Mercurial > repos > mvdbeek > r_goseq_1_22_0
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planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/goseq_1_22_0 commit fdd0811efc61c31f88ff17096fbe8ee8cfacd766-dirty
author | mvdbeek |
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date | Fri, 26 Feb 2016 13:26:56 -0500 |
parents | 5fb82111ec62 |
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sink(stdout(), type = "message") suppressWarnings(suppressMessages(library(goseq))) suppressWarnings(suppressMessages(library(optparse))) option_list <- list( make_option(c("-d", "--dge_file"), type="character", help="Path to file with differential gene expression result"), make_option(c("-w","--wallenius_tab"), type="character", help="Path to output file with P-values estimated using wallenius distribution."), make_option(c("-s","--sampling_tab"), type="character", default=FALSE, help="Path to output file with P-values estimated using wallenius distribution."), make_option(c("-n","--nobias_tab"), type="character", default=FALSE, help="Path to output file with P-values estimated using wallenius distribution and no correction for gene length bias."), make_option(c("-l","--length_bias_plot"), type="character", default=FALSE, help="Path to length-bias plot."), make_option(c("-sw","--sample_vs_wallenius_plot"), type="character", default=FALSE, help="Path to plot comparing sampling with wallenius p-values."), make_option(c("-padj", "--p_adj_column"), type="integer",help="Column that contains p. adjust values"), make_option(c("-c", "--cutoff"), type="double",dest="p_adj_cutoff", help="Genes with p.adjust below cutoff are considered not differentially expressed and serve as control genes"), make_option(c("-r", "--repcnt"), type="integer", default=100, help="Number of repeats for sampling"), make_option(c("-lf", "--length_file"), type="character", default="FALSE", help = "Path to tabular file mapping gene id to length"), make_option(c("-g", "--genome"), type="character", help = "Genome [used for looking up correct gene length]"), make_option(c("-i", "--gene_id"), type="character", help="Gene ID of gene column in DGE file") ) parser <- OptionParser(usage = "%prog [options] file", option_list=option_list) args = parse_args(parser) # Vars: dge_file = args$dge_file p_adj_column = args$p_adj_colum p_adj_cutoff = args$p_adj_cutoff length_file = args$length_file genome = args$genome gene_id = args$gene_id wallenius_tab = args$wallenius_tab sampling_tab = args$sampling_tab nobias_tab = args$nobias_tab length_bias_plot = args$length_bias_plot sample_vs_wallenius_plot = args$sample_vs_wallenius_plot repcnt = args$repcnt # format DE genes into vector suitable for use with goseq dge_table = read.delim(dge_file, header = TRUE, sep="\t", check.names = FALSE) genes = as.integer(dge_table[,p_adj_column]<p_adj_cutoff) names(genes) = dge_table[,1] # Assuming first row contains gene names # Get gene lengths if (length_file != "FALSE" ) { length_table = read.delim(length_file, header=TRUE, sep="\t", check.names=FALSE) row.names(length_table) = length_table[,1] gene_lengths = length_table[names(genes),]$length } else { gene_lengths = getlength(names(genes), genome, gene_id) } # Estimate PWF pdf(length_bias_plot) pwf=nullp(genes, genome, gene_id, gene_lengths) message = dev.off() # wallenius approximation of p-values GO.wall=goseq(pwf, genome, gene_id) GO.nobias=goseq(pwf, genome, gene_id, method="Hypergeometric") # Sampling distribution if (repcnt > 0) { GO.samp=goseq(pwf,genome, gene_id, method="Sampling", repcnt=repcnt) # Compare sampling with wallenius pdf(sample_vs_wallenius_plot) plot(log10(GO.wall[,2]), log10(GO.samp[match(GO.samp[,1],GO.wall[,1]),2]), xlab="log10(Wallenius p-values)",ylab="log10(Sampling p-values)", xlim=c(-3,0)) abline(0,1,col=3,lty=2) message = dev.off() write.table(GO.samp, sampling_tab, sep="\t", row.names = FALSE, quote = FALSE) } write.table(GO.wall, wallenius_tab, sep="\t", row.names = FALSE, quote = FALSE) write.table(GO.nobias, nobias_tab, sep="\t", row.names = FALSE, quote = FALSE) sessionInfo() # Use the following to get a list of supported genomes / gene ids # write.table(supportedGenomes(), "available_genomes.tab", row.names = FALSE, quote=FALSE) # write.table(supportedGeneIDs(), "supported_gene_ids.tab", row.name = FALSE, quote = FALSE) # write.table(table.summary, "input_gene_count_matrix.tab", row.names = FALSE, quote = FALSE)