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import itertools
DATASETS, = glob_wildcards("dataset_configs/{dataset}.yml")
SUPERVISED, = glob_wildcards("model_configs/supervised/{supervised}.yml")
NUM_SEEDS = 3
recount_top_five_tissues = ['Blood', 'Breast', 'Stem_Cell', 'Cervix', 'Brain']
combo_iterator = itertools.combinations(recount_top_five_tissues, 2)
RECOUNT_TISSUE_STRING = ['.'.join(pair) for pair in combo_iterator]
gtex_top_five_tissues = ['Blood', 'Brain', 'Skin', 'Esophagus', 'Blood_Vessel']
combo_iterator = itertools.combinations(gtex_top_five_tissues, 2)
GTEX_TISSUE_STRING = ['.'.join(pair) for pair in combo_iterator]
transfer_top_five_tissues = ['Blood', 'Breast', 'Brain', 'Kidney', 'Lung']
combo_iterator = itertools.combinations(transfer_top_five_tissues, 2)
TRANSFER_TISSUE_STRING = ['.'.join(pair) for pair in combo_iterator]
TCGA_GENES = ['EGFR', 'IDH1', 'KRAS', 'PIK3CA', 'SETD2', 'TP53']
wildcard_constraints:
# Random seeds should be numbers
seed="\d+"
result_files = [
# Recount Binary classification
expand("results/{tissues}.{supervised}_{seed}.tsv",
supervised=SUPERVISED,
seed=range(0,NUM_SEEDS),
tissues=RECOUNT_TISSUE_STRING,
),
# GTEx Binary classification
expand("results/gtex.{tissues}.{supervised}_{seed}.tsv",
supervised=SUPERVISED,
seed=range(0,NUM_SEEDS),
tissues=GTEX_TISSUE_STRING,
),
# Recount Transfer Binary classification
expand("results/recount_transfer.{tissues}.{supervised}_{seed}.tsv",
supervised=SUPERVISED,
seed=range(0,NUM_SEEDS),
tissues=TRANSFER_TISSUE_STRING,
),
# GTEx Transfer Binary classification
expand("results/gtex_transfer.{tissues}.{supervised}_{seed}.tsv",
supervised=SUPERVISED,
seed=range(0,NUM_SEEDS),
tissues=TRANSFER_TISSUE_STRING,
),
expand("results/recount_transfer.split_signal.{tissues}.{supervised}_{seed}.tsv",
supervised=SUPERVISED,
seed=range(0,NUM_SEEDS),
tissues=TRANSFER_TISSUE_STRING,
),
expand("results/gtex_transfer.split_signal.{tissues}.{supervised}_{seed}.tsv",
supervised=SUPERVISED,
seed=range(0,NUM_SEEDS),
tissues=TRANSFER_TISSUE_STRING,
),
expand("results/gtex-signal-removed.{tissues}.{supervised}_{seed}.tsv",
supervised=SUPERVISED,
seed=range(0,NUM_SEEDS),
tissues=GTEX_TISSUE_STRING,
),
# Binary classification w/ corrections
expand("results/{tissues}.{supervised}_{seed}-signal_removed.tsv",
supervised=SUPERVISED,
seed=range(0,NUM_SEEDS),
tissues=RECOUNT_TISSUE_STRING,
),
# Multi-tissue prediction
expand("results/all-tissue.{supervised}_{seed}.tsv",
supervised=SUPERVISED,
seed=range(0,NUM_SEEDS),
),
# Multi-tissue prediction
expand("results/recount-transfer.all-tissue.{supervised}_{seed}.tsv",
supervised=SUPERVISED,
seed=range(0,NUM_SEEDS),
),
# Multi-tissue prediction
expand("results/gtex-transfer.all-tissue.{supervised}_{seed}.tsv",
supervised=SUPERVISED,
seed=range(0,NUM_SEEDS),
),
# Signal removed multitissue be correction
expand("results/recount-transfer.split-signal.all-tissue.{supervised}_{seed}.tsv",
supervised=SUPERVISED,
seed=range(0,NUM_SEEDS),
),
expand("results/gtex-transfer.split-signal.all-tissue.{supervised}_{seed}.tsv",
supervised=SUPERVISED,
seed=range(0,NUM_SEEDS),
),
# Multi-tissue prediction sample split
expand("results/all-tissue_sample-split.{supervised}_{seed}.tsv",
supervised=SUPERVISED,
seed=range(0,NUM_SEEDS),
),
expand("results/all-tissue.{supervised}_{seed}_signal_removed.tsv",
supervised=SUPERVISED,
seed=range(0,NUM_SEEDS),
),
# pretraining
expand("results/study-split.{supervised}_{seed}.tsv",
supervised=SUPERVISED,
seed=range(0,NUM_SEEDS),
),
# study_split sex prediction
expand("results/study-split-sex-prediction.{supervised}_{seed}.tsv",
supervised=SUPERVISED,
seed=range(0,NUM_SEEDS),
),
# sex prediction split-signal
expand("results/sex-prediction-signal-removed.{supervised}_{seed}.tsv",
supervised=SUPERVISED,
