +64 120 0.0 +64 119 0.0 +240 570 0.0 +104 240 0.0 +240 447 0.0 +18 240 0.0 +240 582 0.0 +83 240 0.0 +240 336 0.0 +14 583 0.0 +224 368 0.0 +222 368 0.0 +225 368 0.0 +304 368 0.0 +32 236 0.0 +32 415 0.0 +32 43 0.0 +32 145 0.0 +32 451 0.0 +32 225 0.0 +32 429 0.0 +32 40 0.0 +32 161 0.0 +18 32 0.0 +32 428 0.0 +32 114 0.0 +32 174 0.0 +32 177 0.0 +32 118 0.0 +31 32 0.0 +32 123 0.0 +32 120 0.0 +8 32 0.0 +32 122 0.0 +30 32 0.0 +32 130 0.0 +32 124 0.0 +5 32 0.0 +32 119 0.0 +32 125 0.0 +32 132 0.0 +125 451 0.0 +119 451 0.0 +120 451 0.0 +584 585 0.0 +336 494 0.0 +51 494 0.0 +198 199 0.0 +548 586 0.0 +52 548 0.0 +206 212 0.0 +206 214 0.0 +139 587 0.0 +139 379 0.0 +365 366 0.0 +18 190 0.0 +190 344 0.0 +52 190 0.0 +284 348 0.0 +284 349 0.0 +284 289 0.0 +19 236 0.0 +415 447 0.0 +336 447 0.0 +477 588 0.0 +106 589 0.0 +348 349 0.0 +377 379 0.0 +377 570 0.0 +336 377 0.0 +83 377 0.0 +415 590 0.0 +104 591 0.0 +123 225 0.0 +18 123 0.0 +114 123 0.0 +116 123 0.0 +118 123 0.0 +31 123 0.0 +30 123 0.0 +123 124 0.0 +123 125 0.0 +119 123 0.0 +120 123 0.0 +122 123 0.0 +123 132 0.0 +8 123 0.0 +123 130 0.0 +5 123 0.0 +40 83 0.0 +83 202 0.0 +52 592 0.0 +18 109 0.0 +191 348 0.0 +59 145 0.0 +40 243 0.0 +172 310 0.0 +310 593 0.0 +52 289 0.0 +30 429 0.0 +30 40 0.0 +30 161 0.0 +18 30 0.0 +30 114 0.0 +30 116 0.0 +30 31 0.0 +30 118 0.0 +5 30 0.0 +30 125 0.0 +30 132 0.0 +30 130 0.0 +30 124 0.0 +30 122 0.0 +8 30 0.0 +30 120 0.0 +30 119 0.0 +52 570 0.0 +304 594 0.0 +104 594 0.0 +40 213 0.0 +8 213 0.0 +132 213 0.0 +5 213 0.0 +130 213 0.0 +43 213 0.0 +62 213 0.0 +202 213 0.0 +213 268 0.0 +213 233 0.0 +75 213 0.0 +212 214 0.0 +214 233 0.0 +122 415 0.0 +120 415 0.0 +118 415 0.0 +124 415 0.0 +119 415 0.0 +18 415 0.0 +373 374 0.0 +595 596 0.0 +154 374 0.0 +222 374 0.0 +224 374 0.0 +225 374 0.0 +18 177 0.0 +118 177 0.0 +174 177 0.0 +124 177 0.0 +119 177 0.0 +125 177 0.0 +120 177 0.0 +122 177 0.0 +31 142 0.0 +142 145 0.0 +336 356 0.0 +52 336 0.0 +8 473 0.0 +8 40 0.0 +8 429 0.0 +8 225 0.0 +8 43 0.0 +8 18 0.0 +8 161 0.0 +8 116 0.0 +8 114 0.0 +8 118 0.0 +8 31 0.0 +8 130 0.0 +8 124 0.0 +8 120 0.0 +8 122 0.0 +8 119 0.0 +5 8 0.0 +8 125 0.0 +8 132 0.0 +161 473 0.0 +40 473 0.0 +124 225 0.0 +125 225 0.0 +43 225 0.0 +132 225 0.0 +224 225 0.0 +222 225 0.0 +52 312 0.0 +43 122 0.0 +51 122 0.0 +122 305 0.0 +18 122 0.0 +114 122 0.0 +40 122 0.0 +122 174 0.0 +122 304 0.0 +118 122 0.0 +31 122 0.0 +122 132 0.0 +122 125 0.0 +119 122 0.0 +5 122 0.0 +122 124 0.0 +122 130 0.0 +120 122 0.0 +45 49 0.0 +49 51 0.0 +19 191 0.0 +222 224 0.0 +1 52 0.0 +1 40 0.0 +305 597 0.0 +62 75 0.0 +62 268 0.0 +40 119 0.0 +40 124 0.0 +40 125 0.0 +40 120 0.0 +5 40 0.0 +40 130 0.0 +40 132 0.0 +40 145 0.0 +18 40 0.0 +376 379 0.0 +56 554 0.0 +18 271 0.0 +43 130 0.0 +4 130 0.0 +130 429 0.0 +130 174 0.0 +18 130 0.0 +116 130 0.0 +114 130 0.0 +31 130 0.0 +118 130 0.0 +125 130 0.0 +130 132 0.0 +120 130 0.0 +124 130 0.0 +5 130 0.0 +119 130 0.0 +43 124 0.0 +43 125 0.0 +43 132 0.0 +18 253 0.0 +154 253 0.0 +75 268 0.0 +304 598 0.0 +51 305 0.0 +48 51 0.0 +104 582 0.0 +31 429 0.0 +18 31 0.0 +31 114 0.0 +31 116 0.0 +31 124 0.0 +31 118 0.0 +31 125 0.0 +5 31 0.0 +31 132 0.0 +31 119 0.0 +31 120 0.0 +5 429 0.0 +5 18 0.0 +5 114 0.0 +5 116 0.0 +5 118 0.0 +5 125 0.0 +5 119 0.0 +5 120 0.0 +5 124 0.0 +5 132 0.0 +132 174 0.0 +18 132 0.0 +114 132 0.0 +116 132 0.0 +118 132 0.0 +124 132 0.0 +120 132 0.0 +119 132 0.0 +125 132 0.0 +52 419 0.0 +18 419 0.0 +18 19 0.0 +104 304 0.0 +18 120 0.0 +114 120 0.0 +120 174 0.0 +118 120 0.0 +120 124 0.0 +119 120 0.0 +120 125 0.0 +18 241 0.0 +52 241 0.0 +241 305 0.0 +154 428 0.0 +18 428 0.0 +412 534 0.0 +304 534 0.0 +154 304 0.0 +18 304 0.0 +304 412 0.0 +18 412 0.0 +18 118 0.0 +18 154 0.0 +18 124 0.0 +18 119 0.0 +18 125 0.0 +18 52 0.0 +18 305 0.0 +154 482 0.0 +114 124 0.0 +124 174 0.0 +118 124 0.0 +119 124 0.0 +124 125 0.0 +114 125 0.0 +114 118 0.0 +114 119 0.0 +118 174 0.0 +118 125 0.0 +118 119 0.0 +174 483 0.0 +119 174 0.0 +119 125 0.0 +125 174 0.0 \ No newline at end of file diff --git a/results/networks/model_nodes.txt b/results/networks/model_nodes.txt index 1c31085..bfebb0e 100644 --- a/results/networks/model_nodes.txt +++ b/results/networks/model_nodes.txt @@ -1,574 +1,600 @@ node_id alias shape size color x y weight -0 VAMP3 ELLIPSE 20.0 #ffcccc 509.94 37.11 0.0 -1 VPS53 ELLIPSE 20.0 #ffcccc 426.1 192.06 0.0 -2 PICALM ELLIPSE 20.0 #ffcccc 230.49 122.35 0.0 -3 STX5 ELLIPSE 20.0 #ffcccc 393.29 22.8 0.0 -4 SNAP47 ELLIPSE 20.0 #ffcccc 614.44 -72.34 0.0 -5 PKP2 ELLIPSE 20.0 #ffcccc 159.97 1087.33 0.0 -6 KRT18 ELLIPSE 20.0 #ffcccc 245.34 1330.12 0.0 -7 CTNNB1 ELLIPSE 20.0 #ffcccc -50.61 641.73 0.0 -8 MRPS35 ELLIPSE 20.0 #ffcccc -574.2 88.33 0.0 -9 C18orf32 ELLIPSE 20.0 #ffcccc -374.66 156.25 0.0 -10 RPL17-C18orf32 ELLIPSE 20.0 #ffcccc -356.15 151.35 0.0 -11 HSPBP1 ELLIPSE 20.0 #ffcccc -384.98 32.64 0.0 -12 RPL10 ELLIPSE 20.0 #ffcccc -434.24 113.75 0.0 -13 RPL3 ELLIPSE 20.0 #ffcccc -423.12 105.81 0.0 -14 RPS15A ELLIPSE 20.0 #ffcccc -482.34 115.58 0.0 -15 RPL13A ELLIPSE 20.0 #ffcccc -398.99 137.44 0.0 -16 RPS23 ELLIPSE 20.0 #ffcccc -447.4 84.53 0.0 -17 RPS14 ELLIPSE 20.0 #ffcccc -422.63 114.01 0.0 -18 MRPL51 ELLIPSE 20.0 #ffcccc -823.67 6.22 0.0 -19 RPL23 ELLIPSE 20.0 #ffcccc -464.6 131.99 0.0 -20 MRPL33 ELLIPSE 20.0 #ffcccc -536.2 31.95 0.0 -21 MRPS18B ELLIPSE 20.0 #ffcccc -755.64 -68.33 0.0 -22 TNS1 ELLIPSE 20.0 #ffcccc 198.61 163.5 0.0 -23 NOLC1 ELLIPSE 20.0 #ffcccc -113.28 37.12 0.0 -24 ZYX ELLIPSE 20.0 #ffcccc 102.54 277.44 0.0 -25 VCL ELLIPSE 20.0 #ffcccc 197.34 409.57 0.0 -26 SLC22A4 ELLIPSE 20.0 #ffcccc -372.04 1314.96 0.0 -27 PDZK1 ELLIPSE 20.0 #ffcccc -309.8 1003.47 0.0 -28 PDRG1 ELLIPSE 20.0 #ffcccc -853.72 -259.75 0.0 -29 PFDN5 ELLIPSE 20.0 #ffcccc -582.8 61.1 0.0 -30 TENT4A ELLIPSE 20.0 #ffcccc 377.05 635.17 0.0 -31 RAP1B ELLIPSE 20.0 #ffcccc 213.46 753.07 0.0 -32 MYL12A ELLIPSE 20.0 #ffcccc 311.35 551.81 0.0 -33 MANF ELLIPSE 20.0 #ffcccc 310.85 282.86 0.0 -34 WDR1 ELLIPSE 20.0 #ffcccc 308.6 462.64 0.0 -35 ACTG1 ELLIPSE 20.0 #ffcccc 31.69 513.71 0.0 -36 HSCB ELLIPSE 20.0 #ffcccc -1323.18 -47.82 0.0 -37 PMPCA ELLIPSE 20.0 #ffcccc -1017.7 -5.2 0.0 -38 SDHB ELLIPSE 20.0 #ffcccc -1193.7 2.41 0.0 -39 PNN ELLIPSE 20.0 #ffcccc -514.15 -416.36 0.0 -40 RSRC2 ELLIPSE 20.0 #ffcccc -559.77 -767.95 0.0 -41 HNRNPM ELLIPSE 20.0 #ffcccc -501.53 -142.98 0.0 -42 HNRNPA2B1 ELLIPSE 20.0 #ffcccc -497.34 -31.06 0.0 -43 HNRNPH3 ELLIPSE 20.0 #ffcccc -509.73 -237.95 0.0 -44 ARGLU1 ELLIPSE 20.0 #ffcccc -440.35 -528.75 0.0 -45 CASC3 ELLIPSE 20.0 #ffcccc -575.95 -364.05 0.0 -46 RNPS1 ELLIPSE 20.0 #ffcccc -479.22 -215.29 0.0 -47 ACOT8 ELLIPSE 20.0 #ffcccc -1113.99 -338.3 0.0 -48 PEX7 ELLIPSE 20.0 #ffcccc -571.71 -3.56 0.0 -49 PAOX ELLIPSE 20.0 #ffcccc -1332.14 -483.08 0.0 -50 GNPAT ELLIPSE 20.0 #ffcccc -1298.08 -372.22 0.0 -51 STAG2 ELLIPSE 20.0 #ffcccc -69.8 282.64 0.0 -52 JUND ELLIPSE 20.0 #ffcccc 139.51 337.95 0.0 -53 HIST1H2AC ELLIPSE 20.0 #ffcccc -450.77 410.11 0.0 -54 ESR1 ELLIPSE 20.0 #ffcccc -250.49 409.03 0.0 -55 TERF2 ELLIPSE 20.0 #ffcccc 69.31 84.0 0.0 -56 CCNB1 ELLIPSE 20.0 #ffcccc -101.73 114.82 0.0 -57 SMC1A ELLIPSE 20.0 #ffcccc -39.57 213.34 0.0 -58 CORO1A ELLIPSE 20.0 #ffcccc 576.31 339.4 0.0 -59 CD37 ELLIPSE 20.0 #ffcccc 826.98 303.89 0.0 -60 POC1A ELLIPSE 20.0 #ffcccc 304.83 106.23 0.0 -61 DOCK2 ELLIPSE 20.0 #ffcccc 765.82 541.39 0.0 -62 ACTR3 ELLIPSE 20.0 #ffcccc 153.72 439.95 0.0 -63 MGA ELLIPSE 20.0 #ffcccc -805.98 752.7 0.0 -64 BOLA2-SMG1P6 ELLIPSE 20.0 #ffcccc -632.98 819.41 0.0 -65 CBX3 ELLIPSE 20.0 #ffcccc -630.48 392.63 0.0 -66 GSR ELLIPSE 20.0 #ffcccc -1507.04 233.54 0.0 -67 PDHB ELLIPSE 20.0 #ffcccc -1010.36 183.82 0.0 -68 GSTP1 ELLIPSE 20.0 #ffcccc -1814.53 254.78 0.0 -69 TLE5 ELLIPSE 20.0 #ffcccc 197.9 863.38 0.0 -70 SNAPC2 ELLIPSE 20.0 #ffcccc -750.74 632.84 0.0 -71 GTF2E2 ELLIPSE 20.0 #ffcccc -770.68 351.95 0.0 -72 POLR2G ELLIPSE 20.0 #ffcccc -604.01 243.7 0.0 -73 POLR3G ELLIPSE 20.0 #ffcccc -551.14 931.8 0.0 -74 RABAC1 ELLIPSE 20.0 #ffcccc 348.67 1315.69 0.0 -75 NTAQ1 ELLIPSE 20.0 #ffcccc 457.58 1541.3 0.0 -76 RAB5A ELLIPSE 20.0 #ffcccc 156.37 951.26 0.0 -77 CHN2 ELLIPSE 20.0 #ffcccc -1305.43 -649.3 0.0 -78 KMT5B ELLIPSE 20.0 #ffcccc -1145.65 -467.04 0.0 -79 FIS1 ELLIPSE 20.0 #ffcccc -1492.47 559.55 0.0 -80 MAF1 ELLIPSE 20.0 #ffcccc -1219.87 511.76 0.0 -81 SEC61B ELLIPSE 20.0 #ffcccc -261.69 142.38 0.0 -82 RPS10-NUDT3 ELLIPSE 20.0 #ffcccc -424.02 215.48 0.0 -83 RPS7 ELLIPSE 20.0 #ffcccc -377.69 118.45 0.0 -84 RACK1 ELLIPSE 20.0 #ffcccc -353.77 196.08 0.0 -85 RPL7 ELLIPSE 20.0 #ffcccc -375.1 89.32 0.0 -86 RPS10 ELLIPSE 20.0 #ffcccc -459.13 61.65 0.0 -87 RPS27A ELLIPSE 20.0 #ffcccc -321.64 305.85 0.0 -88 CANX ELLIPSE 20.0 #ffcccc -247.66 349.25 0.0 -89 RPS19 ELLIPSE 20.0 #ffcccc -333.85 131.23 0.0 -90 RPL18 ELLIPSE 20.0 #ffcccc -377.83 198.52 0.0 -91 RPL24 ELLIPSE 20.0 #ffcccc -486.16 160.42 0.0 -92 RPS27 ELLIPSE 20.0 #ffcccc -441.76 146.67 0.0 -93 RPL38 ELLIPSE 20.0 #ffcccc -455.56 183.86 0.0 -94 RPL22 ELLIPSE 20.0 #ffcccc -389.12 215.99 0.0 -95 RPL7A ELLIPSE 20.0 #ffcccc -431.34 47.63 0.0 -96 RPL36A ELLIPSE 20.0 #ffcccc -493.84 179.17 0.0 -97 RPL26 ELLIPSE 20.0 #ffcccc -503.66 125.42 0.0 -98 RPL39 ELLIPSE 20.0 #ffcccc -551.56 128.01 0.0 -99 RPL27 ELLIPSE 20.0 #ffcccc -527.45 106.57 0.0 -100 UBE2J2 ELLIPSE 20.0 #ffcccc -30.13 267.8 0.0 -101 SFXN3 ELLIPSE 20.0 #ffcccc -1218.11 -58.67 0.0 -102 UQCRQ ELLIPSE 20.0 #ffcccc -853.91 78.17 0.0 -103 NUFIP2 ELLIPSE 20.0 #ffcccc -594.53 164.76 0.0 -104 C1QBP ELLIPSE 20.0 #ffcccc -631.76 -160.99 0.0 -105 HSPA8 ELLIPSE 20.0 #ffcccc -302.84 172.4 0.0 -106 UBAP2L ELLIPSE 20.0 #ffcccc -804.28 153.92 0.0 -107 GRSF1 ELLIPSE 20.0 #ffcccc -941.54 -297.07 0.0 -108 MAGED2 ELLIPSE 20.0 #ffcccc -303.2 -616.17 0.0 -109 NOP56 ELLIPSE 20.0 #ffcccc -333.69 22.22 0.0 -110 SSBP1 ELLIPSE 20.0 #ffcccc -642.76 -85.54 0.0 -111 NME2 ELLIPSE 20.0 #ffcccc -448.9 -18.74 0.0 -112 GP1BB ELLIPSE 20.0 #ffcccc -802.67 -532.91 0.0 -113 TOMM40 ELLIPSE 20.0 #ffcccc -771.97 -165.62 0.0 -114 DDX39B ELLIPSE 20.0 #ffcccc -455.53 -100.09 0.0 -115 CHCHD2 ELLIPSE 20.0 #ffcccc -1008.83 -84.1 0.0 -116 SNU13 ELLIPSE 20.0 #ffcccc -423.64 4.53 0.0 -117 PHB1 ELLIPSE 20.0 #ffcccc -689.94 35.61 0.0 -118 TMEM97 ELLIPSE 20.0 #ffcccc -100.93 -626.81 0.0 -119 GUK1 ELLIPSE 20.0 #ffcccc -163.69 -492.3 0.0 -120 JADE1 ELLIPSE 20.0 #ffcccc -1084.1 -112.03 0.0 -121 YJU2 ELLIPSE 20.0 #ffcccc -837.04 -402.14 0.0 -122 ING4 ELLIPSE 20.0 #ffcccc -995.51 325.08 0.0 -123 ZPR1 ELLIPSE 20.0 #ffcccc -9.26 134.15 0.0 -124 WDR3 ELLIPSE 20.0 #ffcccc -240.35 16.59 0.0 -125 UBE4B ELLIPSE 20.0 #ffcccc 177.83 268.94 0.0 -126 UFC1 ELLIPSE 20.0 #ffcccc 44.67 299.09 0.0 -127 IL10RA ELLIPSE 20.0 #ffcccc 754.55 764.59 0.0 -128 ITGAL ELLIPSE 20.0 #ffcccc 517.5 834.15 0.0 -129 GLI1 ELLIPSE 20.0 #ffcccc -326.13 682.9 0.0 -130 SEM1 ELLIPSE 20.0 #ffcccc -234.68 598.31 0.0 -131 PSMB5 ELLIPSE 20.0 #ffcccc -308.58 549.26 0.0 -132 PSMB10 ELLIPSE 20.0 #ffcccc -263.6 535.75 0.0 -133 UBB ELLIPSE 20.0 #ffcccc -308.94 360.94 0.0 -134 PTCH2 ELLIPSE 20.0 #ffcccc -403.19 1066.49 0.0 -135 SUFU ELLIPSE 20.0 #ffcccc -351.24 574.7 0.0 -136 ITFG2 ELLIPSE 20.0 #ffcccc -1357.53 713.25 0.0 -137 BTN2A1 ELLIPSE 20.0 #ffcccc -1554.82 819.72 0.0 -138 WDR24 ELLIPSE 20.0 #ffcccc -1270.09 735.0 0.0 -139 ATP6V0B ELLIPSE 20.0 #ffcccc -1166.07 613.91 0.0 -140 ATP6V1H ELLIPSE 20.0 #ffcccc -1078.9 610.79 0.0 -141 BMT2 ELLIPSE 20.0 #ffcccc -1287.82 696.35 0.0 -142 RHEB ELLIPSE 20.0 #ffcccc -1313.32 633.36 0.0 -143 LAMTOR4 ELLIPSE 20.0 #ffcccc -1245.99 594.86 0.0 -144 NDUFB10 ELLIPSE 20.0 #ffcccc -979.88 61.27 0.0 -145 GPLD1 ELLIPSE 20.0 #ffcccc 1667.31 110.5 0.0 -146 PIGW ELLIPSE 20.0 #ffcccc 1771.44 106.85 0.0 -147 EIF1B ELLIPSE 20.0 #ffcccc -461.54 204.48 0.0 -148 EIF3L ELLIPSE 20.0 #ffcccc -326.62 38.81 0.0 -149 EIF1 ELLIPSE 20.0 #ffcccc -425.81 171.06 0.0 -150 RPS3 ELLIPSE 20.0 #ffcccc -402.31 77.49 0.0 -151 EIF3CL ELLIPSE 20.0 #ffcccc -321.2 75.75 0.0 -152 EIF3C ELLIPSE 20.0 #ffcccc -321.93 109.18 0.0 -153 EIF3A ELLIPSE 20.0 #ffcccc -326.9 166.65 0.0 -154 EIF3G ELLIPSE 20.0 #ffcccc -394.5 77.46 0.0 -155 TTC31 ELLIPSE 20.0 #ffcccc -334.42 -398.69 0.0 -156 TCEANC2 ELLIPSE 20.0 #ffcccc -883.1 513.21 0.0 -157 SUPT5H ELLIPSE 20.0 #ffcccc -696.58 607.17 0.0 -158 TBPL1 ELLIPSE 20.0 #ffcccc -913.67 370.93 0.0 -159 KPNA3 ELLIPSE 20.0 #ffcccc -1071.76 378.91 0.0 -160 TADA2B ELLIPSE 20.0 #ffcccc -620.98 300.36 0.0 -161 YEATS2 ELLIPSE 20.0 #ffcccc -690.31 346.4 0.0 -162 FGF23 ELLIPSE 20.0 #ffcccc -178.94 646.11 0.0 -163 MET ELLIPSE 20.0 #ffcccc -24.55 788.5 0.0 -164 KDR ELLIPSE 20.0 #ffcccc -223.35 819.77 0.0 -165 FGFR1 ELLIPSE 20.0 #ffcccc -180.7 738.99 0.0 -166 SLC35B1 ELLIPSE 20.0 #ffcccc 630.9 243.92 0.0 -167 TFG ELLIPSE 20.0 #ffcccc 601.53 -147.67 0.0 -168 GRIA1 ELLIPSE 20.0 #ffcccc 514.81 -58.83 0.0 -169 ACVR2A ELLIPSE 20.0 #ffcccc 104.26 1479.42 0.0 -170 MAGI2 ELLIPSE 20.0 #ffcccc 93.52 1238.44 0.0 -171 TWIST1 ELLIPSE 20.0 #ffcccc -95.22 788.59 0.0 -172 FOXO3 ELLIPSE 20.0 #ffcccc -158.06 865.26 0.0 -173 PLA2G12A ELLIPSE 20.0 #ffcccc 971.22 792.9 0.0 -174 PEDS1-UBE2V1 ELLIPSE 20.0 #ffcccc 743.95 698.69 0.0 -175 PLD4 ELLIPSE 20.0 #ffcccc 880.22 785.73 0.0 -176 PLD3 ELLIPSE 20.0 #ffcccc 938.07 853.85 0.0 -177 LPCAT1 ELLIPSE 20.0 #ffcccc 1047.64 848.59 0.0 -178 SNRPA ELLIPSE 20.0 #ffcccc -574.27 -244.76 0.0 -179 MFAP1 ELLIPSE 20.0 #ffcccc -577.14 -196.35 0.0 -180 HNRNPA3 ELLIPSE 20.0 #ffcccc -534.15 -100.72 0.0 -181 MBNL2 ELLIPSE 20.0 #ffcccc -684.44 -622.04 0.0 -182 FMC1-LUC7L2 ELLIPSE 20.0 #ffcccc -684.51 -486.33 0.0 -183 CTNNBL1 ELLIPSE 20.0 #ffcccc -445.23 -179.6 0.0 -184 FUBP1 ELLIPSE 20.0 #ffcccc -555.03 -64.46 0.0 -185 HNRNPA1 ELLIPSE 20.0 #ffcccc -502.11 1.64 0.0 -186 RBM17 ELLIPSE 20.0 #ffcccc -486.54 -368.44 0.0 -187 SF1 ELLIPSE 20.0 #ffcccc -537.95 -217.15 0.0 -188 SFPQ ELLIPSE 20.0 #ffcccc -419.46 -124.53 0.0 -189 SART1 ELLIPSE 20.0 #ffcccc -641.45 -363.58 0.0 -190 SF3B5 ELLIPSE 20.0 #ffcccc -670.38 -137.05 0.0 -191 SNRPB2 ELLIPSE 20.0 #ffcccc -618.06 -273.76 0.0 -192 ATP5F1E ELLIPSE 20.0 #ffcccc -895.75 229.43 0.0 -193 MT-CO3 ELLIPSE 20.0 #ffcccc -1099.23 126.5 0.0 -194 PPA2 ELLIPSE 20.0 #ffcccc -1088.49 531.2 0.0 -195 UQCR11 ELLIPSE 20.0 #ffcccc -1067.87 183.05 0.0 -196 NDUFB2 ELLIPSE 20.0 #ffcccc -943.76 124.45 0.0 -197 COX6C ELLIPSE 20.0 #ffcccc -1030.7 95.87 0.0 -198 COX7C ELLIPSE 20.0 #ffcccc -746.18 121.49 0.0 -199 CLPP ELLIPSE 20.0 #ffcccc -1501.41 -67.07 0.0 -200 DNAJC8 ELLIPSE 20.0 #ffcccc -498.07 -312.41 0.0 -201 HTATSF1 ELLIPSE 20.0 #ffcccc -768.73 -416.11 0.0 -202 DDX46 ELLIPSE 20.0 #ffcccc -679.14 -392.08 0.0 -203 RAB40A ELLIPSE 20.0 #ffcccc -523.68 618.43 0.0 -204 RAB8B ELLIPSE 20.0 #ffcccc 87.23 799.16 0.0 -205 CCT3 ELLIPSE 20.0 #ffcccc -314.18 -25.23 0.0 -206 HLA-DRA ELLIPSE 20.0 #ffcccc 249.25 406.39 0.0 -207 KCNH2 ELLIPSE 20.0 #ffcccc -537.66 320.11 0.0 -208 PIN1 ELLIPSE 20.0 #ffcccc -217.32 562.25 0.0 -209 NCOR2 ELLIPSE 20.0 #ffcccc -322.34 623.59 0.0 -210 PPP2R5A ELLIPSE 20.0 #ffcccc -2.39 585.36 0.0 -211 PRKCD ELLIPSE 20.0 #ffcccc -265.33 779.62 0.0 -212 AXIN1 ELLIPSE 20.0 #ffcccc -124.18 645.8 0.0 -213 IRF3 ELLIPSE 20.0 #ffcccc -144.55 435.93 0.0 -214 JPT2 ELLIPSE 20.0 #ffcccc 292.0 -366.88 0.0 -215 STMN1 ELLIPSE 20.0 #ffcccc 52.83 -136.77 0.0 -216 MAP2K3 ELLIPSE 20.0 #ffcccc 110.18 610.62 0.0 -217 SIPA1L2 ELLIPSE 20.0 #ffcccc 507.75 1035.82 0.0 -218 BDNF ELLIPSE 20.0 #ffcccc -89.66 897.5 0.0 -219 SLX1A ELLIPSE 20.0 #ffcccc -739.57 915.35 0.0 -220 ERCC4 ELLIPSE 20.0 #ffcccc -550.31 553.85 0.0 -221 TUBG2 ELLIPSE 20.0 #ffcccc 1.45 -499.79 0.0 -222 TOPORS ELLIPSE 20.0 #ffcccc 126.35 -531.26 0.0 -223 BLOC1S2 ELLIPSE 20.0 #ffcccc 18.76 -618.87 0.0 -224 KIFC1 ELLIPSE 20.0 #ffcccc 192.42 -325.97 0.0 -225 NME7 ELLIPSE 20.0 #ffcccc -246.25 -467.49 0.0 -226 CIAO3 ELLIPSE 20.0 #ffcccc 1823.11 -100.05 0.0 -227 CIAO2A ELLIPSE 20.0 #ffcccc 1765.2 -180.64 0.0 -228 MLLT6 ELLIPSE 20.0 #ffcccc 479.78 344.95 0.0 -229 ZC3H4 ELLIPSE 20.0 #ffcccc -391.98 -621.77 0.0 -230 CLP1 ELLIPSE 20.0 #ffcccc -407.44 -223.42 0.0 -231 DFFA ELLIPSE 20.0 #ffcccc -275.99 -345.67 0.0 -232 MYSM1 ELLIPSE 20.0 #ffcccc -320.65 481.01 0.0 -233 MPND ELLIPSE 20.0 #ffcccc -341.39 377.47 0.0 -234 CCT8 ELLIPSE 20.0 #ffcccc -296.71 48.13 0.0 -235 EIF6 ELLIPSE 20.0 #ffcccc -458.53 35.41 0.0 -236 EIF4A1 ELLIPSE 20.0 #ffcccc -375.12 18.21 0.0 -237 FUS ELLIPSE 20.0 #ffcccc -551.96 74.89 0.0 -238 LARP1 ELLIPSE 20.0 #ffcccc -400.03 -41.46 0.0 -239 ARID1A ELLIPSE 20.0 #ffcccc -347.87 445.27 0.0 -240 DHX30 ELLIPSE 20.0 #ffcccc -745.29 -205.83 0.0 -241 HNRNPA1L2 ELLIPSE 20.0 #ffcccc -623.66 -198.44 0.0 -242 RXRA ELLIPSE 20.0 #ffcccc -507.58 566.14 0.0 -243 SAFB ELLIPSE 20.0 #ffcccc -427.19 -71.5 0.0 -244 SMARCA4 ELLIPSE 20.0 #ffcccc -400.24 362.53 0.0 -245 IARS2 ELLIPSE 20.0 #ffcccc -1141.02 -166.69 0.0 -246 H3-3A ELLIPSE 20.0 #ffcccc -735.16 544.72 0.0 -247 FBXL19 ELLIPSE 20.0 #ffcccc -634.27 600.78 0.0 -248 SUV39H1 ELLIPSE 20.0 #ffcccc -676.86 560.85 0.0 -249 TONSL ELLIPSE 20.0 #ffcccc -957.03 602.71 0.0 -250 SGF29 ELLIPSE 20.0 #ffcccc -757.03 314.2 0.0 -251 ING1 ELLIPSE 20.0 #ffcccc -1013.98 836.37 0.0 -252 UBN1 ELLIPSE 20.0 #ffcccc -1032.93 777.54 0.0 -253 SETDB1 ELLIPSE 20.0 #ffcccc -836.41 678.34 0.0 -254 H2BC8 ELLIPSE 20.0 #ffcccc -505.25 453.05 0.0 -255 CARM1 ELLIPSE 20.0 #ffcccc -492.36 683.14 0.0 -256 H2AC8 ELLIPSE 20.0 #ffcccc -757.85 407.74 0.0 -257 BRD8 ELLIPSE 20.0 #ffcccc -673.88 510.15 0.0 -258 TP63 ELLIPSE 20.0 #ffcccc -458.37 629.39 0.0 -259 DERPC ELLIPSE 20.0 #ffcccc 376.13 -114.16 0.0 -260 WRAP53 ELLIPSE 20.0 #ffcccc -10.93 -55.45 0.0 -261 PPP6R3 ELLIPSE 20.0 #ffcccc 243.03 -113.82 0.0 -262 BTG1 ELLIPSE 20.0 #ffcccc -65.56 1185.9 0.0 -263 CCNJ ELLIPSE 20.0 #ffcccc 104.07 -20.34 0.0 -264 DNMT1 ELLIPSE 20.0 #ffcccc -511.48 406.84 0.0 -265 PRKDC ELLIPSE 20.0 #ffcccc -317.8 281.59 0.0 -266 CNPPD1 ELLIPSE 20.0 #ffcccc 142.95 67.76 0.0 -267 STIL ELLIPSE 20.0 #ffcccc 103.96 -95.77 0.0 -268 CDK17 ELLIPSE 20.0 #ffcccc 155.37 1.04 0.0 -269 UBE2E1 ELLIPSE 20.0 #ffcccc -125.97 268.57 0.0 -270 RCC1 ELLIPSE 20.0 #ffcccc -725.29 277.94 0.0 -271 CENPU ELLIPSE 20.0 #ffcccc 11.99 -9.35 0.0 -272 SKA3 ELLIPSE 20.0 #ffcccc 166.26 -112.29 0.0 -273 CEP55 ELLIPSE 20.0 #ffcccc 27.84 -209.66 0.0 -274 LIN9 ELLIPSE 20.0 #ffcccc 92.58 30.63 0.0 -275 CCNE1 ELLIPSE 20.0 #ffcccc -88.23 162.77 0.0 -276 TOP2A ELLIPSE 20.0 #ffcccc -20.22 79.7 0.0 -277 ARHGAP9 ELLIPSE 20.0 #ffcccc 986.04 514.46 0.0 -278 CD247 ELLIPSE 20.0 #ffcccc 517.11 550.45 0.0 -279 OASL ELLIPSE 20.0 #ffcccc -395.62 268.8 0.0 -280 IFITM1 ELLIPSE 20.0 #ffcccc -141.52 552.5 0.0 -281 LMO2 ELLIPSE 20.0 #ffcccc -327.4 -206.84 0.0 -282 MAPRE2 ELLIPSE 20.0 #ffcccc -97.57 -182.51 0.0 -283 HTRA2 ELLIPSE 20.0 #ffcccc 464.37 641.46 0.0 -284 TRAF3 ELLIPSE 20.0 #ffcccc 176.98 517.41 0.0 -285 COG3 ELLIPSE 20.0 #ffcccc 713.09 65.31 0.0 -286 COPZ1 ELLIPSE 20.0 #ffcccc 1046.86 25.22 0.0 -287 TBRG4 ELLIPSE 20.0 #ffcccc -996.07 -488.98 0.0 -288 MARCHF7 ELLIPSE 20.0 #ffcccc -685.86 -788.31 0.0 -289 PCNP ELLIPSE 20.0 #ffcccc -608.31 -461.39 0.0 -290 BLK ELLIPSE 20.0 #ffcccc -235.97 1046.38 0.0 -291 EFNA5 ELLIPSE 20.0 #ffcccc -152.69 952.11 0.0 -292 RASA1 ELLIPSE 20.0 #ffcccc -262.76 872.48 0.0 -293 DERL1 ELLIPSE 20.0 #ffcccc -112.47 330.97 0.0 -294 UBXN1 ELLIPSE 20.0 #ffcccc -91.52 216.89 0.0 -295 RNF139 ELLIPSE 20.0 #ffcccc -114.52 471.47 0.0 -296 NGLY1 ELLIPSE 20.0 #ffcccc 21.66 360.87 0.0 -297 HINT2 ELLIPSE 20.0 #ffcccc -961.49 0.01 0.0 -298 RIPK1 ELLIPSE 20.0 #ffcccc -24.0 467.83 0.0 -299 MAP4K2 ELLIPSE 20.0 #ffcccc 267.76 654.0 0.0 -300 UBE2V1 ELLIPSE 20.0 #ffcccc -45.92 395.21 0.0 -301 IKBKG ELLIPSE 20.0 #ffcccc -46.96 532.37 0.0 -302 CHRNA1 ELLIPSE 20.0 #ffcccc 221.97 -992.49 0.0 -303 CHRM1 ELLIPSE 20.0 #ffcccc 278.94 -837.28 0.0 -304 CACNG8 ELLIPSE 20.0 #ffcccc 618.52 91.9 0.0 -305 WNT8A ELLIPSE 20.0 #ffcccc -3.36 866.61 0.0 -306 DVL1 ELLIPSE 20.0 #ffcccc -131.39 750.81 0.0 -307 PPP4R4 ELLIPSE 20.0 #ffcccc 347.78 935.66 0.0 -308 USP22 ELLIPSE 20.0 #ffcccc -565.76 386.87 0.0 -309 SAP130 ELLIPSE 20.0 #ffcccc -684.38 433.4 0.0 -310 KCNAB1 ELLIPSE 20.0 #ffcccc -813.1 291.93 0.0 -311 KCNQ4 ELLIPSE 20.0 #ffcccc -553.32 212.79 0.0 -312 SCPEP1 ELLIPSE 20.0 #ffcccc -1390.49 591.36 0.0 -313 GAPVD1 ELLIPSE 20.0 #ffcccc 32.38 967.04 0.0 -314 FBXO6 ELLIPSE 20.0 #ffcccc -93.85 -92.97 0.0 -315 GBA1 ELLIPSE 20.0 #ffcccc -76.33 -44.98 0.0 -316 FKBP9 ELLIPSE 20.0 #ffcccc -148.39 -57.82 0.0 -317 PCBP4 ELLIPSE 20.0 #ffcccc 109.04 726.43 0.0 -318 DNAJC5G ELLIPSE 20.0 #ffcccc -1010.42 -677.28 0.0 -319 ITGAE ELLIPSE 20.0 #ffcccc 321.91 819.09 0.0 -320 ITGA9 ELLIPSE 20.0 #ffcccc 426.91 791.68 0.0 -321 MED15 ELLIPSE 20.0 #ffcccc -795.46 573.36 0.0 -322 ANGPTL4 ELLIPSE 20.0 #ffcccc -667.9 760.63 0.0 -323 UNK ELLIPSE 20.0 #ffcccc -213.97 438.57 0.0 -324 ANP32B ELLIPSE 20.0 #ffcccc 65.16 144.32 0.0 -325 MYO9B ELLIPSE 20.0 #ffcccc 463.84 489.29 0.0 -326 AP2S1 ELLIPSE 20.0 #ffcccc 212.42 211.34 0.0 -327 BAIAP2L2 ELLIPSE 20.0 #ffcccc 436.56 98.02 0.0 -328 SGIP1 ELLIPSE 20.0 #ffcccc 476.04 158.37 0.0 -329 AP1B1 ELLIPSE 20.0 #ffcccc 141.22 195.23 0.0 -330 AP2A1 ELLIPSE 20.0 #ffcccc 265.41 177.42 0.0 -331 WDR76 ELLIPSE 20.0 #ffcccc -182.39 -426.84 0.0 -332 GABARAP ELLIPSE 20.0 #ffcccc -678.67 951.22 0.0 -333 PLCB4 ELLIPSE 20.0 #ffcccc -145.62 1002.2 0.0 -334 KIF1B ELLIPSE 20.0 #ffcccc 366.26 -538.17 0.0 -335 KIF3C ELLIPSE 20.0 #ffcccc 450.41 -561.15 0.0 -336 KIF5A ELLIPSE 20.0 #ffcccc 482.89 -487.05 0.0 -337 KLC2 ELLIPSE 20.0 #ffcccc 402.0 -471.99 0.0 -338 IFT46 ELLIPSE 20.0 #ffcccc 432.98 -648.89 0.0 -339 CPSF7 ELLIPSE 20.0 #ffcccc -641.81 -308.07 0.0 -340 SRSF5 ELLIPSE 20.0 #ffcccc -462.99 -271.19 0.0 -341 GAS8 ELLIPSE 20.0 #ffcccc -862.58 1092.79 0.0 -342 FLNC ELLIPSE 20.0 #ffcccc 635.36 956.01 0.0 -343 SRP9 ELLIPSE 20.0 #ffcccc -497.63 58.11 0.0 -344 ALDH8A1 ELLIPSE 20.0 #ffcccc -624.41 1526.4 0.0 -345 ANG ELLIPSE 20.0 #ffcccc -588.52 1307.57 0.0 -346 ZCRB1 ELLIPSE 20.0 #ffcccc -735.09 5.72 0.0 -347 SNRNP25 ELLIPSE 20.0 #ffcccc -850.48 -39.65 0.0 -348 TMEM19 ELLIPSE 20.0 #ffcccc 1683.35 -376.41 0.0 -349 BSCL2 ELLIPSE 20.0 #ffcccc 1625.83 -294.62 0.0 -350 UBE2Q2 ELLIPSE 20.0 #ffcccc -98.33 405.89 0.0 -351 UBE2G1 ELLIPSE 20.0 #ffcccc -124.51 367.9 0.0 -352 UBE2F ELLIPSE 20.0 #ffcccc 35.74 411.93 0.0 -353 UBE2E2 ELLIPSE 20.0 #ffcccc -72.63 344.11 0.0 -354 UBE2A ELLIPSE 20.0 #ffcccc -189.86 300.05 0.0 -355 SEPTIN12 ELLIPSE 20.0 #ffcccc 1634.7 -459.12 0.0 -356 TMEM250 ELLIPSE 20.0 #ffcccc 1708.11 -533.87 0.0 -357 SEPTIN9 ELLIPSE 20.0 #ffcccc 1607.92 -560.85 0.0 -358 CISD2 ELLIPSE 20.0 #ffcccc -1347.82 59.48 0.0 -359 SLC25A45 ELLIPSE 20.0 #ffcccc -1242.96 -146.51 0.0 -360 PARK7 ELLIPSE 20.0 #ffcccc -455.75 266.77 0.0 -361 APOBEC3G ELLIPSE 20.0 #ffcccc -944.2 209.06 0.0 -362 CHCHD6 ELLIPSE 20.0 #ffcccc -1086.52 -176.09 0.0 -363 SDHD ELLIPSE 20.0 #ffcccc -1245.94 39.37 0.0 -364 TIMMDC1 ELLIPSE 20.0 #ffcccc -1196.41 99.17 0.0 -365 CFAP45 ELLIPSE 20.0 #ffcccc -1099.31 1204.49 0.0 -366 CBX8 ELLIPSE 20.0 #ffcccc -847.75 402.77 0.0 -367 H1-10 ELLIPSE 20.0 #ffcccc -1023.88 495.96 0.0 -368 JARID2 ELLIPSE 20.0 #ffcccc -835.44 545.24 0.0 -369 CASP8AP2 ELLIPSE 20.0 #ffcccc -1123.51 470.87 0.0 -370 CETN2 ELLIPSE 20.0 #ffcccc -616.65 494.07 0.0 -371 PHC1 ELLIPSE 20.0 #ffcccc -914.62 442.65 0.0 -372 CCDC97 ELLIPSE 20.0 #ffcccc -920.98 -428.42 0.0 -373 SCYL1 ELLIPSE 20.0 #ffcccc 1215.19 50.32 0.0 -374 CACNA1G ELLIPSE 20.0 #ffcccc 983.73 -126.32 0.0 -375 GRID2 ELLIPSE 20.0 #ffcccc 708.94 -82.63 0.0 -376 EPB41L1 ELLIPSE 20.0 #ffcccc 732.98 -29.72 0.0 -377 PRCC ELLIPSE 20.0 #ffcccc -675.93 -875.59 0.0 -378 RBM10 ELLIPSE 20.0 #ffcccc -607.75 -564.74 0.0 -379 FANCF ELLIPSE 20.0 #ffcccc -409.86 555.53 0.0 -380 EGLN1 ELLIPSE 20.0 #ffcccc -741.05 477.79 0.0 -381 CHMP7 ELLIPSE 20.0 #ffcccc -428.27 503.25 0.0 -382 CHMP6 ELLIPSE 20.0 #ffcccc -475.72 504.99 0.0 -383 GTF2H2 ELLIPSE 20.0 #ffcccc -566.3 441.83 0.0 -384 COMMD6 ELLIPSE 20.0 #ffcccc -557.27 694.0 0.0 -385 TRIM32 ELLIPSE 20.0 #ffcccc -160.83 391.57 0.0 -386 BUB3 ELLIPSE 20.0 #ffcccc -256.76 -31.66 0.0 -387 GPS1 ELLIPSE 20.0 #ffcccc -454.27 448.88 0.0 -388 ELOC ELLIPSE 20.0 #ffcccc -623.69 455.52 0.0 -389 RPP40 ELLIPSE 20.0 #ffcccc -287.62 84.19 0.0 -390 SPRED3 ELLIPSE 20.0 #ffcccc -278.07 649.87 0.0 -391 KLHL12 ELLIPSE 20.0 #ffcccc -358.7 787.16 0.0 -392 LGR6 ELLIPSE 20.0 #ffcccc -165.59 505.39 0.0 -393 XRCC3 ELLIPSE 20.0 #ffcccc -11.23 328.31 0.0 -394 JOSD2 ELLIPSE 20.0 #ffcccc -217.58 500.87 0.0 -395 ANXA6 ELLIPSE 20.0 #ffcccc -299.94 1199.91 0.0 -396 GPR174 ELLIPSE 20.0 #ffcccc 662.33 731.19 0.0 -397 INPPL1 ELLIPSE 20.0 #ffcccc 410.76 863.49 0.0 -398 P2RX7 ELLIPSE 20.0 #ffcccc 826.89 891.08 0.0 -399 CD40LG ELLIPSE 20.0 #ffcccc 540.77 649.33 0.0 -400 GRAP2 ELLIPSE 20.0 #ffcccc 571.77 491.77 0.0 -401 GNRH1 ELLIPSE 20.0 #ffcccc 380.45 -1094.33 0.0 -402 CCK ELLIPSE 20.0 #ffcccc 396.41 -942.94 0.0 -403 EDN3 ELLIPSE 20.0 #ffcccc 314.25 -1004.38 0.0 -404 LIN7C ELLIPSE 20.0 #ffcccc 758.0 -984.35 0.0 -405 SYN1 ELLIPSE 20.0 #ffcccc 651.68 -911.09 0.0 -406 HSD17B12 ELLIPSE 20.0 #ffcccc -990.53 -239.08 0.0 -407 DNAJC1 ELLIPSE 20.0 #ffcccc -232.15 96.99 0.0 -408 GSPT2 ELLIPSE 20.0 #ffcccc -317.04 -83.0 0.0 -409 TM7SF2 ELLIPSE 20.0 #ffcccc 1357.53 -2853.57 0.0 -410 DHCR24 ELLIPSE 20.0 #ffcccc 1386.83 -2751.1 0.0 -411 ITM2B ELLIPSE 20.0 #ffcccc 383.53 402.63 0.0 -412 DONSON ELLIPSE 20.0 #ffcccc 153.89 -165.18 0.0 -413 NBAS ELLIPSE 20.0 #ffcccc 1209.84 -29.9 0.0 -414 SETBP1 ELLIPSE 20.0 #ffcccc -848.41 944.83 0.0 -415 ADAMTS18 ELLIPSE 20.0 #ffcccc 1471.0 249.48 0.0 -416 ADAMTS3 ELLIPSE 20.0 #ffcccc 1573.78 235.98 0.0 -417 ADAMTSL2 ELLIPSE 20.0 #ffcccc 1534.97 331.72 0.0 -418 SCN3A ELLIPSE 20.0 #ffcccc 1134.92 -162.24 0.0 -419 SCN3B ELLIPSE 20.0 #ffcccc 1163.38 -233.54 0.0 -420 SCN1B ELLIPSE 20.0 #ffcccc 1084.62 -249.37 0.0 -421 PLA2G4E ELLIPSE 20.0 #ffcccc 969.96 746.43 0.0 -422 ABCA6 ELLIPSE 20.0 #ffcccc -178.8 1188.82 0.0 -423 ODF1 ELLIPSE 20.0 #ffcccc -113.55 -398.3 0.0 -424 BRIX1 ELLIPSE 20.0 #ffcccc -370.56 -1.0 0.0 -425 TSC22D1 ELLIPSE 20.0 #ffcccc 527.88 1685.35 0.0 -426 SLC6A1 ELLIPSE 20.0 #ffcccc 559.13 -879.37 0.0 -427 CPNE6 ELLIPSE 20.0 #ffcccc 446.34 -850.97 0.0 -428 SNCB ELLIPSE 20.0 #ffcccc 489.26 -777.33 0.0 -429 LY6H ELLIPSE 20.0 #ffcccc 514.8 -950.19 0.0 -430 SYNPR ELLIPSE 20.0 #ffcccc 463.28 -906.72 0.0 -431 GPC2 ELLIPSE 20.0 #ffcccc 1439.41 -455.41 0.0 -432 HS3ST4 ELLIPSE 20.0 #ffcccc 1538.41 -425.22 0.0 -433 TAMALIN ELLIPSE 20.0 #ffcccc -54.73 -3002.12 0.0 -434 MARCHF2 ELLIPSE 20.0 #ffcccc -111.81 -2915.62 0.0 -435 NCL ELLIPSE 20.0 #ffcccc -358.91 -36.72 0.0 -436 UBXN6 ELLIPSE 20.0 #ffcccc 13.3 -283.55 0.0 -437 TRAPPC9 ELLIPSE 20.0 #ffcccc 584.72 -6.18 0.0 -438 DNAI3 ELLIPSE 20.0 #ffcccc -1386.84 1602.48 0.0 -439 CCDC114 ELLIPSE 20.0 #ffcccc -1306.88 1286.89 0.0 -440 FABP1 ELLIPSE 20.0 #ffcccc -500.64 899.08 0.0 -441 RGL1 ELLIPSE 20.0 #ffcccc -578.92 853.18 0.0 -442 CHD9 ELLIPSE 20.0 #ffcccc -508.81 745.51 0.0 -443 ADH5 ELLIPSE 20.0 #ffcccc -1966.95 314.33 0.0 -444 NOL10 ELLIPSE 20.0 #ffcccc -302.19 6.75 0.0 -445 NKD2 ELLIPSE 20.0 #ffcccc -75.29 1089.86 0.0 -446 RP9 ELLIPSE 20.0 #ffcccc -781.89 -698.68 0.0 -447 RPP25L ELLIPSE 20.0 #ffcccc -204.84 -97.44 0.0 -448 PRDX3 ELLIPSE 20.0 #ffcccc -1119.41 -52.8 0.0 -449 CKB ELLIPSE 20.0 #ffcccc -766.85 207.79 0.0 -450 ALDOA ELLIPSE 20.0 #ffcccc -689.6 201.15 0.0 -451 RNF214 ELLIPSE 20.0 #ffcccc 4920.51 367.34 0.0 -452 SMG8 ELLIPSE 20.0 #ffcccc 4829.13 415.96 0.0 -453 NABP1 ELLIPSE 20.0 #ffcccc -1047.62 303.07 0.0 -454 TMEM256 ELLIPSE 20.0 #ffcccc -1356.88 -103.81 0.0 -455 RAB29 ELLIPSE 20.0 #ffcccc -1464.03 -125.37 0.0 -456 TMEM14C ELLIPSE 20.0 #ffcccc -1355.44 -190.38 0.0 -457 TPST1 ELLIPSE 20.0 #ffcccc 690.52 -2926.02 0.0 -458 EIF2B1 ELLIPSE 20.0 #ffcccc 638.2 -3015.99 0.0 -459 OR52A5 ELLIPSE 20.0 #ffcccc -78.11 -850.71 0.0 -460 GNAL ELLIPSE 20.0 #ffcccc 4.07 -733.22 0.0 -461 OAZ1 ELLIPSE 20.0 #ffcccc -237.51 682.85 0.0 -462 SRP72 ELLIPSE 20.0 #ffcccc -628.06 114.07 0.0 -463 PBDC1 ELLIPSE 20.0 #ffcccc -791.57 -100.67 0.0 -464 LCMT2 ELLIPSE 20.0 #ffcccc 522.83 1137.87 0.0 -465 LPAR4 ELLIPSE 20.0 #ffcccc 163.54 -830.83 0.0 -466 GMPPA ELLIPSE 20.0 #ffcccc -805.0 1347.64 0.0 -467 FNIP1 ELLIPSE 20.0 #ffcccc -1108.72 794.41 0.0 -468 TBC1D25 ELLIPSE 20.0 #ffcccc -848.8 1197.4 0.0 -469 ATG5 ELLIPSE 20.0 #ffcccc -767.97 1222.51 0.0 -470 VSNL1 ELLIPSE 20.0 #ffcccc 587.36 -731.89 0.0 -471 CEND1 ELLIPSE 20.0 #ffcccc 603.51 -807.59 0.0 -472 TYW1B ELLIPSE 20.0 #ffcccc -26.75 -346.42 0.0 -473 FTSJ1 ELLIPSE 20.0 #ffcccc -270.75 -173.16 0.0 -474 PUS7L ELLIPSE 20.0 #ffcccc -229.25 -159.5 0.0 -475 DPH5 ELLIPSE 20.0 #ffcccc -156.79 7.54 0.0 -476 ELP2 ELLIPSE 20.0 #ffcccc -126.85 -233.48 0.0 -477 DDX24 ELLIPSE 20.0 #ffcccc -254.28 -74.11 0.0 -478 B4GAT1 ELLIPSE 20.0 #ffcccc 1513.79 -252.17 0.0 -479 PRELP ELLIPSE 20.0 #ffcccc 1590.31 -175.91 0.0 -480 LARGE2 ELLIPSE 20.0 #ffcccc 1438.77 -326.64 0.0 -481 RHNO1 ELLIPSE 20.0 #ffcccc -786.47 870.73 0.0 -482 RPH3A ELLIPSE 20.0 #ffcccc 255.57 1075.48 0.0 -483 KCTD2 ELLIPSE 20.0 #ffcccc -482.67 1119.02 0.0 -484 KLHL2 ELLIPSE 20.0 #ffcccc -518.68 999.36 0.0 -485 ATAD5 ELLIPSE 20.0 #ffcccc 228.92 271.1 0.0 -486 DLGAP1 ELLIPSE 20.0 #ffcccc 175.04 1464.42 0.0 -487 RAB4B ELLIPSE 20.0 #ffcccc 91.28 1088.8 0.0 -488 CFAP299 ELLIPSE 20.0 #ffcccc -1140.87 1366.33 0.0 -489 ECT2L ELLIPSE 20.0 #ffcccc 427.32 -292.97 0.0 -490 B3GNT4 ELLIPSE 20.0 #ffcccc 1665.18 -101.31 0.0 -491 KDM3A ELLIPSE 20.0 #ffcccc -278.4 588.33 0.0 -492 GTF3A ELLIPSE 20.0 #ffcccc -386.22 626.23 0.0 -493 PELI3 ELLIPSE 20.0 #ffcccc 162.29 584.42 0.0 -494 OR10K2 ELLIPSE 20.0 #ffcccc 83.59 -864.42 0.0 -495 PHF21B ELLIPSE 20.0 #ffcccc -552.84 779.12 0.0 -496 RTN4IP1 ELLIPSE 20.0 #ffcccc 458.29 258.23 0.0 -497 SRPK3 ELLIPSE 20.0 #ffcccc -502.31 -479.67 0.0 -498 PRKCH ELLIPSE 20.0 #ffcccc -291.94 1519.81 0.0 -499 ADRA2B ELLIPSE 20.0 #ffcccc -283.04 1272.3 0.0 -500 ATP11C ELLIPSE 20.0 #ffcccc 1588.46 38.64 0.0 -501 TENM1 ELLIPSE 20.0 #ffcccc 1536.75 -49.59 0.0 -502 OR3A2 ELLIPSE 20.0 #ffcccc -125.85 -802.98 0.0 -503 OR11G2 ELLIPSE 20.0 #ffcccc -29.94 -879.54 0.0 -504 OR2T7 ELLIPSE 20.0 #ffcccc 29.62 -884.97 0.0 -505 TRAPPC11 ELLIPSE 20.0 #ffcccc 800.87 -132.57 0.0 -506 LIPA ELLIPSE 20.0 #ffcccc 1424.5 -2652.47 0.0 -507 EBAG9 ELLIPSE 20.0 #ffcccc -35.49 705.69 0.0 -508 ADA ELLIPSE 20.0 #ffcccc -174.99 -139.57 0.0 -509 ZNF385A ELLIPSE 20.0 #ffcccc 305.48 995.22 0.0 -510 IFNAR2 ELLIPSE 20.0 #ffcccc 265.92 345.39 0.0 -511 TREM2 ELLIPSE 20.0 #ffcccc 826.95 472.66 0.0 -512 ARL4C ELLIPSE 20.0 #ffcccc -464.87 782.74 0.0 -513 TNRC6B ELLIPSE 20.0 #ffcccc -388.19 724.82 0.0 -514 AGO4 ELLIPSE 20.0 #ffcccc -367.03 490.07 0.0 -515 CDH18 ELLIPSE 20.0 #ffcccc 139.37 890.55 0.0 -516 ADGRA2 ELLIPSE 20.0 #ffcccc 94.22 946.2 0.0 -517 CRYAB ELLIPSE 20.0 #ffcccc 108.66 529.92 0.0 -518 MAP3K15 ELLIPSE 20.0 #ffcccc 966.02 622.33 0.0 -519 TNFSF13B ELLIPSE 20.0 #ffcccc 648.98 598.03 0.0 -520 STIM2 ELLIPSE 20.0 #ffcccc 1160.07 642.18 0.0 -521 LRRC41 ELLIPSE 20.0 #ffcccc -743.52 765.77 0.0 -522 BTBD6 ELLIPSE 20.0 #ffcccc -782.21 1106.95 0.0 -523 ARID5A ELLIPSE 20.0 #ffcccc -630.0 710.83 0.0 -524 DPM3 ELLIPSE 20.0 #ffcccc -868.85 1583.89 0.0 -525 ETS2 ELLIPSE 20.0 #ffcccc -405.25 863.21 0.0 -526 COA3 ELLIPSE 20.0 #ffcccc -1382.2 170.47 0.0 -527 COX14 ELLIPSE 20.0 #ffcccc -1233.32 160.61 0.0 -528 COX7B2 ELLIPSE 20.0 #ffcccc -1061.27 57.5 0.0 -529 NTPCR ELLIPSE 20.0 #ffcccc -370.59 -466.8 0.0 -530 DYRK1B ELLIPSE 20.0 #ffcccc 667.49 1195.57 0.0 -531 EGLN2 ELLIPSE 20.0 #ffcccc -1059.51 694.7 0.0 -532 VARS2 ELLIPSE 20.0 #ffcccc -1021.66 -181.25 0.0 -533 SMIM20 ELLIPSE 20.0 #ffcccc -876.02 -488.09 0.0 -534 NAXE ELLIPSE 20.0 #ffcccc 1467.31 -504.84 0.0 -535 GBE1 ELLIPSE 20.0 #ffcccc 1530.93 -585.56 0.0 -536 DOLPP1 ELLIPSE 20.0 #ffcccc -905.83 1732.78 0.0 -537 PI4KB ELLIPSE 20.0 #ffcccc -117.47 1323.8 0.0 -538 BCKDK ELLIPSE 20.0 #ffcccc -903.28 783.05 0.0 -539 TMED5 ELLIPSE 20.0 #ffcccc 59.45 1155.17 0.0 -540 WNT5B ELLIPSE 20.0 #ffcccc -3.1 1039.35 0.0 -541 ADGRL4 ELLIPSE 20.0 #ffcccc 1656.84 321.66 0.0 -542 CD63 ELLIPSE 20.0 #ffcccc 1737.63 264.0 0.0 -543 PLEKHG6 ELLIPSE 20.0 #ffcccc 183.56 -436.93 0.0 -544 FOXO6 ELLIPSE 20.0 #ffcccc -122.45 1209.79 0.0 -545 FOXP4 ELLIPSE 20.0 #ffcccc -1526.93 -2312.8 0.0 -546 FOXP2 ELLIPSE 20.0 #ffcccc -1449.27 -2375.33 0.0 -547 BAK1 ELLIPSE 20.0 #ffcccc -1037.07 -429.15 0.0 -548 LYPLA2 ELLIPSE 20.0 #ffcccc -1494.12 2.79 0.0 -549 KAZN ELLIPSE 20.0 #ffcccc 406.24 1163.51 0.0 -550 ERC1 ELLIPSE 20.0 #ffcccc 255.74 933.92 0.0 -551 SRM ELLIPSE 20.0 #ffcccc -621.43 -3.22 0.0 -552 TCOF1 ELLIPSE 20.0 #ffcccc 173.74 -245.45 0.0 -553 RAD54L2 ELLIPSE 20.0 #ffcccc -890.72 890.85 0.0 -554 C7orf50 ELLIPSE 20.0 #ffcccc -191.38 -275.47 0.0 -555 ZRSR2P1 ELLIPSE 20.0 #ffcccc -490.23 -725.97 0.0 -556 BTBD3 ELLIPSE 20.0 #ffcccc -927.86 1313.17 0.0 -557 CLDN3 ELLIPSE 20.0 #ffcccc 1436.95 -807.27 0.0 -558 CLDN2 ELLIPSE 20.0 #ffcccc 1519.17 -742.7 0.0 -559 CTSV ELLIPSE 20.0 #ffcccc 576.86 418.2 0.0 -560 SOCS4 ELLIPSE 20.0 #ffcccc -940.81 699.4 0.0 -561 GPX8 ELLIPSE 20.0 #ffcccc -1971.46 217.8 0.0 -562 NFIC ELLIPSE 20.0 #ffcccc -332.24 1113.28 0.0 -563 MAMLD1 ELLIPSE 20.0 #ffcccc -387.27 992.89 0.0 -564 ZNF638 ELLIPSE 20.0 #ffcccc -751.71 -2670.28 0.0 -565 SENP6 ELLIPSE 20.0 #ffcccc -824.3 -2602.69 0.0 -566 RWDD4 ELLIPSE 20.0 #ffcccc -895.47 -193.19 0.0 -567 ATP2B1 ELLIPSE 20.0 #ffcccc 37.45 707.27 0.0 -568 ZNF746 ELLIPSE 20.0 #ffcccc -189.29 -356.66 0.0 -569 HSPB6 ELLIPSE 20.0 #ffcccc 381.07 707.71 0.0 -570 CALU ELLIPSE 20.0 #ffcccc 1405.8 -594.06 0.0 -571 SARS2 ELLIPSE 20.0 #ffcccc 1470.02 -669.57 0.0 -572 CIC ELLIPSE 20.0 #ffcccc -965.79 907.27 0.0 +0 HSPB6 ELLIPSE 2.5 #ffcccc 496.75 683.82 0.0 +1 CRYAB ELLIPSE 2.5 #ffcccc 342.36 550.18 0.0 +2 TARBP1 