From a0a8f02e0b975bfe253ba935f8ecc4f4a605751d Mon Sep 17 00:00:00 2001 From: Stephanie Hicks Date: Thu, 15 Aug 2019 09:12:25 -0400 Subject: [PATCH] adding DMRs from WGBS BLUEPRINT data --- R/find_dmrs_wgbs.R | 200 ++++++++++++++++++ data/blueprint_blood_regions_dmrseq_bcell.RDS | Bin 0 -> 36210 bytes data/blueprint_blood_regions_dmrseq_cd4t.RDS | Bin 0 -> 19396 bytes data/blueprint_blood_regions_dmrseq_cd8t.RDS | Bin 0 -> 21696 bytes data/blueprint_blood_regions_dmrseq_gran.RDS | Bin 0 -> 24474 bytes data/blueprint_blood_regions_dmrseq_mono.RDS | Bin 0 -> 16322 bytes data/blueprint_blood_regions_dmrseq_nk.RDS | Bin 0 -> 47603 bytes 7 files changed, 200 insertions(+) create mode 100644 R/find_dmrs_wgbs.R create mode 100644 data/blueprint_blood_regions_dmrseq_bcell.RDS create mode 100644 data/blueprint_blood_regions_dmrseq_cd4t.RDS create mode 100644 data/blueprint_blood_regions_dmrseq_cd8t.RDS create mode 100644 data/blueprint_blood_regions_dmrseq_gran.RDS create mode 100644 data/blueprint_blood_regions_dmrseq_mono.RDS create mode 100644 data/blueprint_blood_regions_dmrseq_nk.RDS diff --git a/R/find_dmrs_wgbs.R b/R/find_dmrs_wgbs.R new file mode 100644 index 0000000..74d4b61 --- /dev/null +++ b/R/find_dmrs_wgbs.R @@ -0,0 +1,200 @@ +#' @title find_dmrs_wgbs +#' +#' @description Add here. +#' +#' @param verbose Add here. +#' @param gr_target Add here. +#' @param include_cpgs Add here. +#' @param include_dmrs Add here. +#' @param num_cpgs Add here. +#' @param num_regions Add here. +#' @param bumphunter_beta_cutoff Add here. +#' @param dmr_up_cutoff Add here. +#' @param dmr_down_cutoff Add here. +#' @param dmr_pval_cutoff Add here. +#' @param cpg_pval_cutoff Add here. +#' @param cpg_up_dm_cutoff Add here. +#' @param cpg_down_dm_cutoff Add here. +#' @param pairwise_comparison Add here. +#' @param mset_train_flow_sort Add here. +#' +#' @export +#' +#' @return Add here. +#' +#' @details +#' Add here. +#' +#' @aliases find_dmrs_wgbs +#' +#' @docType methods +#' @name find_dmrs_wgbs +#' +#' @import minfi +#' @import FlowSorted.Blood.450k +#' @importFrom plyranges arrange +#' @importFrom S4Vectors queryHits +#' @importFrom utils head +#' @importFrom bumphunter clusterMaker +#' @importFrom stats model.matrix +#' @importFrom genefilter rowttests +#' +#' @examples +#' found_regions <- find_dmrs_wgbs() +#' +#' @rdname find_dmrs_wgbs +#' @export +find_dmrs_wgbs <- function(verbose=TRUE, gr_target=NULL, + num_regions=50, bumphunter_beta_cutoff = 0.2, + dmr_up_cutoff = 0.5, dmr_down_cutoff = 0.4, + dmr_pval_cutoff = 1e-11, + dmrseq_search = FALSE, workers = 1) { + + + library(rhdf5) + library(HDF5Array) + library(bsseq) + + dataPath <- "/users/shicks1/data/DNAm/blueprint_ihec" + hdf5_bs_se_path <- file.path(dataPath, "files_bsseq_hdf5_se") + bs <- loadHDF5SummarizedExperiment(hdf5_bs_se_path) + + IDs = c("Gran", "CD4T", "CD8T", "Bcell","Mono", "NK") + + # extract beta values, phenotypic information and GRanges objects + cell <- factor(bs$cell_type, levels = IDs) + cell_levels <- levels(cell) + + # define design matrix to search for DMRs + xmat = model.matrix(~ cell - 1) + colnames(xmat) = cell_levels + pData(bs) <- cbind(pData(bs), xmat) + + all_poss = diag(length(cell_levels)) + all_poss <- (all_poss == TRUE) + colnames(all_poss) <- cell_levels + + # find celltype specific regions using only overlap CpGs in target object + if(!is.null(gr_target)){ + # which of the WGBS CpGs overlap with the target CpGs + zz <- findOverlaps(granges(bs), gr_target) + bs <- bs[queryHits(zz), ] + if(verbose){ + mes <- "[estimatecc] gr_target is not null. Using %s overlapping CpGs." + message(sprintf(mes, nrow(bs))) + } + } + + regs <- vector("list", length(IDs)) + regions_all <- GRanges() + zmat <- c() # regions_all, will contain all celltype-specific DMRs + + for(ind in seq_len(nrow(all_poss))){ + + if(!dmrseq_search){ + if(verbose){ + mes <- "[estimatecc] Loading %s cell type-specific regions." + message(sprintf(mes, cell_levels[ind])) + } + regs[[ind]] <- readRDS(file = file.path("data", + paste0("blueprint_blood_regions_dmrseq_", + tolower(IDs[ind]),".RDS"))) + } else { + library(BiocParallel) + register(MulticoreParam(workers)) + + if(verbose){ + mes <- "[estimatecc] Searching for %s cell type-specific regions." + message(sprintf(mes, cell_levels[ind])) + } + regs[[ind]] <- dmrseq(bs=bs, testCovariate=IDs[ind], minNumRegion = 3, + cutoff = bumphunter_beta_cutoff, verbose = TRUE) + } + + keep_dmrs = .pick_target_positions(target_granges = granges(bs), + target_object = getCoverage(bs, type = "M"), + target_cvg = getCoverage(bs, type = "Cov"), + dmp_regions = regs[[ind]])$dmp_granges + + # y_regions are the beta values collapsed (CpGs averaged) by regions from bumphunter + y_regions <- as.matrix(mcols(keep_dmrs)) + + tmp <- genefilter::rowttests(x = y_regions,fac = factor(pData(bs)[, IDs[ind]])) + regs[[ind]]$ttest_pval <- tmp$p.value + regs[[ind]]$ttest_dm <- tmp$dm + regs[[ind]]$dmr_up_max_diff <- apply(abs(sweep(y_regions, 2, (pData(bs)[, IDs[ind]]), FUN = "-")), 1, max) + regs[[ind]]$dmr_down_max_diff <- apply(abs(sweep(y_regions, 2, (1 - pData(bs)[, IDs[ind]]), FUN = "-")), 1, max) + + # Apply quality control + keep_ind_regions <- (regs[[ind]]$qval < 0.05) & # (regs[[ind]]$area > 1) # & + (regs[[ind]]$ttest_pval < dmr_pval_cutoff) # ideally less than 1e-11 + regs[[ind]] <- regs[[ind]][keep_ind_regions, ] + gr_regions_up <- regs[[ind]][(regs[[ind]]$stat > 0) & + (regs[[ind]]$dmr_up_max_diff < dmr_up_cutoff), ] + gr_regions_down <- regs[[ind]][(regs[[ind]]$stat < 0) & + (regs[[ind]]$dmr_down_max_diff < dmr_down_cutoff), ] + + if(length(gr_regions_up) > 0){ + gr_regions_up <- gr_regions_up[, names(mcols(gr_regions_up)) %in% + c("L", "area", "stat", "ttest_dm", + "ttest_pval", "dmr_up_max_diff")] + names(mcols(gr_regions_up))[ + names(mcols(gr_regions_up)) == "dmr_up_max_diff"] <- "dmr_max_diff" + gr_regions_up <- gr_regions_up[order(-gr_regions_up$stat), ] + gr_regions_up <- gr_regions_up[seq_len(min(length(gr_regions_up), num_regions)), ] + } else { + gr_regions_up <- GRanges() + } + + if(length(gr_regions_down) > 0){ + gr_regions_down <- gr_regions_down[, names(mcols(gr_regions_down)) %in% + c("L", "area", "stat", "ttest_dm", + "ttest_pval", "dmr_down_max_diff")] + names(mcols(gr_regions_down))[ + names(mcols(gr_regions_down)) == "dmr_down_max_diff"] <- "dmr_max_diff" + gr_regions_down <- gr_regions_down[order(gr_regions_down$stat), ] + gr_regions_down <- gr_regions_down[seq_len(min(length(gr_regions_down), num_regions)), ] + } else { + gr_regions_down <- GRanges() + } + + mcols(gr_regions_up)$status <- rep("Up", length(gr_regions_up)) + mcols(gr_regions_down)$status <- rep("Down", length(gr_regions_down)) + bump_mat_all <- c(gr_regions_up, gr_regions_down) + mcols(bump_mat_all)$cellType <- rep(cell_levels[ind], length(bump_mat_all)) + + if(verbose){ + mes <- "[estimatecc] Found %s %s cell type-specific regions." + message(sprintf(mes, length(bump_mat_all), cell_levels[ind])) + } + if(length(bump_mat_all) > 0){ + regions_all <- c(regions_all, bump_mat_all) + } + if(length(gr_regions_up) > 0){ + zmat <- rbind(zmat, t(replicate(min(length(gr_regions_up), num_regions), + as.numeric(all_poss[ind,])))) + } + if(length(gr_regions_down) > 0){ + zmat <- rbind(zmat, t(replicate(min(length(gr_regions_down), num_regions), + as.numeric(!all_poss[ind,])))) + } + } + + colnames(zmat) <- cell_levels + + keep_dmrs = .pick_target_positions(target_granges = granges(bs), + target_object = getCoverage(bs, type = "M"), + target_cvg = getCoverage(bs, type = "Cov"), + dmp_regions = regions_all)$dmp_granges + y_regions <- as.matrix(mcols(keep_dmrs)) + + profiles <- sapply(.splitit(cell),function(ind){ rowMeans(y_regions[,ind]) } ) + + removeMe <- duplicated(regions_all) + list(regions_all = regions_all[!removeMe,], + zmat = zmat[!removeMe,], + y_regions = y_regions[!removeMe,], + profiles = profiles[!removeMe,], + cell = cell, cell_mat = all_poss, + cell_levels = cell_levels, pd = pData(bs)) +} diff --git a/data/blueprint_blood_regions_dmrseq_bcell.RDS b/data/blueprint_blood_regions_dmrseq_bcell.RDS new file mode 100644 index 0000000000000000000000000000000000000000..5bd2508190a9bef7fa5715f32548e3268924eddb GIT binary patch literal 36210 zcmV(*K;FL}iwFP!000001MK|=R256RE(+Jo8b0THoVKtV)6a*~{L&f)JVb1wN@Ywi8*v+w!uIr}chsPS}He8cm;RZaIC zu3-ZJ5CMro0z?u31d=EKWFlTi0A#?5Ba5Hso}KPKo_>GPMh$S^;g7cf5+`2Z&ldV@ z0C3@jh8MgZursdl=>Z>J$c$?qywF#t;Dr}2{CMGD+_N&~q1Or0rC{8%F#6IM_w>Hh zIeppYtii`<=Vr`DVe}!-nS(i&#*mqfu?7cYJSU@$gVC2Z=bpJfnW48Zqn;@TjWHJ+ 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