seed=range(0,NUM_SEEDS),
),
# Multi-tissue prediction
expand("results/gtex-all-tissue.{supervised}_{seed}.tsv",
supervised=SUPERVISED,
seed=range(0,NUM_SEEDS),
),
# Multi-tissue prediction
expand("results/gtex-all-tissue-signal-removed.{supervised}_{seed}.tsv",
supervised=SUPERVISED,
seed=range(0,NUM_SEEDS),
),
# Sim results
expand("results/sim-data.{supervised}_{seed}.tsv",
supervised=SUPERVISED,
seed=range(0,NUM_SEEDS),
),
# Sim results be corrected
expand("results/sim-data-signal-removed.{supervised}_{seed}.tsv",
supervised=SUPERVISED,
seed=range(0,NUM_SEEDS),
),
# Linear sim results
expand("results/linear-sim-data.{supervised}_{seed}.tsv",
supervised=SUPERVISED,
seed=range(0,NUM_SEEDS),
),
expand("results/linear-sim-data-signal-removed.{supervised}_{seed}.tsv",
supervised=SUPERVISED,
seed=range(0,NUM_SEEDS),
),
# No signal sim
expand("results/no-signal-sim-data.{supervised}_{seed}.tsv",
supervised=SUPERVISED,
seed=range(0,NUM_SEEDS),
),
expand("results/no-signal-sim-data-signal-removed.{supervised}_{seed}.tsv",
supervised=SUPERVISED,
seed=range(0,NUM_SEEDS),
),
]
figures = [
'figures/full_signal_combined.svg',
'figures/simulated_data_combined.svg',
'figures/signal_removed_combined.svg',
'figures/recount_binary.svg',
'figures/no_signal_sim_signal_removed.svg',
'figures/recount_binary_combined.svg',
'figures/recount_multiclass_sample_split.svg',
'figures/recount_pretraining.svg',
]
data_files = [
"data/sra_counts.tsv",
"data/metadata_df.rda",
"data/recount_metadata.tsv",
"data/no_scrna_counts.tsv",
"data/gene_lengths.tsv",
"data/no_scrna_tpm.tsv",
"data/no_scrna_tpm.pkl",
"data/gtex_tpm.gct",
"data/gtex_sample_attributes.txt",
"data/gtex_normalized.tsv",
"data/gtex_normalized.pkl",
"data/batch_sim_data.tsv",
"data/linear_batch_sim_data.tsv",
"data/no_signal_batch_sim_data.tsv",
"data/recount_gtex_genes.tsv",
"data/recount_gtex_genes.pkl"
]
rule all:
input:
result_files,
figures,
data_files
rule generate_figures:
input:
result_files
output:
figures
shell:
"jupyter nbconvert --to notebook --execute notebook/analysis/visualize_results.ipynb"
rule metadata_to_tsv:
input:
"data/metadata_df.rda"
output:
"data/recount_metadata.tsv"
shell:
"Rscript saged/metadata_to_tsv.R"
rule download_recount:
output:
"data/metadata_df.rda",
"data/sra_counts.tsv"
shell:
"Rscript saged/download_recount3.R "
rule download_manifest:
output:
"data/manifest.tsv"
shell:
"bash saged/download_manifest.sh"
rule remove_scrna:
input:
"data/sra_counts.tsv",
"data/recount_metadata.tsv"
output:
"data/no_scrna_counts.tsv"
shell:
"python src/remove_scrnaseq.py "
"data/sra_counts.tsv "
"data/recount_metadata.tsv "
"data/no_scrna_counts.tsv "
rule normalize_data:
input:
"data/no_scrna_counts.tsv",
"data/gene_lengths.tsv"
output:
"data/no_scrna_tpm.tsv"
shell:
"python src/normalize_recount_data.py "
"data/no_scrna_counts.tsv "
"data/gene_lengths.tsv "
"data/no_scrna_tpm.tsv "
"data/recount_metadata.tsv "
rule get_gene_lengths:
output:
"data/gene_lengths.tsv"
shell:
"Rscript saged/get_gene_lengths.R "
rule get_tissue_labels:
input:
"data/recount_metadata.tsv",
"data/no_scrna_tpm.pkl"
output:
"data/recount_sample_to_label.pkl",
"data/no_scrna_tissue_subset.pkl",
shell:
"python src/get_tissue_data.py data/no_scrna_tpm.pkl data/recount_metadata.tsv "
"data/no_scrna_tissue_subset.pkl data/recount_sample_to_label.pkl"
rule pickle_counts:
input:
"data/no_scrna_tpm.tsv"
output:
"data/no_scrna_tpm.pkl"
shell:
"python src/pickle_tsv.py data/no_scrna_tpm.tsv data/no_scrna_tpm.pkl"
rule tissue_prediction:
threads: 4
input:
"data/no_scrna_tpm.pkl",
"data/recount_metadata.tsv",
"data/recount_sample_to_label.pkl",
supervised_model = "model_configs/supervised/{supervised}.yml",
dataset_config = "dataset_configs/recount_dataset.yml",
output:
"results/{tissue1}.{tissue2}.{supervised}_{seed}.tsv"