ELLIPSE 2.5 #ffcccc 633.25 351.66 0.0 +3 BRIX1 ELLIPSE 2.5 #ffcccc 627.0 197.84 0.0 +4 DDX24 ELLIPSE 2.5 #ffcccc 681.49 177.02 0.0 +5 RPL26 ELLIPSE 2.5 #ffcccc 552.51 160.54 0.0 +6 RPL3 ELLIPSE 2.5 #ffcccc 509.95 124.3 0.0 +7 RPL13A ELLIPSE 2.5 #ffcccc 519.98 149.72 0.0 +8 RPL23 ELLIPSE 2.5 #ffcccc 538.14 85.03 0.0 +9 WDR3 ELLIPSE 2.5 #ffcccc 487.3 172.58 0.0 +10 PUS7L ELLIPSE 2.5 #ffcccc 472.13 330.16 0.0 +11 VAMP3 ELLIPSE 2.5 #ffcccc 412.52 -46.29 0.0 +12 BAIAP2L2 ELLIPSE 2.5 #ffcccc 204.48 -311.68 0.0 +13 FAM169A ELLIPSE 2.5 #ffcccc 73.31 59.37 0.0 +14 MYO9B ELLIPSE 2.5 #ffcccc 756.11 366.87 0.0 +15 PKN2 ELLIPSE 2.5 #ffcccc 937.28 39.21 0.0 +16 SGIP1 ELLIPSE 2.5 #ffcccc 125.02 -130.87 0.0 +17 RPS27A ELLIPSE 2.5 #ffcccc 615.57 33.37 0.0 +18 UBB ELLIPSE 2.5 #ffcccc 626.83 19.71 0.0 +19 AP2S1 ELLIPSE 2.5 #ffcccc 314.35 -227.4 0.0 +20 AP2A1 ELLIPSE 2.5 #ffcccc 203.23 -130.96 0.0 +21 VPS53 ELLIPSE 2.5 #ffcccc 935.48 145.85 0.0 +22 PICALM ELLIPSE 2.5 #ffcccc 388.37 -245.14 0.0 +23 SNAP47 ELLIPSE 2.5 #ffcccc -99.93 -78.59 0.0 +24 STX5 ELLIPSE 2.5 #ffcccc 197.61 -157.35 0.0 +25 PKP2 ELLIPSE 2.5 #ffcccc 1043.25 260.57 0.0 +26 BRD8 ELLIPSE 2.5 #ffcccc 870.25 151.45 0.0 +27 MRPS35 ELLIPSE 2.5 #ffcccc 712.68 21.06 0.0 +28 RPS15A ELLIPSE 2.5 #ffcccc 582.59 92.09 0.0 +29 HSPBP1 ELLIPSE 2.5 #ffcccc 454.44 115.2 0.0 +30 RPL10 ELLIPSE 2.5 #ffcccc 652.08 121.61 0.0 +31 RPL17-C18orf32 ELLIPSE 2.5 #ffcccc 635.53 179.34 0.0 +32 RPS14 ELLIPSE 2.5 #ffcccc 545.79 38.23 0.0 +33 MRPL51 ELLIPSE 2.5 #ffcccc 499.24 -204.14 0.0 +34 RPS23 ELLIPSE 2.5 #ffcccc 596.1 64.52 0.0 +35 MRPL33 ELLIPSE 2.5 #ffcccc 654.52 6.6 0.0 +36 MRPS18B ELLIPSE 2.5 #ffcccc 779.94 -109.39 0.0 +37 FAP ELLIPSE 2.5 #ffcccc -206.35 52.27 0.0 +38 THY1 ELLIPSE 2.5 #ffcccc -151.3 105.64 0.0 +39 PDRG1 ELLIPSE 2.5 #ffcccc 279.93 285.67 0.0 +40 HSPA8 ELLIPSE 2.5 #ffcccc 475.32 -8.42 0.0 +41 CCT3 ELLIPSE 2.5 #ffcccc 592.58 -7.56 0.0 +42 CCT8 ELLIPSE 2.5 #ffcccc 558.79 -20.07 0.0 +43 PFDN5 ELLIPSE 2.5 #ffcccc 424.85 130.43 0.0 +44 VCL ELLIPSE 2.5 #ffcccc 325.49 -182.78 0.0 +45 MANF ELLIPSE 2.5 #ffcccc 532.44 518.94 0.0 +46 TFG ELLIPSE 2.5 #ffcccc 55.92 20.94 0.0 +47 MYL7 ELLIPSE 2.5 #ffcccc 493.75 -598.73 0.0 +48 MYL12A ELLIPSE 2.5 #ffcccc 784.75 -567.38 0.0 +49 WDR1 ELLIPSE 2.5 #ffcccc 195.33 236.96 0.0 +50 RAP1B ELLIPSE 2.5 #ffcccc 122.38 -356.43 0.0 +51 ACTG1 ELLIPSE 2.5 #ffcccc 451.83 -265.46 0.0 +52 CTNNB1 ELLIPSE 2.5 #ffcccc 514.08 47.32 0.0 +53 TMED1 ELLIPSE 2.5 #ffcccc 222.25 526.13 0.0 +54 ZFPL1 ELLIPSE 2.5 #ffcccc 1150.94 6.13 0.0 +55 HSCB ELLIPSE 2.5 #ffcccc 579.7 -400.45 0.0 +56 SARS2 ELLIPSE 2.5 #ffcccc 237.86 -360.55 0.0 +57 PMPCA ELLIPSE 2.5 #ffcccc 215.51 -207.64 0.0 +58 IARS2 ELLIPSE 2.5 #ffcccc 519.6 -24.56 0.0 +59 TOMM40 ELLIPSE 2.5 #ffcccc 688.37 -512.59 0.0 +60 SDHB ELLIPSE 2.5 #ffcccc 373.29 -209.01 0.0 +61 ALKBH1 ELLIPSE 2.5 #ffcccc 912.32 211.97 0.0 +62 CLP1 ELLIPSE 2.5 #ffcccc 155.61 -181.96 0.0 +63 PNN ELLIPSE 2.5 #ffcccc 240.37 -225.31 0.0 +64 SNU13 ELLIPSE 2.5 #ffcccc 481.27 26.84 0.0 +65 RSRC2 ELLIPSE 2.5 #ffcccc 342.83 -673.66 0.0 +66 LSM2 ELLIPSE 2.5 #ffcccc 389.2 -140.96 0.0 +67 HNRNPM ELLIPSE 2.5 #ffcccc 306.49 18.67 0.0 +68 SART1 ELLIPSE 2.5 #ffcccc 189.98 -89.84 0.0 +69 FUS ELLIPSE 2.5 #ffcccc 361.93 -112.0 0.0 +70 HNRNPH3 ELLIPSE 2.5 #ffcccc 451.15 -65.22 0.0 +71 HNRNPA2B1 ELLIPSE 2.5 #ffcccc 370.74 24.16 0.0 +72 ARGLU1 ELLIPSE 2.5 #ffcccc -214.29 -31.88 0.0 +73 SNRPA ELLIPSE 2.5 #ffcccc 210.84 -21.54 0.0 +74 CASC3 ELLIPSE 2.5 #ffcccc 32.93 -146.12 0.0 +75 RNPS1 ELLIPSE 2.5 #ffcccc 246.94 -102.7 0.0 +76 ACOT8 ELLIPSE 2.5 #ffcccc 773.88 461.21 0.0 +77 STAG2 ELLIPSE 2.5 #ffcccc 569.69 -397.29 0.0 +78 JUND ELLIPSE 2.5 #ffcccc 414.39 -373.49 0.0 +79 CCNB1 ELLIPSE 2.5 #ffcccc 701.15 81.9 0.0 +80 H2AC8 ELLIPSE 2.5 #ffcccc 558.68 -162.1 0.0 +81 HIST1H2AC ELLIPSE 2.5 #ffcccc 583.13 -136.71 0.0 +82 TERF2 ELLIPSE 2.5 #ffcccc 512.61 -478.1 0.0 +83 ESR1 ELLIPSE 2.5 #ffcccc 445.94 -195.53 0.0 +84 SMC1A ELLIPSE 2.5 #ffcccc 651.57 -275.21 0.0 +85 CORO1A ELLIPSE 2.5 #ffcccc 877.2 191.0 0.0 +86 ITGAL ELLIPSE 2.5 #ffcccc 385.38 -489.37 0.0 +87 ARHGAP9 ELLIPSE 2.5 #ffcccc 709.26 617.96 0.0 +88 ACTR3 ELLIPSE 2.5 #ffcccc 385.3 181.68 0.0 +89 POC1A ELLIPSE 2.5 #ffcccc 777.24 274.1 0.0 +90 CAPN15 ELLIPSE 2.5 #ffcccc 782.02 498.09 0.0 +91 RNF126 ELLIPSE 2.5 #ffcccc 365.22 415.18 0.0 +92 MGA ELLIPSE 2.5 #ffcccc 228.15 110.92 0.0 +93 RNASEK-C17orf49 ELLIPSE 2.5 #ffcccc 718.08 614.74 0.0 +94 COG3 ELLIPSE 2.5 #ffcccc 523.12 -324.64 0.0 +95 CBX3 ELLIPSE 2.5 #ffcccc 687.66 -85.84 0.0 +96 AQP9 ELLIPSE 2.5 #ffcccc 959.77 -61.21 0.0 +97 FGGY ELLIPSE 2.5 #ffcccc 443.72 569.12 0.0 +98 GSR ELLIPSE 2.5 #ffcccc 370.54 -302.42 0.0 +99 IBA57 ELLIPSE 2.5 #ffcccc 161.17 -692.07 0.0 +100 PDHB ELLIPSE 2.5 #ffcccc 390.13 106.84 0.0 +101 GSTP1 ELLIPSE 2.5 #ffcccc 1071.64 92.44 0.0 +102 GPX8 ELLIPSE 2.5 #ffcccc 893.33 -291.58 0.0 +103 SNAPC2 ELLIPSE 2.5 #ffcccc 677.3 -324.43 0.0 +104 SUPT5H ELLIPSE 2.5 #ffcccc 521.66 -79.9 0.0 +105 GTF2E2 ELLIPSE 2.5 #ffcccc 866.24 -159.51 0.0 +106 POLR3G ELLIPSE 2.5 #ffcccc 964.47 -105.04 0.0 +107 RABAC1 ELLIPSE 2.5 #ffcccc -165.84 -65.63 0.0 +108 NTAQ1 ELLIPSE 2.5 #ffcccc 201.35 -428.96 0.0 +109 TRIM32 ELLIPSE 2.5 #ffcccc 203.83 164.25 0.0 +110 FIS1 ELLIPSE 2.5 #ffcccc 296.75 664.49 0.0 +111 UBXN6 ELLIPSE 2.5 #ffcccc 396.54 592.96 0.0 +112 MYBPHL ELLIPSE 2.5 #ffcccc 923.98 -663.0 0.0 +113 SEC61B ELLIPSE 2.5 #ffcccc 497.38 192.28 0.0 +114 TEX48 ELLIPSE 2.5 #ffcccc 667.42 112.87 0.0 +115 UBE2J2 ELLIPSE 2.5 #ffcccc 422.17 298.46 0.0 +116 SRP72 ELLIPSE 2.5 #ffcccc 509.51 267.15 0.0 +117 SRP9 ELLIPSE 2.5 #ffcccc 523.81 212.29 0.0 +118 RPS10-NUDT3 ELLIPSE 2.5 #ffcccc 647.87 82.85 0.0 +119 RPS7 ELLIPSE 2.5 #ffcccc 583.11 112.49 0.0 +120 RPS19 ELLIPSE 2.5 #ffcccc 600.87 84.59 0.0 +121 RPS3 ELLIPSE 2.5 #ffcccc 545.1 54.3 0.0 +122 RACK1 ELLIPSE 2.5 #ffcccc 522.35 72.17 0.0 +123 RPL36A ELLIPSE 2.5 #ffcccc 638.6 159.59 0.0 +124 RPS10 ELLIPSE 2.5 #ffcccc 557.18 91.72 0.0 +125 RPS27 ELLIPSE 2.5 #ffcccc 594.2 148.48 0.0 +126 RPL24 ELLIPSE 2.5 #ffcccc 607.46 131.87 0.0 +127 RPL7 ELLIPSE 2.5 #ffcccc 538.11 140.23 0.0 +128 RPL38 ELLIPSE 2.5 #ffcccc 490.9 133.47 0.0 +129 RPL22 ELLIPSE 2.5 #ffcccc 603.24 210.78 0.0 +130 RPL18 ELLIPSE 2.5 #ffcccc 573.93 60.88 0.0 +131 RPL7A ELLIPSE 2.5 #ffcccc 554.1 125.75 0.0 +132 RPL27 ELLIPSE 2.5 #ffcccc 490.92 94.66 0.0 +133 RPL39 ELLIPSE 2.5 #ffcccc 580.09 163.73 0.0 +134 SFXN3 ELLIPSE 2.5 #ffcccc 525.73 -752.19 0.0 +135 UQCRQ ELLIPSE 2.5 #ffcccc 272.83 -241.02 0.0 +136 NUFIP2 ELLIPSE 2.5 #ffcccc 718.45 -47.05 0.0 +137 C1QBP ELLIPSE 2.5 #ffcccc 553.33 -224.14 0.0 +138 NOP56 ELLIPSE 2.5 #ffcccc 566.36 -53.12 0.0 +139 UBAP2L ELLIPSE 2.5 #ffcccc 351.68 -377.77 0.0 +140 GP1BB ELLIPSE 2.5 #ffcccc 1029.84 471.85 0.0 +141 WDR76 ELLIPSE 2.5 #ffcccc 679.89 132.73 0.0 +142 SSBP1 ELLIPSE 2.5 #ffcccc 627.24 -49.26 0.0 +143 MAGED2 ELLIPSE 2.5 #ffcccc -46.65 -363.07 0.0 +144 CHCHD2 ELLIPSE 2.5 #ffcccc 569.69 -606.92 0.0 +145 PHB1 ELLIPSE 2.5 #ffcccc 412.13 -81.07 0.0 +146 TMEM97 ELLIPSE 2.5 #ffcccc 17.89 -635.85 0.0 +147 GUK1 ELLIPSE 2.5 #ffcccc 151.08 11.94 0.0 +148 JADE1 ELLIPSE 2.5 #ffcccc -85.84 190.69 0.0 +149 YJU2 ELLIPSE 2.5 #ffcccc -81.66 -132.88 0.0 +150 ING4 ELLIPSE 2.5 #ffcccc 155.51 117.36 0.0 +151 ZPR1 ELLIPSE 2.5 #ffcccc -59.65 17.66 0.0 +152 IL10RA ELLIPSE 2.5 #ffcccc -66.63 -81.51 0.0 +153 GLI1 ELLIPSE 2.5 #ffcccc 779.93 -208.28 0.0 +154 SEM1 ELLIPSE 2.5 #ffcccc 548.81 -141.83 0.0 +155 PSMB10 ELLIPSE 2.5 #ffcccc 567.24 -99.28 0.0 +156 PSMB5 ELLIPSE 2.5 #ffcccc 587.87 -80.0 0.0 +157 SUFU ELLIPSE 2.5 #ffcccc 821.8 -176.27 0.0 +158 ITFG2 ELLIPSE 2.5 #ffcccc 532.39 189.58 0.0 +159 BTN2A1 ELLIPSE 2.5 #ffcccc 895.81 -411.21 0.0 +160 ATP6V1H ELLIPSE 2.5 #ffcccc 355.8 -11.3 0.0 +161 ATP6V0B ELLIPSE 2.5 #ffcccc 402.13 73.56 0.0 +162 RHEB ELLIPSE 2.5 #ffcccc 363.59 447.27 0.0 +163 LAMTOR4 ELLIPSE 2.5 #ffcccc 310.8 243.46 0.0 +164 BMT2 ELLIPSE 2.5 #ffcccc 466.87 374.52 0.0 +165 WDR24 ELLIPSE 2.5 #ffcccc 157.14 220.54 0.0 +166 NME2 ELLIPSE 2.5 #ffcccc 534.42 -32.01 0.0 +167 MEA1 ELLIPSE 2.5 #ffcccc 10.54 123.13 0.0 +168 GPLD1 ELLIPSE 2.5 #ffcccc 239.39 205.77 0.0 +169 LY6H ELLIPSE 2.5 #ffcccc -38.62 -370.22 0.0 +170 CPM ELLIPSE 2.5 #ffcccc 1123.81 94.0 0.0 +171 CNTN5 ELLIPSE 2.5 #ffcccc -212.09 -99.69 0.0 +172 PIGW ELLIPSE 2.5 #ffcccc 796.5 558.58 0.0 +173 EIF1B ELLIPSE 2.5 #ffcccc 680.27 -1.3 0.0 +174 EIF3L ELLIPSE 2.5 #ffcccc 548.58 -8.51 