Mercurial > repos > bgruening > diffbind
diff diffbind.R @ 17:2605cbdaa7d8 draft
planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/diffbind commit 3da34ac6e5b18fd5deacaf31b757aca6bae82251
author | iuc |
---|---|
date | Fri, 15 Dec 2023 19:39:14 +0000 |
parents | 163688bb8f73 |
children | f907216064f6 |
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--- a/diffbind.R Wed Nov 18 12:54:07 2020 +0000 +++ b/diffbind.R Fri Dec 15 19:39:14 2023 +0000 @@ -1,14 +1,15 @@ ## Setup R error handling to go to stderr -options(show.error.messages = F, error = function() { - cat(geterrmessage(), file = stderr()); q("no", 1, F) +options(show.error.messages = FALSE, error = function() { + cat(geterrmessage(), file = stderr()) + q("no", 1, FALSE) }) # we need that to not crash galaxy with an UTF8 error on German LC settings. Sys.setlocale("LC_MESSAGES", "en_US.UTF-8") suppressPackageStartupMessages({ - library("getopt") - library("DiffBind") - library("rjson") + library("getopt") + library("DiffBind") + library("rjson") }) options(stringAsfactors = FALSE, useFancyQuotes = FALSE) @@ -17,28 +18,28 @@ #get options, using the spec as defined by the enclosed list. #we read the options from the default: commandArgs(TRUE). spec <- matrix(c( - "infile", "i", 1, "character", - "outfile", "o", 1, "character", - "scorecol", "n", 1, "integer", - "lowerbetter", "l", 1, "logical", - "summits", "s", 1, "integer", - "th", "t", 1, "double", - "format", "f", 1, "character", - "plots", "p", 2, "character", - "bmatrix", "b", 0, "logical", - "rdaOpt", "r", 0, "logical", - "infoOpt", "a", 0, "logical", - "verbose", "v", 2, "integer", - "help", "h", 0, "logical" -), byrow = TRUE, ncol = 4); + "infile", "i", 1, "character", + "outfile", "o", 1, "character", + "scorecol", "n", 1, "integer", + "lowerbetter", "l", 1, "logical", + "summits", "s", 1, "integer", + "th", "t", 1, "double", + "format", "f", 1, "character", + "plots", "p", 2, "character", + "bmatrix", "b", 0, "logical", + "rdaOpt", "r", 0, "logical", + "infoOpt", "a", 0, "logical", + "verbose", "v", 2, "integer", + "help", "h", 0, "logical" +), byrow = TRUE, ncol = 4) -opt <- getopt(spec); +opt <- getopt(spec) # if help was asked for print a friendly message # and exit with a non-zero error code if (!is.null(opt$help)) { - cat(getopt(spec, usage = TRUE)); - q(status = 1); + cat(getopt(spec, usage = TRUE)) + q(status = 1) } parser <- newJSONParser() @@ -54,28 +55,31 @@ samples <- sapply(strsplit(peaks, "-"), `[`, 2) if (length(ctrls) != 0) { - sample_table <- data.frame(SampleID = samples, - Condition = groups, - bamReads = bams, - bamControl = ctrls, - Peaks = peaks, - Tissue = samples) # using "Tissue" column to display ids as labels in PCA plot + sample_table <- data.frame( + SampleID = samples, + Condition = groups, + bamReads = bams, + bamControl = ctrls, + Peaks = peaks, + Tissue = samples + ) # using "Tissue" column to display ids as labels in PCA plot } else { - - sample_table <- data.frame(SampleID = samples, - Replicate = samples, - Condition = groups, - bamReads = bams, - Peaks = peaks, - Tissue = samples) + sample_table <- data.frame( + SampleID = samples, + Replicate = samples, + Condition = groups, + bamReads = bams, + Peaks = peaks, + Tissue = samples + ) } sample <- dba(sampleSheet = sample_table, peakFormat = "bed", scoreCol = opt$scorecol, bLowerScoreBetter = opt$lowerbetter) if (!is.null(opt$summits)) { - sample_count <- dba.count(sample, summits = opt$summits) + sample_count <- dba.count(sample, summits = opt$summits) } else { - sample_count <- dba.count(sample) + sample_count <- dba.count(sample) } sample_contrast <- dba.contrast(sample_count, categories = DBA_CONDITION, minMembers = 2) @@ -84,74 +88,82 @@ # Generate plots if (!is.null(opt$plots)) { - pdf(opt$plots) - orvals <- dba.plotHeatmap(sample_analyze, contrast = 1, correlations = FALSE, cexCol = 0.8, th = opt$th) - dba.plotPCA(sample_analyze, contrast = 1, th = opt$th, label = DBA_TISSUE, labelSize = 0.3) - dba.plotMA(sample_analyze, th = opt$th) - dba.plotVolcano(sample_analyze, th = opt$th) - dba.plotBox(sample_analyze, th = opt$th) - dev.off() + pdf(opt$plots) + orvals <- dba.plotHeatmap(sample_analyze, contrast = 1, correlations = FALSE, cexCol = 0.8, th = opt$th) + dba.plotPCA(sample_analyze, contrast = 1, th = opt$th, label = DBA_TISSUE, labelSize = 0.3) + dba.plotMA(sample_analyze, th = opt$th) + dba.plotVolcano(sample_analyze, th = opt$th) + dba.plotBox(sample_analyze, th = opt$th) + dev.off() } # Output differential binding sites res_sorted <- diff_bind[order(diff_bind$FDR), ] # Convert from GRanges (1-based) to 0-based format (adapted from https://www.biostars.org/p/89341/) if (opt$format == "bed") { - res_sorted <- data.frame(Chrom = seqnames(res_sorted), - Start = start(res_sorted) - 1, - End = end(res_sorted), - Name = rep("DiffBind", length(res_sorted)), - Score = rep("0", length(res_sorted)), - Strand = gsub("\\*", ".", strand(res_sorted))) + res_sorted <- data.frame( + Chrom = seqnames(res_sorted), + Start = start(res_sorted) - 1, + End = end(res_sorted), + Name = rep("DiffBind", length(res_sorted)), + Score = rep("0", length(res_sorted)), + Strand = gsub("\\*", ".", strand(res_sorted)) + ) } else if (opt$format == "interval") { - # Output as interval - df <- as.data.frame(res_sorted) - extrainfo <- NULL - for (i in seq_len(nrow(df))) { - extrainfo[i] <- paste0(c(df$width[i], df[i, 6:ncol(df)]), collapse = "|") - } - res_sorted <- data.frame(Chrom = seqnames(res_sorted), - Start = start(res_sorted) - 1, - End = end(res_sorted), - Name = rep("DiffBind", length(res_sorted)), - Score = rep("0", length(res_sorted)), - Strand = gsub("\\*", ".", strand(res_sorted)), - Comment = extrainfo) + # Output as interval + df <- as.data.frame(res_sorted) + extrainfo <- NULL + for (i in seq_len(nrow(df))) { + extrainfo[i] <- paste0(c(df$width[i], df[i, 6:ncol(df)]), collapse = "|") + } + res_sorted <- data.frame( + Chrom = seqnames(res_sorted), + Start = start(res_sorted) - 1, + End = end(res_sorted), + Name = rep("DiffBind", length(res_sorted)), + Score = rep("0", length(res_sorted)), + Strand = gsub("\\*", ".", strand(res_sorted)), + Comment = extrainfo + ) } else { - # Output as 0-based tabular - res_sorted <- data.frame(Chrom = seqnames(res_sorted), - Start = start(res_sorted) - 1, - End = end(res_sorted), - Name = rep("DiffBind", length(res_sorted)), - Score = rep("0", length(res_sorted)), - Strand = gsub("\\*", ".", strand(res_sorted)), - mcols(res_sorted)) + # Output as 0-based tabular + res_sorted <- data.frame( + Chrom = seqnames(res_sorted), + Start = start(res_sorted) - 1, + End = end(res_sorted), + Name = rep("DiffBind", length(res_sorted)), + Score = rep("0", length(res_sorted)), + Strand = gsub("\\*", ".", strand(res_sorted)), + mcols(res_sorted) + ) } write.table(res_sorted, file = opt$outfile, sep = "\t", quote = FALSE, row.names = FALSE) # Output binding affinity scores if (!is.null(opt$bmatrix)) { - bmat <- dba.peakset(sample_count, bRetrieve = TRUE, DataType = DBA_DATA_FRAME) - # Output as 0-based tabular - bmat <- data.frame(Chrom = bmat[, 1], - Start = bmat[, 2] - 1, - End = bmat[, 3], - bmat[, 4:ncol(bmat)]) - write.table(bmat, file = "bmatrix.tab", sep = "\t", quote = FALSE, row.names = FALSE) + bmat <- dba.peakset(sample_count, bRetrieve = TRUE, DataType = DBA_DATA_FRAME) + # Output as 0-based tabular + bmat <- data.frame( + Chrom = bmat[, 1], + Start = bmat[, 2] - 1, + End = bmat[, 3], + bmat[, 4:ncol(bmat)] + ) + write.table(bmat, file = "bmatrix.tab", sep = "\t", quote = FALSE, row.names = FALSE) } # Output RData file if (!is.null(opt$rdaOpt)) { - save.image(file = "DiffBind_analysis.RData") + save.image(file = "DiffBind_analysis.RData") } # Output analysis info if (!is.null(opt$infoOpt)) { - info <- "DiffBind_analysis_info.txt" - cat("dba.count Info\n\n", file = info, append = TRUE) - capture.output(sample, file = info, append = TRUE) - cat("\ndba.analyze Info\n\n", file = info, append = TRUE) - capture.output(sample_analyze, file = info, append = TRUE) - cat("\nSessionInfo\n\n", file = info, append = TRUE) - capture.output(sessionInfo(), file = info, append = TRUE) + info <- "DiffBind_analysis_info.txt" + cat("dba.count Info\n\n", file = info, append = TRUE) + capture.output(sample, file = info, append = TRUE) + cat("\ndba.analyze Info\n\n", file = info, append = TRUE) + capture.output(sample_analyze, file = info, append = TRUE) + cat("\nSessionInfo\n\n", file = info, append = TRUE) + capture.output(sessionInfo(), file = info, append = TRUE) }