wildcard_constraints:
tissue1='[a-zA-Z]+_?[a-zA-Z]*',
tissue2='[a-zA-Z]+_?[a-zA-Z]*'
shell:
"python src/predict_tissue.py {input.dataset_config} {input.supervised_model} "
"results/{wildcards.tissue1}.{wildcards.tissue2}.{wildcards.supervised}_{wildcards.seed}.tsv "
"--neptune_config neptune.yml "
"--seed {wildcards.seed} "
"--tissue1 {wildcards.tissue1} "
"--tissue2 {wildcards.tissue2} "
"--weighted_loss "
# "--disable_optuna "
rule all_tissue_prediction:
threads: 8
input:
"data/no_scrna_tpm.pkl",
"data/recount_metadata.tsv",
"data/recount_sample_to_label.pkl",
supervised_model = "model_configs/supervised/{supervised}.yml",
dataset_config = "dataset_configs/recount_dataset.yml",
output:
"results/all-tissue.{supervised}_{seed}.tsv"
shell:
"python src/predict_tissue.py {input.dataset_config} {input.supervised_model} "
"results/all-tissue.{wildcards.supervised}_{wildcards.seed}.tsv "
"--neptune_config neptune.yml "
"--seed {wildcards.seed} "
"--all_tissue "
"--weighted_loss "
# "--disable_optuna "
rule all_tissue_sample_split:
threads: 8
input:
"data/no_scrna_tpm.pkl",
"data/recount_metadata.tsv",
"data/recount_sample_to_label.pkl",
supervised_model = "model_configs/supervised/{supervised}.yml",
dataset_config = "dataset_configs/recount_dataset.yml",
output:
"results/all-tissue_sample-split.{supervised}_{seed}.tsv"
shell:
"python src/predict_tissue.py {input.dataset_config} {input.supervised_model} "
"results/all-tissue_sample-split.{wildcards.supervised}_{wildcards.seed}.tsv "
"--neptune_config neptune.yml "
"--seed {wildcards.seed} "
"--all_tissue "
"--weighted_loss "
"--sample_split "
# "--disable_optuna "
rule tissue_prediction_signal_removed:
threads: 4
input:
"data/no_scrna_tpm.pkl",
"data/recount_metadata.tsv",
"data/recount_sample_to_label.pkl",
supervised_model = "model_configs/supervised/{supervised}.yml",
dataset_config = "dataset_configs/recount_dataset.yml",
output:
"results/{tissue1}.{tissue2}.{supervised}_{seed}-signal_removed.tsv"
shell:
"python src/predict_tissue.py {input.dataset_config} {input.supervised_model} "
"results/{wildcards.tissue1}.{wildcards.tissue2}.{wildcards.supervised}_{wildcards.seed}-signal_removed.tsv "
"--neptune_config neptune.yml "
"--seed {wildcards.seed} "
"--tissue1 {wildcards.tissue1} "
"--tissue2 {wildcards.tissue2} "
"--weighted_loss "
"--correction split_signal "
# "--disable_optuna "
rule tissue_prediction_signal_removed_sample_split:
threads: 4
input:
"data/no_scrna_tpm.pkl",
"data/recount_metadata.tsv",
"data/recount_sample_to_label.pkl",
supervised_model = "model_configs/supervised/{supervised}.yml",
dataset_config = "dataset_configs/recount_dataset.yml",
output:
"results/{tissue1}.{tissue2}.{supervised}_{seed}-signal_removed_sample_level.tsv"
shell:
"python src/predict_tissue.py {input.dataset_config} {input.supervised_model} "
"results/{wildcards.tissue1}.{wildcards.tissue2}.{wildcards.supervised}_{wildcards.seed}-signal_removed_sample_level.tsv "
"--neptune_config neptune.yml "
"--seed {wildcards.seed} "
"--tissue1 {wildcards.tissue1} "
"--tissue2 {wildcards.tissue2} "
"--weighted_loss "
"--correction split_signal "
"--sample_split "
# "--disable_optuna "
rule tissue_prediction_study_corrected:
threads: 4
input:
"data/no_scrna_tpm.pkl",
"data/recount_metadata.tsv",
"data/recount_sample_to_label.pkl",
supervised_model = "model_configs/supervised/{supervised}.yml",
dataset_config = "dataset_configs/recount_dataset.yml",
output:
"results/{tissue1}.{tissue2}.{supervised}_{seed}-study_corrected.tsv"
shell:
"python src/predict_tissue.py {input.dataset_config} {input.supervised_model} "
"results/{wildcards.tissue1}.{wildcards.tissue2}.{wildcards.supervised}_{wildcards.seed}-study_corrected.tsv "
"--neptune_config neptune.yml "
"--seed {wildcards.seed} "