0.0 +175 EIF3CL ELLIPSE 2.5 #ffcccc 718.2 80.71 0.0 +176 EIF3C ELLIPSE 2.5 #ffcccc 665.33 158.22 0.0 +177 EIF1 ELLIPSE 2.5 #ffcccc 707.07 130.48 0.0 +178 EIF3A ELLIPSE 2.5 #ffcccc 629.05 124.29 0.0 +179 EIF3G ELLIPSE 2.5 #ffcccc 514.98 96.94 0.0 +180 TCEANC2 ELLIPSE 2.5 #ffcccc 770.05 -591.89 0.0 +181 POLR2G ELLIPSE 2.5 #ffcccc 592.0 -162.66 0.0 +182 TTR ELLIPSE 2.5 #ffcccc -191.16 30.43 0.0 +183 ITM2B ELLIPSE 2.5 #ffcccc -67.36 444.46 0.0 +184 TBPL1 ELLIPSE 2.5 #ffcccc 996.45 -3.45 0.0 +185 GTF2H2 ELLIPSE 2.5 #ffcccc 824.3 -88.41 0.0 +186 CCNE1 ELLIPSE 2.5 #ffcccc 655.1 -137.16 0.0 +187 FGF23 ELLIPSE 2.5 #ffcccc 926.16 39.73 0.0 +188 MET ELLIPSE 2.5 #ffcccc 676.9 -154.48 0.0 +189 KDR ELLIPSE 2.5 #ffcccc 851.97 247.61 0.0 +190 FGFR1 ELLIPSE 2.5 #ffcccc 886.37 106.3 0.0 +191 GRIA1 ELLIPSE 2.5 #ffcccc 210.47 -270.12 0.0 +192 TRAPPC9 ELLIPSE 2.5 #ffcccc 310.94 651.01 0.0 +193 TRAF3 ELLIPSE 2.5 #ffcccc 305.63 -244.55 0.0 +194 TWIST1 ELLIPSE 2.5 #ffcccc 702.54 -654.01 0.0 +195 FOXO3 ELLIPSE 2.5 #ffcccc 349.48 -170.42 0.0 +196 PLA2G12A ELLIPSE 2.5 #ffcccc 555.06 -417.85 0.0 +197 PEDS1-UBE2V1 ELLIPSE 2.5 #ffcccc 707.02 -147.37 0.0 +198 PLD4 ELLIPSE 2.5 #ffcccc 861.61 -433.07 0.0 +199 PLD3 ELLIPSE 2.5 #ffcccc 1007.86 -317.48 0.0 +200 LPCAT1 ELLIPSE 2.5 #ffcccc 1042.63 -160.24 0.0 +201 SRPK3 ELLIPSE 2.5 #ffcccc 424.63 423.89 0.0 +202 SAFB ELLIPSE 2.5 #ffcccc 177.68 33.06 0.0 +203 RBM10 ELLIPSE 2.5 #ffcccc 242.95 -134.97 0.0 +204 MBNL2 ELLIPSE 2.5 #ffcccc -252.34 74.55 0.0 +205 FUBP1 ELLIPSE 2.5 #ffcccc 174.64 -98.22 0.0 +206 RBM17 ELLIPSE 2.5 #ffcccc 51.09 -85.72 0.0 +207 CTNNBL1 ELLIPSE 2.5 #ffcccc 281.85 -80.39 0.0 +208 MFAP1 ELLIPSE 2.5 #ffcccc 180.47 -145.75 0.0 +209 HNRNPA3 ELLIPSE 2.5 #ffcccc 204.24 69.56 0.0 +210 SF1 ELLIPSE 2.5 #ffcccc 277.26 -127.12 0.0 +211 HNRNPA1 ELLIPSE 2.5 #ffcccc 374.07 -0.46 0.0 +212 FMC1-LUC7L2 ELLIPSE 2.5 #ffcccc -93.92 -115.27 0.0 +213 DDX39B ELLIPSE 2.5 #ffcccc 340.73 -34.8 0.0 +214 DDX46 ELLIPSE 2.5 #ffcccc 52.88 -202.01 0.0 +215 SFPQ ELLIPSE 2.5 #ffcccc 162.58 -2.73 0.0 +216 SNRPB2 ELLIPSE 2.5 #ffcccc 144.87 -42.35 0.0 +217 SF3B5 ELLIPSE 2.5 #ffcccc 238.26 33.32 0.0 +218 ATP5F1E ELLIPSE 2.5 #ffcccc 373.36 -291.05 0.0 +219 SMARCA4 ELLIPSE 2.5 #ffcccc 614.81 -223.27 0.0 +220 JARID2 ELLIPSE 2.5 #ffcccc 486.48 -152.8 0.0 +221 PPA2 ELLIPSE 2.5 #ffcccc 423.13 -201.03 0.0 +222 COX6C ELLIPSE 2.5 #ffcccc 308.41 -158.97 0.0 +223 NDUFB10 ELLIPSE 2.5 #ffcccc 204.82 -92.67 0.0 +224 UQCR11 ELLIPSE 2.5 #ffcccc 165.26 -302.77 0.0 +225 COX7C ELLIPSE 2.5 #ffcccc 437.33 -68.95 0.0 +226 CLPP ELLIPSE 2.5 #ffcccc 331.26 -95.18 0.0 +227 TBRG4 ELLIPSE 2.5 #ffcccc 315.86 -509.92 0.0 +228 GRSF1 ELLIPSE 2.5 #ffcccc 838.05 -84.51 0.0 +229 HINT2 ELLIPSE 2.5 #ffcccc -55.81 129.46 0.0 +230 PIN1 ELLIPSE 2.5 #ffcccc 122.36 90.8 0.0 +231 CCDC97 ELLIPSE 2.5 #ffcccc 100.49 355.24 0.0 +232 DNAJC8 ELLIPSE 2.5 #ffcccc 194.05 -36.2 0.0 +233 HTATSF1 ELLIPSE 2.5 #ffcccc 127.8 -182.22 0.0 +234 CANX ELLIPSE 2.5 #ffcccc 489.56 -182.45 0.0 +235 HLA-DRA ELLIPSE 2.5 #ffcccc 226.85 -38.8 0.0 +236 HLA-DQB2 ELLIPSE 2.5 #ffcccc 271.76 33.47 0.0 +237 KCNH2 ELLIPSE 2.5 #ffcccc 26.31 -180.7 0.0 +238 CISD2 ELLIPSE 2.5 #ffcccc -22.11 32.97 0.0 +239 PRKCD ELLIPSE 2.5 #ffcccc 298.07 -83.71 0.0 +240 NCOR2 ELLIPSE 2.5 #ffcccc 393.84 -55.69 0.0 +241 IRF3 ELLIPSE 2.5 #ffcccc 352.65 120.45 0.0 +242 JPT2 ELLIPSE 2.5 #ffcccc 964.41 -688.34 0.0 +243 STMN1 ELLIPSE 2.5 #ffcccc 564.26 -531.67 0.0 +244 VGF ELLIPSE 2.5 #ffcccc 1175.25 -16.07 0.0 +245 AP1B1 ELLIPSE 2.5 #ffcccc 339.71 -185.54 0.0 +246 RAB5A ELLIPSE 2.5 #ffcccc 46.07 -434.85 0.0 +247 RAB8B ELLIPSE 2.5 #ffcccc -201.18 15.14 0.0 +248 SIPA1L2 ELLIPSE 2.5 #ffcccc 75.04 -665.27 0.0 +249 ABHD17A ELLIPSE 2.5 #ffcccc 86.24 455.71 0.0 +250 ABHD17C ELLIPSE 2.5 #ffcccc 986.11 186.32 0.0 +251 SLX1A ELLIPSE 2.5 #ffcccc 595.01 -276.17 0.0 +252 FANCF ELLIPSE 2.5 #ffcccc 738.77 -400.79 0.0 +253 XRCC3 ELLIPSE 2.5 #ffcccc 389.58 144.81 0.0 +254 ERCC4 ELLIPSE 2.5 #ffcccc 769.79 -296.41 0.0 +255 TUBG2 ELLIPSE 2.5 #ffcccc 398.0 382.74 0.0 +256 TOPORS ELLIPSE 2.5 #ffcccc -41.26 480.19 0.0 +257 BLOC1S2 ELLIPSE 2.5 #ffcccc -60.83 -14.91 0.0 +258 NME7 ELLIPSE 2.5 #ffcccc 702.29 33.34 0.0 +259 CIAO3 ELLIPSE 2.5 #ffcccc 1028.09 456.21 0.0 +260 CIAO2A ELLIPSE 2.5 #ffcccc 1141.78 261.49 0.0 +261 MLLT6 ELLIPSE 2.5 #ffcccc 19.4 147.4 0.0 +262 ZC3H4 ELLIPSE 2.5 #ffcccc -130.8 -534.83 0.0 +263 UBXN1 ELLIPSE 2.5 #ffcccc 602.54 371.63 0.0 +264 EIF4A1 ELLIPSE 2.5 #ffcccc 571.06 183.68 0.0 +265 TOMM34 ELLIPSE 2.5 #ffcccc -260.87 162.24 0.0 +266 DHX30 ELLIPSE 2.5 #ffcccc 536.59 -307.77 0.0 +267 LARP1 ELLIPSE 2.5 #ffcccc 895.13 -380.74 0.0 +268 SRSF5 ELLIPSE 2.5 #ffcccc 121.72 11.09 0.0 +269 ARID1A ELLIPSE 2.5 #ffcccc 674.61 -408.19 0.0 +270 NCL ELLIPSE 2.5 #ffcccc 408.11 99.74 0.0 +271 H2BC8 ELLIPSE 2.5 #ffcccc 781.04 63.63 0.0 +272 YEATS2 ELLIPSE 2.5 #ffcccc 707.68 -198.2 0.0 +273 TADA2B ELLIPSE 2.5 #ffcccc 585.85 -223.9 0.0 +274 PPP6R3 ELLIPSE 2.5 #ffcccc 26.05 -472.62 0.0 +275 WRAP53 ELLIPSE 2.5 #ffcccc 500.89 -343.74 0.0 +276 EIF6 ELLIPSE 2.5 #ffcccc 570.59 223.52 0.0 +277 BTG1 ELLIPSE 2.5 #ffcccc 73.64 -629.9 0.0 +278 AHCTF1 ELLIPSE 2.5 #ffcccc 853.1 461.18 0.0 +279 UBE2E1 ELLIPSE 2.5 #ffcccc 472.94 48.64 0.0 +280 CDK17 ELLIPSE 2.5 #ffcccc 1148.17 -458.07 0.0 +281 PPP2R5A ELLIPSE 2.5 #ffcccc 611.67 291.27 0.0 +282 DNMT1 ELLIPSE 2.5 #ffcccc 696.75 -180.77 0.0 +283 LIN9 ELLIPSE 2.5 #ffcccc 849.73 310.87 0.0 +284 KIFC1 ELLIPSE 2.5 #ffcccc 638.56 41.64 0.0 +285 CENPU ELLIPSE 2.5 #ffcccc 628.64 367.35 0.0 +286 BUB3 ELLIPSE 2.5 #ffcccc 454.72 149.76 0.0 +287 SKA3 ELLIPSE 2.5 #ffcccc 305.97 312.41 0.0 +288 CEP55 ELLIPSE 2.5 #ffcccc 521.59 448.26 0.0 +289 TOP2A ELLIPSE 2.5 #ffcccc 558.75 351.26 0.0 +290 OASL ELLIPSE 2.5 #ffcccc 549.38 229.74 0.0 +291 FBXL19 ELLIPSE 2.5 #ffcccc 349.32 359.3 0.0 +292 LMO2 ELLIPSE 2.5 #ffcccc 182.41 -255.71 0.0 +293 MAPRE2 ELLIPSE 2.5 #ffcccc 283.54 616.33 0.0 +294 HTRA2 ELLIPSE 2.5 #ffcccc -64.45 -583.01 0.0 +295 OR13C9 ELLIPSE 2.5 #ffcccc 265.48 533.68 0.0 +296 GNAL ELLIPSE 2.5 #ffcccc 160.62 -85.54 0.0 +297 CTSV ELLIPSE 2.5 #ffcccc 41.42 196.03 0.0 +298 DERL1 ELLIPSE 2.5 #ffcccc 707.74 334.6 0.0 +299 SLC35B1 ELLIPSE 2.5 #ffcccc 710.08 485.03 0.0 +300 NGLY1 ELLIPSE 2.5 #ffcccc 352.2 346.7 0.0 +301 RNF139 ELLIPSE 2.5 #ffcccc 1008.23 -74.25 0.0 +302 RIPK1 ELLIPSE 2.5 #ffcccc 363.21 14.63 0.0 +303 UBE2V1 ELLIPSE 2.5 #ffcccc 287.78 149.16 0.0 +304 ELOC ELLIPSE 2.5 #ffcccc 736.89 14.47 0.0 +305 IKBKG ELLIPSE 2.5 #ffcccc 433.35 -25.83 0.0 +306 GUCA1C ELLIPSE 2.5 #ffcccc -236.31 -201.74 0.0 +307 PI4KB ELLIPSE 2.5 #ffcccc 307.65 259.06 0.0 +308 GYS2 ELLIPSE 2.5 #ffcccc 1047.32 284.07 0.0 +309 GMPPA ELLIPSE 2.5 #ffcccc 842.24 329.83 0.0 +310 GBE1 ELLIPSE 2.5 #ffcccc 973.32 361.61 0.0 +311 PPP4R4 ELLIPSE 2.5 #ffcccc 445.43 549.09 0.0 +312 WNT8A ELLIPSE 2.5 #ffcccc 520.63 520.71 0.0 +313 DVL1 ELLIPSE 2.5 #ffcccc 541.2 242.29 0.0 +314 CACNG8 ELLIPSE 2.5 #ffcccc 592.85 -152.14 0.0 +315 AXIN1 ELLIPSE 2.5 #ffcccc 428.62 78.05 0.0 +316 USP22 ELLIPSE 2.5 #ffcccc 670.26 -95.27 0.0 +317 SAP130 ELLIPSE 2.5 #ffcccc 829.17 -211.9 0.0 +318 SGF29 ELLIPSE 2.5 #ffcccc 519.22 -13.6 0.0 +319 KPNA3 ELLIPSE 2.5 #ffcccc -252.88 -70.05 0.0 +320 RCC1 ELLIPSE 2.5 #ffcccc 258.74 368.74 0.0 +321 SLC30A4 ELLIPSE 2.5 #ffcccc 544.23 -499.53 0.0 +322 C19orf25 ELLIPSE 2.5 #ffcccc -10.17 -15.85 0.0 +323 KCNAB1 ELLIPSE 2.5 #ffcccc -35.36 278.5 0.0 +324 MAF1 ELLIPSE 2.5 #ffcccc 616.6 79.04 0.0 +325 CARM1 ELLIPSE 2.5 #ffcccc 318.08 -44.43 0.0 +326 GAPVD1 ELLIPSE 2.5 #ffcccc 101.57 -310.12 0.0 +327 FBXO6 ELLIPSE 2.5 #ffcccc 648.16 -330.58 0.0 +328 GBA1 ELLIPSE 2.5 #ffcccc 700.56 -282.97 0.0 +329 FKBP9 ELLIPSE 2.5 #ffcccc 442.44 -147.26 0.0 +330 PCBP4 ELLIPSE 2.5 #ffcccc -17.31 -206.58 0.0 +331 KCNQ4 ELLIPSE 2.5 #ffcccc 482.51 219.98 0.0 +332 ITGAE ELLIPSE 2.5 #ffcccc 56.53 -632.14 0.0 +333 ITGA9 ELLIPSE 2.5 #ffcccc 294.12 -715.67 0.0 +334 MED15 ELLIPSE 2.5 #ffcccc 449.86 28.34 0.0 +335 ANGPTL4 ELLIPSE 2.5 #ffcccc 195.31 173.92 0.0 +336 RXRA ELLIPSE 2.5 #ffcccc 354.21 -195.72 0.0 +337 CD247 ELLIPSE 2.5 #ffcccc 332.25 294.76 0.0 +338 KRT18 ELLIPSE 2.5 #ffcccc 216.79 636.9 0.0 +339 CETN2 ELLIPSE 2.5 #ffcccc 644.93 -78.9 0.0 +340 PRKDC ELLIPSE 2.5 #ffcccc 675.41 33.99 0.0 +341 ADGRL4 ELLIPSE 2.5 #ffcccc 275.6 625.95 0.0 +342 PLCB4 ELLIPSE 2.5 #ffcccc 580.8 310.82 0.0 +343 EFNA5 ELLIPSE 2.5 #ffcccc 1032.53 -133.77 0.0 +344 BDNF ELLIPSE 2.5 #ffcccc 993.24 -142.84 0.0 +345 KIF1B ELLIPSE 2.5 #ffcccc 941.47 -71.62 0.0 +346 NBAS ELLIPSE 2.5 #ffcccc 617.88 -277.98 0.0 +347 KIF3C ELLIPSE 2.5 #ffcccc 850.31 -300.19 0.0 +348 KIF5A ELLIPSE 2.5 #ffcccc 788.14 -253.15 0.0 +349 KLC2 ELLIPSE 2.5 #ffcccc 835.98 18.39 0.0 +350 CPSF7 ELLIPSE 2.5 #ffcccc 161.46 -133.64 0.0 +351 TP63 ELLIPSE 2.5 #ffcccc 1011.79 168.96 0.0 +352 RPH3A ELLIPSE 2.5 #ffcccc 213.27 492.14 0.0 +353 FLNC ELLIPSE 2.5 #ffcccc 233.33 -620.57 0.0 +354 PCNP ELLIPSE 2.5 #ffcccc 602.22 -744.8 0.0 +355 ALDH8A1 ELLIPSE 2.5 #ffcccc -126.66 -454.02 0.0 +356 APOC4-APOC2 ELLIPSE 2.5 #ffcccc 406.55 -468.64 0.0 +357 ZCRB1 ELLIPSE 2.5 #ffcccc 667.24 294.44 0.0 +358 SNRNP25 ELLIPSE 2.5 #ffcccc 291.31 592.51 0.0 +359 TMEM19 ELLIPSE 2.5 #ffcccc 113.35 -335.83 0.0 +360 DTD2 ELLIPSE 2.5 #ffcccc -123.13 175.16 0.0 +361 BSCL2 ELLIPSE 2.5 #ffcccc -76.3 489.58 0.0 +362 UBE2Q2 ELLIPSE 2.5 #ffcccc 1149.24 -73.26 0.0 +363 UBE2G1 ELLIPSE 2.5 #ffcccc 1008.0 -16.98 0.0 +364 SEPTIN12 ELLIPSE 2.5 #ffcccc 751.17 -421.02 0.0 +365 TMEM250 ELLIPSE 2.5 #ffcccc 800.29 389.81 0.0 +366 SEPTIN9 ELLIPSE 2.5 #ffcccc 1056.4 -84.14 0.0 +367 CHCHD6 ELLIPSE 2.5 #ffcccc 861.85 -225.34 0.0 +368 APOBEC3G ELLIPSE 2.5 #ffcccc 301.4 -334.37 0.0 +369 COX14 ELLIPSE 2.5 #ffcccc 4.89 -26.77 0.0 +370 SDHD ELLIPSE 2.5 #ffcccc 111.2 -157.38 0.0 +371 MT-CO3 ELLIPSE 2.5 #ffcccc 157.83 -240.0 0.0 +372 PWWP3B ELLIPSE 2.5 #ffcccc 88.42 -141.88 0.0 +373 TIMMDC1 ELLIPSE 2.5 #ffcccc -71.79 246.23 0.0 +374 NDUFB2 ELLIPSE 2.5 #ffcccc 274.68 -216.01 0.0 +375 CBX8 ELLIPSE 2.5 #ffcccc 339.22 -80.21 0.0 +376 CASP8AP2 ELLIPSE 2.5 #ffcccc -127.08 257.53 0.0 +377 TNRC6B ELLIPSE 2.5 #ffcccc 374.34 -341.8 0.0 +378 AGO4 ELLIPSE 2.5 #ffcccc 339.72 -255.17 0.0 +379 PHC1 ELLIPSE 2.5 #ffcccc 338.69 -133.61 0.0 +380 PNMT ELLIPSE 2.5 #ffcccc 768.93 624.44 0.0 +381 LRTOMT ELLIPSE 2.5 #ffcccc 816.28 467.91 0.0 +382 SCYL1 ELLIPSE 2.5 #ffcccc 737.08 -141.54 0.0 +383 SZRD1 ELLIPSE 2.5 #ffcccc 879.94 -35.16 0.0 +384 RIC8A ELLIPSE 2.5 #ffcccc 803.88 301.71 0.0 +385 COPZ1 ELLIPSE 2.5 #ffcccc 260.13 -549.36 0.0 +386 EPB41L1 ELLIPSE 2.5 #ffcccc 66.25 -154.94 0.0 +387 GRID2 ELLIPSE 2.5 #ffcccc 184.58 -400.9 0.0 +388 CACNA1G ELLIPSE 2.5 #ffcccc 1038.38 -36.05 0.0 +389 PRCC ELLIPSE 2.5 #ffcccc 897.48 -155.28 0.0 +390 UNK ELLIPSE 2.5 #ffcccc 1074.27 335.88 0.0 +391 SETDB1 ELLIPSE 2.5 #ffcccc 320.9 -60.91 0.0 +392 H3C4 ELLIPSE 2.5 #ffcccc 692.84 -3.26 0.0 +393 H3-3A ELLIPSE 2.5 #ffcccc 531.19 -65.61 0.0 +394 SUV39H1 ELLIPSE 2.5 #ffcccc 722.83 -324.32 0.0 +395 NKD2 ELLIPSE 2.5 #ffcccc 1049.24 323.28 0.0 +396 RBM11 ELLIPSE 2.5 #ffcccc 199.05 -198.41 0.0 +397 MPND ELLIPSE 2.5 #ffcccc 569.49 273.41 0.0 +398 PEX7 ELLIPSE 2.5 #ffcccc 852.8 -182.45 0.0 +399 SPRED3 ELLIPSE 2.5 #ffcccc 828.5 -55.59 0.0 +400 NLRP4 ELLIPSE 2.5 #ffcccc 560.46 444.96 0.0 +401 PAOX ELLIPSE 2.5 #ffcccc 933.31 -304.73 0.0 +402 LGR6 ELLIPSE 2.5 #ffcccc 36.1 233.72 0.0 +403 CHMP6 ELLIPSE 2.5 #ffcccc 794.85 -39.43 0.0 +404 KLHL12 ELLIPSE 2.5 #ffcccc 461.84 69.62 0.0 +405 CHMP7 ELLIPSE 2.5 #ffcccc 832.34 115.39 0.0 +406 GNPAT ELLIPSE 2.5 #ffcccc 995.4 118.15 0.0 +407 EGLN1 ELLIPSE 2.5 #ffcccc 466.22 197.22 0.0 +408 GSPT2 ELLIPSE 2.5 #ffcccc 650.61 225.18 0.0 +409 GPS1 ELLIPSE 2.5 #ffcccc 847.36 50.65 0.0 +410 COMMD6 ELLIPSE 2.5 #ffcccc 755.61 169.53 0.0 +411 PARK7 ELLIPSE 2.5 #ffcccc 653.95 169.01 0.0 +412 UBE2F ELLIPSE 2.5 #ffcccc 1009.33 188.17 0.0 +413 IZUMO4 ELLIPSE 2.5 #ffcccc 708.79 -536.13 0.0 +414 USP38 ELLIPSE 2.5 #ffcccc 1045.41 -322.39 0.0 +415 MYSM1 ELLIPSE 2.5 #ffcccc 665.0 -109.46 0.0 +416 UBE2E2 ELLIPSE 2.5 #ffcccc 473.77 273.47 0.0 +417 NOL10 ELLIPSE 2.5 #ffcccc 730.21 150.97 0.0 +418 UBE2A ELLIPSE 2.5 #ffcccc 337.27 141.56 0.0 +419 JOSD2 ELLIPSE 2.5 #ffcccc 543.06 392.59 0.0 +420 ADGRG7 ELLIPSE 2.5 #ffcccc 335.94 -459.93 0.0 +421 RASA1 ELLIPSE 2.5 #ffcccc 951.4 -368.66 0.0 +422 TAF11L4 ELLIPSE 2.5 #ffcccc 1162.87 -50.2 0.0 +423 KCTD2 ELLIPSE 2.5 #ffcccc 471.03 -321.67 0.0 +424 LIN7C ELLIPSE 2.5 #ffcccc 411.39 -597.1 0.0 +425 SYN1 ELLIPSE 2.5 #ffcccc 703.41 -690.62 0.0 +426 HSD17B12 ELLIPSE 2.5 #ffcccc -201.11 182.97 0.0 +427 DHCR24 ELLIPSE 2.5 #ffcccc -18.3 -147.46 0.0 +428 OAZ1 ELLIPSE 2.5 #ffcccc 709.32 -223.62 0.0 +429 TRIM52 ELLIPSE 2.5 #ffcccc 605.91 8.02 0.0 +430 TM7SF2 ELLIPSE 2.5 #ffcccc -267.6 -47.32 0.0 +431 HAUS1 ELLIPSE 2.5 #ffcccc 85.44 -263.85 0.0 +432 CEP162 ELLIPSE 2.5 #ffcccc 475.87 -724.87 0.0 +433 SCN3A ELLIPSE 2.5 #ffcccc 817.48 -548.71 0.0 +434 SCN3B ELLIPSE 2.5 #ffcccc 789.06 -430.87 0.0 +435 SCN1B ELLIPSE 2.5 #ffcccc 941.74 -243.21 0.0 +436 PLA2G4E ELLIPSE 2.5 #ffcccc 1087.65 -396.36 0.0 +437 ABCA6 ELLIPSE 2.5 #ffcccc -177.7 240.6 0.0 +438 ODF1 ELLIPSE 2.5 #ffcccc 1191.08 132.92 0.0 +439 GPC2 ELLIPSE 2.5 #ffcccc 755.79 -31.69 0.0 +440 HS3ST4 ELLIPSE 2.5 #ffcccc -32.95 -333.02 0.0 +441 MARCHF7 ELLIPSE 2.5 #ffcccc 1023.15 442.17 0.0 +442 UBE4B ELLIPSE 2.5 #ffcccc 891.9 407.9 0.0 +443 DNAI3 ELLIPSE 2.5 #ffcccc 501.39 -754.43 0.0 +444 CCDC114 ELLIPSE 2.5 #ffcccc 726.23 -269.7 0.0 +445 FABP1 ELLIPSE 2.5 #ffcccc 395.65 -343.34 0.0 +446 RGL1 ELLIPSE 2.5 #ffcccc 166.23 -448.42 0.0 +447 CHD9 ELLIPSE 2.5 #ffcccc 239.23 -255.47 0.0 +448 SNCB ELLIPSE 2.5 #ffcccc 984.96 -550.37 0.0 +449 DNAJC5G ELLIPSE 2.5 #ffcccc 829.53 -385.75 0.0 +450 ADH5 ELLIPSE 2.5 #ffcccc 950.57 507.76 0.0 +451 MCC ELLIPSE 2.5 #ffcccc 750.38 76.35 0.0 +452 RPP25L ELLIPSE 2.5 #ffcccc 296.95 -181.19 0.0 +453 NOLC1 ELLIPSE 2.5 #ffcccc 271.99 49.37 0.0 +454 ENOX2 ELLIPSE 2.5 #ffcccc 840.13 -542.42 0.0 +455 RPP40 ELLIPSE 2.5 #ffcccc 331.48 45.47 0.0 +456 INPPL1 ELLIPSE 2.5 #ffcccc -144.67 118.83 0.0 +457 GRAP2 ELLIPSE 2.5 #ffcccc -34.92 1.27 0.0 +458 PRDX3 ELLIPSE 2.5 #ffcccc 229.24 168.93 0.0 +459 CKB ELLIPSE 2.5 #ffcccc 334.03 510.62 0.0 +460 ALDOA ELLIPSE 2.5 #ffcccc 824.88 464.59 0.0 +461 PPFIBP2 ELLIPSE 2.5 #ffcccc 575.44 -703.05 0.0 +462 KAZN ELLIPSE 2.5 #ffcccc 826.94 -586.78 0.0 +463 MARCHF2 ELLIPSE 2.5 #ffcccc 617.74 543.82 0.0 +464 TMEM256 ELLIPSE 2.5 #ffcccc 597.39 -332.25 0.0 +465 RAB29 ELLIPSE 2.5 #ffcccc 779.94 -654.52 0.0 +466 TMEM14C ELLIPSE 2.5 #ffcccc 838.23 58.41 0.0 +467 TONSL ELLIPSE 2.5 #ffcccc -10.57 -277.47 0.0 +468 H1-10 ELLIPSE 2.5 #ffcccc 1139.25 -234.86 0.0 +469 CHRM1 ELLIPSE 2.5 #ffcccc 70.38 233.63 0.0 +470 EDN3 ELLIPSE 2.5 #ffcccc 920.71 100.42 0.0 +471 LPAR4 ELLIPSE 2.5 #ffcccc -193.25 -58.63 0.0 +472 GABARAP ELLIPSE 2.5 #ffcccc 783.31 295.59 0.0 +473 FNIP1 ELLIPSE 2.5 #ffcccc 490.14 310.83 0.0 +474 TBC1D25 ELLIPSE 2.5 #ffcccc 501.72 556.76 0.0 +475 ATG5 ELLIPSE 2.5 #ffcccc 1100.27 -256.32 0.0 +476 LCMT2 ELLIPSE 2.5 #ffcccc -4.28 -540.72 0.0 +477 ZNF302 ELLIPSE 2.5 #ffcccc -150.48 134.4 0.0 +478 B4GAT1 ELLIPSE 2.5 #ffcccc 654.53 475.96 0.0 +479 PRELP ELLIPSE 2.5 #ffcccc 645.32 714.28 0.0 +480 LARGE2 ELLIPSE 2.5 #ffcccc 651.74 -487.15 0.0 +481 FTSJ1 ELLIPSE 2.5 #ffcccc 583.77 277.04 0.0 +482 RHNO1 ELLIPSE 2.5 #ffcccc 642.9 -656.21 0.0 +483 ZNF746 ELLIPSE 2.5 #ffcccc 198.31 -547.04 0.0 +484 KLHL2 ELLIPSE 2.5 #ffcccc 324.78 217.62 0.0 +485 ATAD5 ELLIPSE 2.5 #ffcccc -97.61 -174.66 0.0 +486 DNAJC1 ELLIPSE 2.5 #ffcccc 277.34 320.15 0.0 +487 RAB4B ELLIPSE 2.5 #ffcccc 1058.39 38.64 0.0 +488 ECT2L ELLIPSE 2.5 #ffcccc 511.29 -581.37 0.0 +489 CFAP45 ELLIPSE 2.5 #ffcccc 1075.9 12.64 0.0 +490 CFAP53 ELLIPSE 2.5 #ffcccc 992.26 102.94 0.0 +491 CNPPD1 ELLIPSE 2.5 #ffcccc 558.43 -598.64 0.0 +492 STIL ELLIPSE 2.5 #ffcccc 167.53 532.78 0.0 +493 B3GNT4 ELLIPSE 2.5 #ffcccc 243.99 594.14 0.0 +494 KDM3A ELLIPSE 2.5 #ffcccc 600.3 -555.8 0.0 +495 FAM3A ELLIPSE 2.5 #ffcccc -65.27 490.07 0.0 +496 SNX15 ELLIPSE 2.5 #ffcccc 250.84 697.5 0.0 +497 DNAJC25 ELLIPSE 2.5 #ffcccc 188.39 329.68 0.0 +498 PELI3 ELLIPSE 2.5 #ffcccc -81.64 398.5 0.0 +499 CD6 ELLIPSE 2.5 #ffcccc -4.7 301.21 0.0 +500 CD40LG ELLIPSE 2.5 #ffcccc 420.1 -293.14 0.0 +501 ZYX ELLIPSE 2.5 #ffcccc -57.34 26.27 0.0 +502 TBC1D10B ELLIPSE 2.5 #ffcccc -161.02 -253.3 0.0 +503 DPH5 ELLIPSE 2.5 #ffcccc -57.25 -454.25 0.0 +504 RTN4IP1 ELLIPSE 2.5 #ffcccc 129.09 463.22 0.0 +505 COA3 ELLIPSE 2.5 #ffcccc 331.05 276.93 0.0 +506 PRKCH ELLIPSE 2.5 #ffcccc 12.79 -528.9 0.0 +507 ADRA2B ELLIPSE 2.5 #ffcccc 413.14 -688.04 0.0 +508 ADGRG6 ELLIPSE 2.5 #ffcccc -244.42 264.01 0.0 +509 OR3A2 ELLIPSE 2.5 #ffcccc -219.19 -442.99 0.0 +510 OR2T5 ELLIPSE 2.5 #ffcccc -71.59 -166.96 0.0 +511 OR11G2 ELLIPSE 2.5 #ffcccc 450.02 688.45 0.0 +512 OR10K2 ELLIPSE 2.5 #ffcccc 163.09 -647.49 0.0 +513 