"--tissue1 {wildcards.tissue1} "
"--tissue2 {wildcards.tissue2} "
"--weighted_loss "
"--correction study "
# "--disable_optuna "
rule all_tissue_prediction_be_corrected:
threads: 8
input:
"data/no_scrna_tpm.pkl",
"data/recount_metadata.tsv",
"data/recount_sample_to_label.pkl",
supervised_model = "model_configs/supervised/{supervised}.yml",
dataset_config = "dataset_configs/recount_dataset.yml",
output:
"results/all-tissue.{supervised}_{seed}_be_corrected.tsv"
shell:
"python src/predict_tissue.py {input.dataset_config} {input.supervised_model} "
"results/all-tissue.{wildcards.supervised}_{wildcards.seed}_be_corrected.tsv "
"--neptune_config neptune.yml "
"--seed {wildcards.seed} "
"--all_tissue "
"--correction study "
"--weighted_loss "
# "--disable_optuna "
rule all_tissue_prediction_signal_removed:
threads: 8
input:
"data/no_scrna_tpm.pkl",
"data/recount_metadata.tsv",
"data/recount_sample_to_label.pkl",
supervised_model = "model_configs/supervised/{supervised}.yml",
dataset_config = "dataset_configs/recount_dataset.yml",
output:
"results/all-tissue.{supervised}_{seed}_signal_removed.tsv"
shell:
"python src/predict_tissue.py {input.dataset_config} {input.supervised_model} "
"results/all-tissue.{wildcards.supervised}_{wildcards.seed}_signal_removed.tsv "
"--neptune_config neptune.yml "
"--seed {wildcards.seed} "
"--all_tissue "
"--correction split_signal "
"--weighted_loss "
# "--disable_optuna "
rule sample_level_control:
threads: 8
input:
"data/no_scrna_tpm.pkl",
"data/recount_metadata.tsv",
"data/recount_sample_to_label.pkl",
supervised_model = "model_configs/supervised/{supervised}.yml",
dataset_config = "dataset_configs/recount_dataset.yml",
output:
"results/sample-split.{supervised}_{seed}.tsv"
shell:
"python src/sample_split_control.py {input.dataset_config} {input.supervised_model} "
"results/sample-split.{wildcards.supervised}_{wildcards.seed}.tsv "
"--neptune_config neptune.yml "
"--seed {wildcards.seed} "
"--sample_split "
"--weighted_loss "
rule sample_level_control_signal_removed:
threads: 8
input:
"data/no_scrna_tpm.pkl",
"data/recount_metadata.tsv",
"data/recount_sample_to_label.pkl",
supervised_model = "model_configs/supervised/{supervised}.yml",
dataset_config = "dataset_configs/recount_dataset.yml",
output:
"results/sample-split-signal-removed.{supervised}_{seed}.tsv"
shell:
"python src/sample_split_control.py {input.dataset_config} {input.supervised_model} "
"results/sample-split-signal-removed.{wildcards.supervised}_{wildcards.seed}.tsv "
"--neptune_config neptune.yml "
"--seed {wildcards.seed} "
"--sample_split "
"--weighted_loss "
"--correction split_signal "
rule sample_level_be_corrected:
threads: 8
input:
"data/no_scrna_tpm.pkl",
"data/recount_metadata.tsv",
"data/recount_sample_to_label.pkl",
supervised_model = "model_configs/supervised/{supervised}.yml",
dataset_config = "dataset_configs/recount_dataset.yml",
output:
"results/sample-split-study-corrected.{supervised}_{seed}.tsv"
shell:
"python src/sample_split_control.py {input.dataset_config} {input.supervised_model} "
"results/sample-split-study-corrected.{wildcards.supervised}_{wildcards.seed}.tsv "
"--neptune_config neptune.yml "
"--seed {wildcards.seed} "
"--sample_split "
"--weighted_loss "
"--correction study "
rule study_level_control:
threads: 8
input:
"data/no_scrna_tpm.pkl",
"data/recount_metadata.tsv",
"data/recount_sample_to_label.pkl",
supervised_model = "model_configs/supervised/{supervised}.yml",
dataset_config = "dataset_configs/recount_dataset.yml",
output:
"results/study-split.{supervised}_{seed}.tsv"
shell:
"python src/sample_split_control.py {input.dataset_config} {input.supervised_model} "
"results/study-split.{wildcards.supervised}_{wildcards.seed}.tsv "
"--neptune_config neptune.yml "
"--seed {wildcards.seed} "
"--weighted_loss "
rule study_level_sex_prediction:
threads: 5
input:
"data/combined_human_mouse_meta_v2.csv",
"data/no_scrna_tpm.pkl",
"data/recount_metadata.tsv",
"data/recount_sample_to_label.pkl",
supervised_model = "model_configs/supervised/{supervised}.yml",
dataset_config = "dataset_configs/recount_dataset.yml",
output:
"results/study-split-sex-prediction.{supervised}_{seed}.tsv"
shell:
"python src/predict_tissue.py {input.dataset_config} {input.supervised_model} "
"results/study-split-sex-prediction.{wildcards.supervised}_{wildcards.seed}.tsv "
"--neptune_config neptune.yml "
"--seed {wildcards.seed} "
"--weighted_loss "
"--use_sex_labels "
# "--disable_optuna "
rule sex_prediction_signal_removed:
threads: 5
input:
"data/combined_human_mouse_meta_v2.csv",
"data/no_scrna_tpm.pkl",
"data/recount_metadata.tsv",
"data/recount_sample_to_label.pkl",
supervised_model = "model_configs/supervised/{supervised}.yml",
dataset_config = "dataset_configs/recount_dataset.yml",
output:
"results/sex-prediction-signal-removed.{supervised}_{seed}.tsv"
shell:
"python src/predict_tissue.py {input.dataset_config} {input.supervised_model} "
"results/sex-prediction-signal-removed.{wildcards.supervised}_{wildcards.seed}.tsv "
"--neptune_config neptune.yml "
"--seed {wildcards.seed} "
"--weighted_loss "
"--use_sex_labels "
# "--disable_optuna "
"--correction split_signal "
rule sample_level_control_sex_prediction:
threads: 8
input:
"data/combined_human_mouse_meta_v2.csv",
"data/no_scrna_tpm.pkl",
"data/recount_metadata.tsv",
"data/recount_sample_to_label.pkl",
supervised_model = "model_configs/supervised/{supervised}.yml",
dataset_config = "dataset_configs/recount_dataset.yml",
output:
"results/sample-split-sex-prediction.{supervised}_{seed}.tsv"
shell:
"python src/predict_tissue.py {input.dataset_config} {input.supervised_model} "
"results/sample-split-sex-prediction.{wildcards.supervised}_{wildcards.seed}.tsv "
"--neptune_config neptune.yml "
"--seed {wildcards.seed} "
"--sample_split "
"--weighted_loss "
"--use_sex_labels "
# "--disable_optuna "
rule study_level_signal_removed:
threads: 8
input:
"data/no_scrna_tpm.pkl",
"data/recount_metadata.tsv",
"data/recount_sample_to_label.pkl",
supervised_model = "model_configs/supervised/{supervised}.yml",
dataset_config = "dataset_configs/recount_dataset.yml",
output:
"results/study-split-signal-removed.{supervised}_{seed}.tsv"
shell:
"python src/sample_split_control.py {input.dataset_config} {input.supervised_model} "
"results/study-split-signal-removed.{wildcards.supervised}_{wildcards.seed}.tsv "
"--neptune_config neptune.yml "
"--seed {wildcards.seed} "
"--weighted_loss "
"--correction split_signal "
rule study_level_be_corrected:
threads: 8
input:
"data/no_scrna_tpm.pkl",
"data/recount_metadata.tsv",
"data/recount_sample_to_label.pkl",
supervised_model = "model_configs/supervised/{supervised}.yml",
dataset_config = "dataset_configs/recount_dataset.yml",
output:
"results/study-split-study-corrected.{supervised}_{seed}.tsv"
shell:
"python src/sample_split_control.py {input.dataset_config} {input.supervised_model} "
"results/study-split-study-corrected.{wildcards.supervised}_{wildcards.seed}.tsv "
"--neptune_config neptune.yml "
"--seed {wildcards.seed} "
"--weighted_loss "
"--correction study "
rule tissue_split:
threads: 8
input:
"data/no_scrna_tpm.pkl",
"data/recount_metadata.tsv",
"data/recount_sample_to_label.pkl",
supervised_model = "model_configs/supervised/{supervised}.yml",
dataset_config = "dataset_configs/recount_dataset.yml",
output:
"results/tissue-split.{supervised}_{seed}.tsv"
shell:
"python src/tissue_split.py {input.dataset_config} {input.supervised_model} "
"results/tissue-split.{wildcards.supervised}_{wildcards.seed}.tsv "
"--neptune_config neptune.yml "
"--seed {wildcards.seed} "
"--weighted_loss "