OR52A5 ELLIPSE 2.5 #ffcccc 650.63 -571.45 0.0 +514 OR9A4 ELLIPSE 2.5 #ffcccc 1027.78 -221.06 0.0 +515 TRAPPC11 ELLIPSE 2.5 #ffcccc 447.67 701.38 0.0 +516 CLDN2 ELLIPSE 2.5 #ffcccc 1048.82 -451.4 0.0 +517 CLDN3 ELLIPSE 2.5 #ffcccc 1043.11 269.29 0.0 +518 WHRN ELLIPSE 2.5 #ffcccc 82.85 588.25 0.0 +519 LIPA ELLIPSE 2.5 #ffcccc 39.18 -408.27 0.0 +520 EBAG9 ELLIPSE 2.5 #ffcccc -18.18 377.51 0.0 +521 ZNF385A ELLIPSE 2.5 #ffcccc -108.21 270.99 0.0 +522 TREM2 ELLIPSE 2.5 #ffcccc -129.0 157.41 0.0 +523 IFNAR2 ELLIPSE 2.5 #ffcccc -197.99 144.43 0.0 +524 FOXO6 ELLIPSE 2.5 #ffcccc 629.17 676.58 0.0 +525 ARL4C ELLIPSE 2.5 #ffcccc -44.34 -266.55 0.0 +526 HNRNPA1L2 ELLIPSE 2.5 #ffcccc -86.29 -2.7 0.0 +527 MAP3K15 ELLIPSE 2.5 #ffcccc 128.81 -694.14 0.0 +528 TNFSF13B ELLIPSE 2.5 #ffcccc 372.91 -455.35 0.0 +529 ANP32B ELLIPSE 2.5 #ffcccc 907.23 -599.04 0.0 +530 MAGI2 ELLIPSE 2.5 #ffcccc 549.78 663.35 0.0 +531 ZNF512 ELLIPSE 2.5 #ffcccc 658.47 -407.18 0.0 +532 TNFRSF14 ELLIPSE 2.5 #ffcccc -78.29 -524.95 0.0 +533 BTBD6 ELLIPSE 2.5 #ffcccc 378.31 513.14 0.0 +534 LRRC41 ELLIPSE 2.5 #ffcccc 1176.22 112.88 0.0 +535 AADACL2 ELLIPSE 2.5 #ffcccc 61.09 557.45 0.0 +536 CFAP43 ELLIPSE 2.5 #ffcccc 6.48 629.0 0.0 +537 ADGB ELLIPSE 2.5 #ffcccc 349.62 674.22 0.0 +538 SLFN11 ELLIPSE 2.5 #ffcccc -162.65 -209.92 0.0 +539 ARID5A ELLIPSE 2.5 #ffcccc -247.87 -61.97 0.0 +540 FOXH1 ELLIPSE 2.5 #ffcccc 8.13 -185.35 0.0 +541 TGIF2 ELLIPSE 2.5 #ffcccc 953.26 -88.6 0.0 +542 ING1 ELLIPSE 2.5 #ffcccc 1099.21 -137.98 0.0 +543 EIF2B1 ELLIPSE 2.5 #ffcccc 1126.41 -38.26 0.0 +544 AMDHD2 ELLIPSE 2.5 #ffcccc 1015.9 -37.03 0.0 +545 DPM3 ELLIPSE 2.5 #ffcccc 312.26 310.86 0.0 +546 ETS2 ELLIPSE 2.5 #ffcccc 915.4 -391.34 0.0 +547 ERC1 ELLIPSE 2.5 #ffcccc 1157.91 179.64 0.0 +548 AC098614 ELLIPSE 2.5 #ffcccc 471.8 418.07 0.0 +549 DOCK2 ELLIPSE 2.5 #ffcccc 977.19 205.81 0.0 +550 COX7B2 ELLIPSE 2.5 #ffcccc 249.52 -449.94 0.0 +551 NTPCR ELLIPSE 2.5 #ffcccc 543.83 -551.68 0.0 +552 EGLN2 ELLIPSE 2.5 #ffcccc 610.35 678.43 0.0 +553 HDGFL2 ELLIPSE 2.5 #ffcccc 586.23 550.31 0.0 +554 VARS2 ELLIPSE 2.5 #ffcccc 112.4 227.12 0.0 +555 SMIM20 ELLIPSE 2.5 #ffcccc -178.01 415.06 0.0 +556 C5orf49 ELLIPSE 2.5 #ffcccc 970.14 128.28 0.0 +557 SPAG6 ELLIPSE 2.5 #ffcccc 770.52 203.92 0.0 +558 NAXE ELLIPSE 2.5 #ffcccc 965.21 -345.44 0.0 +559 DOLPP1 ELLIPSE 2.5 #ffcccc 88.08 419.98 0.0 +560 VSNL1 ELLIPSE 2.5 #ffcccc 567.28 661.97 0.0 +561 MID1IP1 ELLIPSE 2.5 #ffcccc 925.74 -511.3 0.0 +562 BCKDK ELLIPSE 2.5 #ffcccc 831.87 435.67 0.0 +563 TMED5 ELLIPSE 2.5 #ffcccc 839.19 556.01 0.0 +564 WNT5B ELLIPSE 2.5 #ffcccc 381.2 626.58 0.0 +565 PLEKHG6 ELLIPSE 2.5 #ffcccc 1035.01 406.42 0.0 +566 NUDT8 ELLIPSE 2.5 #ffcccc -189.8 -338.25 0.0 +567 RAB40A ELLIPSE 2.5 #ffcccc 906.86 557.83 0.0 +568 FOXP4 ELLIPSE 2.5 #ffcccc 209.31 379.05 0.0 +569 FOXP2 ELLIPSE 2.5 #ffcccc 268.98 -543.84 0.0 +570 MAMLD1 ELLIPSE 2.5 #ffcccc 155.6 -336.67 0.0 +571 BAK1 ELLIPSE 2.5 #ffcccc 1002.73 -584.21 0.0 +572 LYPLA2 ELLIPSE 2.5 #ffcccc 86.19 -482.04 0.0 +573 PRR3 ELLIPSE 2.5 #ffcccc 11.97 -613.59 0.0 +574 SRM ELLIPSE 2.5 #ffcccc 217.42 -612.31 0.0 +575 TCOF1 ELLIPSE 2.5 #ffcccc -87.97 -309.68 0.0 +576 GTF3A ELLIPSE 2.5 #ffcccc 1101.28 -350.02 0.0 +577 DHX57 ELLIPSE 2.5 #ffcccc 1107.09 -182.41 0.0 +578 CDH18 ELLIPSE 2.5 #ffcccc 793.31 -538.98 0.0 +579 BTBD3 ELLIPSE 2.5 #ffcccc -135.55 252.43 0.0 +580 CAPSL ELLIPSE 2.5 #ffcccc 859.4 370.42 0.0 +581 CFAP299 ELLIPSE 2.5 #ffcccc 1104.58 -33.93 0.0 +582 CIC ELLIPSE 2.5 #ffcccc 516.23 556.01 0.0 +583 RBM33 ELLIPSE 2.5 #ffcccc 986.18 610.51 0.0 +584 ZNF638 ELLIPSE 2.5 #ffcccc 690.16 -659.05 0.0 +585 SENP6 ELLIPSE 2.5 #ffcccc 330.67 -677.62 0.0 +586 SAMD3 ELLIPSE 2.5 #ffcccc 462.57 633.75 0.0 +587 MCRIP1 ELLIPSE 2.5 #ffcccc 383.19 -753.76 0.0 +588 TMEM25 ELLIPSE 2.5 #ffcccc 20.8 583.91 0.0 +589 NFIC ELLIPSE 2.5 #ffcccc 565.94 -708.15 0.0 +590 C17orf58 ELLIPSE 2.5 #ffcccc 1015.97 -332.33 0.0 +591 NABP1 ELLIPSE 2.5 #ffcccc 88.5 538.3 0.0 +592 ADGRA2 ELLIPSE 2.5 #ffcccc 916.08 -374.11 0.0 +593 KIAA0513 ELLIPSE 2.5 #ffcccc 1054.89 469.97 0.0 +594 ELP2 ELLIPSE 2.5 #ffcccc 894.36 -337.98 0.0 +595 SYNPR ELLIPSE 2.5 #ffcccc 400.03 635.7 0.0 +596 SLC6A1 ELLIPSE 2.5 #ffcccc 827.23 588.5 0.0 +597 PARP10 ELLIPSE 2.5 #ffcccc 261.13 -623.2 0.0 +598 SOCS4 ELLIPSE 2.5 #ffcccc 1032.54 -251.82 0.0 \ No newline at end of file From 831b88e4573320b809a3160de489c0586a775d6e Mon Sep 17 00:00:00 2001 From: Iara Souza Date: Wed, 8 May 2024 14:02:05 -0300 Subject: [PATCH 24/24] fix: changed the figure 1 and 3 --- scripts/metadata.R | 4 ++++ scripts/network.R | 11 ++++------- scripts/plots.rmd | 40 ++++++++++++++++++++++++++++++++++++++-- 3 files changed, 46 insertions(+), 9 deletions(-) diff --git a/scripts/metadata.R b/scripts/metadata.R index 3a672e1..7e85ed0 100644 --- a/scripts/metadata.R +++ b/scripts/metadata.R @@ -27,12 +27,16 @@ ann$rin <- scale(ann$rin)[,1] rownames(ann) <- ann$sample_id ann$sample_id <- NULL +# Keep the full dataframe +ann_full <- ann + # Remove samples "SRR5961961" and "SRR5961809" that appeared as outliers on robust pca analysis ann <- ann %>% filter(!(rownames(ann) %in% c("SRR5961961", "SRR5961809"))) # Save (this metadata will be used in all future models) save(ann, file = "results/important_variables/ann.rda") +save(ann_full, file = "results/important_variables/ann_full.rda") diff --git a/scripts/network.R b/scripts/network.R index 886be1b..34eefc4 100644 --- a/scripts/network.R +++ b/scripts/network.R @@ -82,9 +82,6 @@ addGraph(rdp, g) nodes <- read_tsv("results/networks/model_nodes.txt") edges <- read_delim("results/networks/model_edges.txt") -nodes <- read_tsv("~/model_nodes.txt") -edges <- read_delim("~/model_edges.txt") - # Import nodes coordinates determined by vivagraph layout <- read.csv("results/networks/layout.csv") @@ -109,16 +106,16 @@ ggraph(g, x = x, y = y) + data = as_data_frame(g, "vertices") %>% filter(gwas == "gwas"), colour = NA, n = 5, - pie_scale = 0.5, + pie_scale = 0.9, show.legend = F) + geom_scatterpie( cols = c("a", "b", "c"), data = as_data_frame(g, "vertices") %>% filter(gwas == "not_gwas"), colour = NA, - pie_scale = 0.2, + pie_scale = 0.3, show.legend = F ) + - geom_node_text(aes(label = alias), size = 0.9, nudge_x = 2, nudge_y = 4) + + #geom_node_text(aes(label = alias), size = 1.7, nudge_x = 2, nudge_y = 4) + #geom_node_label(aes(label = alias)) + scale_fill_manual(values = c("#0ac80aff", "#4f4affff", "#ff822fff")) + coord_fixed() + @@ -130,7 +127,7 @@ if(!dir.exists("results/plots_paper/")) { dir.create("results/plots_paper") } -svg(filename = "results/plots_paper/network.svg", height = 10, width = 10) +pdf(file = "~/Área de Trabalho/network.pdf", height = 15, width = 15) print(p) dev.off() diff --git a/scripts/plots.rmd b/scripts/plots.rmd index c79293d..5f81e80 100644 --- a/scripts/plots.rmd +++ b/scripts/plots.rmd @@ -355,9 +355,45 @@ ggsave("results/plots_paper/fig2C_2.png", height = 4, width = 5, dpi = 300) ``` -## Figure 3 +# Figure 3 -Figure 3 was produced on the biotype analysis, in the `summarise_biotypes.R` script. +```{r} +# Load enrichment data +load("results/tx_enrich/go_terms_tx_by_group.rda") + +# Create a dataframe with results from OFC (female) and CG25 (male) enrichment +df_enrich <- bind_rows(enriched_df_diff[["OFC_female"]], enriched_df_diff[["Cg25_male"]]) + +# Parse gene ratio column +df_enrich <- df_enrich %>% mutate( + n_tag = as.numeric(sapply(strsplit(GeneRatio, split = "\\/"), "[[", 2)), + GeneRatio = as.numeric(Count) / n_tag +) + +# Plot +df_enrich %>% + ggplot(aes(x = fct_reorder2(Description, -p.adjust, -Count), y = GeneRatio, size = Count, col = p.adjust)) + + geom_point() + + facet_grid(rows = vars(group), scales = "free_y", space = "free_y", + labeller = as_labeller(c( + "Cg25_male" = "Cg25 (male)", + "OFC_female" = "OFC (female)" + ))) + + force_panelsizes(rows = c(0.17, 1)) + + scale_color_continuous(limits = c(0, 0.05), breaks = seq(0, 0.05, 0.01)) + + labs(x = "", y = "Gene ratio", color = "FDR", size = "Intersection") + + coord_flip() + + theme_bw() + + theme(axis.text.y = element_text(size = 9), + strip.text.y = element_text(size = 9)) + +ggsave(filename = "results/plots_paper/fig3.pdf", width = 9, height = 6) +ggsave(filename = "results/plots_paper/fig3.png", width = 9, height = 6) +``` + +## Figure 4 + +Figure 4 was produced on the biotype analysis, in the `summarise_biotypes.R` script. # Supplementary Figures