rule download_gtex:
output:
"data/gtex_tpm.gct",
"data/gtex_sample_attributes.txt"
shell:
"bash saged/download_gtex_data.sh"
rule preprocess_gtex:
input:
"data/gtex_tpm.gct"
output:
"data/gtex_normalized.tsv"
shell:
"python src/normalize_gtex.py data/gtex_tpm.gct data/gtex_normalized.tsv"
rule pickle_gtex:
input:
"data/gtex_normalized.tsv"
output:
"data/gtex_normalized.pkl"
shell:
"python src/pickle_tsv.py data/gtex_normalized.tsv data/gtex_normalized.pkl"
rule all_tissue_gtex:
threads: 5
input:
"data/gtex_normalized.pkl",
"data/gtex_sample_attributes.txt",
supervised_model = "model_configs/supervised/{supervised}.yml",
dataset_config = "dataset_configs/gtex_dataset.yml",
output:
"results/gtex-all-tissue.{supervised}_{seed}.tsv"
shell:
"python src/predict_tissue.py {input.dataset_config} {input.supervised_model} "
"results/gtex-all-tissue.{wildcards.supervised}_{wildcards.seed}.tsv "
"--neptune_config neptune.yml "
"--seed {wildcards.seed} "
"--all_tissue "
"--weighted_loss "
# "--disable_optuna "
"--dataset gtex"
rule all_tissue_signal_removed_gtex:
threads: 8
input:
"data/gtex_normalized.pkl",
"data/gtex_sample_attributes.txt",
supervised_model = "model_configs/supervised/{supervised}.yml",
dataset_config = "dataset_configs/gtex_dataset.yml",
output:
"results/gtex-all-tissue-signal-removed.{supervised}_{seed}.tsv"
shell:
"python src/predict_tissue.py {input.dataset_config} {input.supervised_model} "
"results/gtex-all-tissue-signal-removed.{wildcards.supervised}_{wildcards.seed}.tsv "
"--neptune_config neptune.yml "
"--seed {wildcards.seed} "
"--all_tissue "
"--weighted_loss "
# "--disable_optuna "
"--dataset gtex "
"--correction split_signal "
rule gtex_binary_prediction:
threads: 4
input:
"data/gtex_normalized.pkl",
"data/gtex_sample_attributes.txt",
supervised_model = "model_configs/supervised/{supervised}.yml",
dataset_config = "dataset_configs/gtex_dataset.yml",
output:
"results/gtex.{tissue1}.{tissue2}.{supervised}_{seed}.tsv"
shell:
"python src/predict_tissue.py {input.dataset_config} {input.supervised_model} "
"results/gtex.{wildcards.tissue1}.{wildcards.tissue2}.{wildcards.supervised}_{wildcards.seed}.tsv "
"--neptune_config neptune.yml "
"--seed {wildcards.seed} "
"--tissue1 {wildcards.tissue1} "
"--tissue2 {wildcards.tissue2} "
"--weighted_loss "
# "--disable_optuna "
"--dataset gtex "
rule gtex_binary_prediction_signal_removed:
threads: 4
input:
"data/gtex_normalized.pkl",
"data/gtex_sample_attributes.txt",
supervised_model = "model_configs/supervised/{supervised}.yml",
dataset_config = "dataset_configs/gtex_dataset.yml",
output:
"results/gtex-signal-removed.{tissue1}.{tissue2}.{supervised}_{seed}.tsv"
shell:
"python src/predict_tissue.py {input.dataset_config} {input.supervised_model} "
"results/gtex-signal-removed.{wildcards.tissue1}.{wildcards.tissue2}.{wildcards.supervised}_{wildcards.seed}.tsv "
"--neptune_config neptune.yml "
"--seed {wildcards.seed} "
"--tissue1 {wildcards.tissue1} "
"--tissue2 {wildcards.tissue2} "
"--weighted_loss "
# "--disable_optuna "
"--dataset gtex "
"--correction split_signal "
rule simulate_data:
threads: 8
output:
"data/batch_sim_data.tsv"
shell:
"python src/simulate_be_data.py {output}"
rule simulate_linear_data:
threads: 8
output:
"data/linear_batch_sim_data.tsv"
shell:
"python src/simulate_be_data.py {output} --n_nonlinear 0"
rule simulate_no_signal_data:
threads: 8
output:
"data/no_signal_batch_sim_data.tsv"
shell:
"python src/simulate_be_data.py {output} --n_linear 0 --n_nonlinear 0 --n_random 2500"
rule sim_prediction:
threads: 8
input:
supervised_model = "model_configs/supervised/{supervised}.yml",
dataset_config = "dataset_configs/sim_dataset.yml",
data="data/batch_sim_data.tsv"
output:
"results/sim-data.{supervised}_{seed}.tsv"
shell:
"python src/predict_tissue.py {input.dataset_config} {input.supervised_model} "
"results/sim-data.{wildcards.supervised}_{wildcards.seed}.tsv "
"--neptune_config neptune.yml "
"--seed {wildcards.seed} "
"--all_tissue "
"--weighted_loss "
"--disable_optuna "
"--dataset sim "
rule sim_prediction_signal_removed:
threads: 8
input:
supervised_model = "model_configs/supervised/{supervised}.yml",
dataset_config = "dataset_configs/sim_dataset.yml",
data="data/batch_sim_data.tsv"
output:
"results/sim-data-signal-removed.{supervised}_{seed}.tsv"
shell:
"python src/predict_tissue.py {input.dataset_config} {input.supervised_model} "
"results/sim-data-signal-removed.{wildcards.supervised}_{wildcards.seed}.tsv "
"--neptune_config neptune.yml "
"--seed {wildcards.seed} "
"--all_tissue "
"--weighted_loss "
"--disable_optuna "
"--correction split_signal "
"--dataset sim "
rule linear_sim_prediction:
threads: 8
input:
supervised_model = "model_configs/supervised/{supervised}.yml",
dataset_config = "dataset_configs/linear_sim_dataset.yml",
data="data/linear_batch_sim_data.tsv"
output:
"results/linear-sim-data.{supervised}_{seed}.tsv"
shell:
"python src/predict_tissue.py {input.dataset_config} {input.supervised_model} "
"results/linear-sim-data.{wildcards.supervised}_{wildcards.seed}.tsv "
"--neptune_config neptune.yml "
"--seed {wildcards.seed} "
"--all_tissue "
"--weighted_loss "
"--disable_optuna "
"--dataset sim"
rule linear_sim_prediction_signal_removed:
threads: 8
input:
supervised_model = "model_configs/supervised/{supervised}.yml",
dataset_config = "dataset_configs/linear_sim_dataset.yml",
data="data/linear_batch_sim_data.tsv"
output:
"results/linear-sim-data-signal-removed.{supervised}_{seed}.tsv"
shell:
"python src/predict_tissue.py {input.dataset_config} {input.supervised_model} "
"results/linear-sim-data-signal-removed.{wildcards.supervised}_{wildcards.seed}.tsv "
"--neptune_config neptune.yml "
"--seed {wildcards.seed} "
"--all_tissue "
"--weighted_loss "
"--disable_optuna "
"--correction split_signal "
"--dataset sim"
rule no_signal_sim_prediction:
threads: 8
input:
supervised_model = "model_configs/supervised/{supervised}.yml",
dataset_config = "dataset_configs/no_signal_sim_dataset.yml",
data="data/no_signal_batch_sim_data.tsv"
output:
"results/no-signal-sim-data.{supervised}_{seed}.tsv"
shell:
"python src/predict_tissue.py {input.dataset_config} {input.supervised_model} "
"results/no-signal-sim-data.{wildcards.supervised}_{wildcards.seed}.tsv "
"--neptune_config neptune.yml "
"--seed {wildcards.seed} "
"--all_tissue "
"--weighted_loss "
"--disable_optuna "
"--dataset sim "
rule no_signal_sim_prediction_signal_removed:
threads: 8
input:
supervised_model = "model_configs/supervised/{supervised}.yml",
dataset_config = "dataset_configs/no_signal_sim_dataset.yml",
data="data/no_signal_batch_sim_data.tsv"
output:
"results/no-signal-sim-data-signal-removed.{supervised}_{seed}.tsv"
shell:
"python src/predict_tissue.py {input.dataset_config} {input.supervised_model} "
"results/no-signal-sim-data-signal-removed.{wildcards.supervised}_{wildcards.seed}.tsv "
"--neptune_config neptune.yml "
"--seed {wildcards.seed} "
"--all_tissue "
"--weighted_loss "
"--disable_optuna "
"--correction signal "
"--dataset sim "
rule no_signal_sim_prediction_split:
threads: 8
input:
supervised_model = "model_configs/supervised/{supervised}.yml",
dataset_config = "dataset_configs/no_signal_sim_dataset.yml",
data="data/no_signal_batch_sim_data.tsv"
output:
"results/no-signal-sim-data-split-signal.{supervised}_{seed}.tsv"
shell:
"python src/predict_tissue.py {input.dataset_config} {input.supervised_model} "
"results/no-signal-sim-data-split-signal.{wildcards.supervised}_{wildcards.seed}.tsv "
"--neptune_config neptune.yml "
"--seed {wildcards.seed} "
"--all_tissue "
"--weighted_loss "
"--disable_optuna "
"--correction split_signal "
"--dataset sim "
rule sim_split_signal:
threads: 8
input:
supervised_model = "model_configs/supervised/{supervised}.yml",
dataset_config = "dataset_configs/sim_dataset.yml",
data="data/batch_sim_data.tsv"
output:
"results/sim-data-split-signal.{supervised}_{seed}.tsv"
shell:
"python src/predict_tissue.py {input.dataset_config} {input.supervised_model} "
"results/sim-data-split-signal.{wildcards.supervised}_{wildcards.seed}.tsv "
"--neptune_config neptune.yml "
"--seed {wildcards.seed} "
"--all_tissue "
"--weighted_loss "
"--disable_optuna "
"--dataset sim "
"--correction split_signal "
# Reviewer requested rules:
rule subset_recount_data:
threads: 1
input:
"data/no_scrna_counts.tsv"
output:
"data/recount_gtex_genes.tsv"
shell:
"python src/normalize_recount_gtex_genes.py data/no_scrna_counts.tsv data/gene_lengths.tsv "
"data/recount_gtex_genes.tsv data/recount_metadata.tsv data/gtex_normalized.tsv"
rule change_gene_order:
threads: 1
input:
"data/recount_gtex_genes.tsv",
"data/gtex_normalized.tsv"
output:
"data/reformatted_recount.tsv"
shell:
"python src/reorder_genes.py data/recount_gtex_genes.tsv "
"data/gtex_normalized.tsv data/reformatted_recount.tsv "
rule pickle_recount_gtex:
input:
"data/reformatted_recount.tsv"
output:
"data/reformatted_recount.pkl"
shell:
"python src/pickle_tsv.py {input} data/reformatted_recount.pkl"
rule recount_to_gtex_binary:
threads: 4
input:
"data/reformatted_recount.pkl",
"data/recount_metadata.tsv",
"data/recount_sample_to_label.pkl",
"data/gtex_normalized.pkl",
"data/gtex_sample_attributes.txt",
supervised_model = "model_configs/supervised/{supervised}.yml",
dataset_config = "dataset_configs/recount_gtex_genes.yml",
transfer_config = "dataset_configs/gtex_dataset.yml"
output:
"results/recount_transfer.{tissue1}.{tissue2}.{supervised}_{seed}.tsv"
wildcard_constraints:
tissue1='[a-zA-Z]+_?[a-zA-Z]*',
tissue2='[a-zA-Z]+_?[a-zA-Z]*'
shell:
"python src/transfer_model.py {input.dataset_config} {input.transfer_config} {input.supervised_model} "
"results/recount_transfer.{wildcards.tissue1}.{wildcards.tissue2}.{wildcards.supervised}_{wildcards.seed}.tsv "
"--neptune_config neptune.yml "
"--seed {wildcards.seed} "
"--tissue1 {wildcards.tissue1} "
"--tissue2 {wildcards.tissue2} "
"--weighted_loss "
"--dataset recount "
"--disable_optuna "
rule gtex_to_recount_binary:
threads: 4
input:
"data/reformatted_recount.pkl",
"data/recount_metadata.tsv",
"data/recount_sample_to_label.pkl",
"data/gtex_normalized.pkl",
"data/gtex_sample_attributes.txt",
supervised_model = "model_configs/supervised/{supervised}.yml",
dataset_config = "dataset_configs/gtex_dataset.yml",
transfer_config = "dataset_configs/recount_gtex_genes.yml",
output:
"results/gtex_transfer.{tissue1}.{tissue2}.{supervised}_{seed}.tsv"
wildcard_constraints:
tissue1='[a-zA-Z]+_?[a-zA-Z]*',
tissue2='[a-zA-Z]+_?[a-zA-Z]*'
shell:
"python src/transfer_model.py {input.dataset_config} {input.transfer_config} {input.supervised_model} "
"results/gtex_transfer.{wildcards.tissue1}.{wildcards.tissue2}.{wildcards.supervised}_{wildcards.seed}.tsv "
"--neptune_config neptune.yml "
"--seed {wildcards.seed} "
"--tissue1 {wildcards.tissue1} "
"--tissue2 {wildcards.tissue2} "
"--weighted_loss "
"--dataset gtex "
"--disable_optuna "
rule recount_to_gtex_binary_signal_removed:
threads: 4
input:
"data/reformatted_recount.pkl",
"data/recount_metadata.tsv",
"data/recount_sample_to_label.pkl",
"data/gtex_normalized.pkl",
"data/gtex_sample_attributes.txt",
supervised_model = "model_configs/supervised/{supervised}.yml",
dataset_config = "dataset_configs/recount_gtex_genes.yml",
transfer_config = "dataset_configs/gtex_dataset.yml"
output:
"results/recount_transfer.split_signal.{tissue1}.{tissue2}.{supervised}_{seed}.tsv"