# HG changeset patch # User iuc # Date 1479418819 18000 # Node ID ade933eff0076c1e2725ad21173d32bfc9a609b1 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/goseq commit b7dcd020c6a15fa55f392cc09cbc37580d6e75c4 diff -r 000000000000 -r ade933eff007 goseq.r --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/goseq.r Thu Nov 17 16:40:19 2016 -0500 @@ -0,0 +1,121 @@ +options( show.error.messages=F, error = function () { cat( geterrmessage(), file=stderr() ); q( "no", 1, F ) } ) + +# we need that to not crash galaxy with an UTF8 error on German LC settings. +loc <- Sys.setlocale("LC_MESSAGES", "en_US.UTF-8") + +suppressPackageStartupMessages({ + library("goseq") + 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("-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("-cat_file", "--category_file"), default="FALSE", type="character", help = "Path to tabular file with gene_id <-> category mapping."), + make_option(c("-g", "--genome"), default=NULL, type="character", help = "Genome [used for looking up correct gene length]"), + make_option(c("-i", "--gene_id"), default=NULL, type="character", help = "Gene ID format of genes in DGE file"), + make_option(c("-p", "--p_adj_method"), default="BH", type="character", help="Multiple hypothesis testing correction method to use"), + make_option(c("-cat", "--use_genes_without_cat"), default=FALSE, type="logical", + help="A large number of gene may have no GO term annotated. If this option is set to FALSE, genes without category will be ignored in the calculation of p-values(default behaviour). If TRUE these genes will count towards the total number of genes outside the tested category (default behaviour prior to version 1.15.2)."), + make_option(c("-plots", "--make_plots"), default=FALSE, type="logical", help="produce diagnostic plots?") + ) + +parser <- OptionParser(usage = "%prog [options] file", option_list=option_list) +args = parse_args(parser) + +# Vars: +dge_file = args$dge_file +category_file = args$category_file +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$repcnt +p_adj_method = args$p_adj_method +use_genes_without_cat = args$use_genes_without_cat +make_plots = args$make_plots + +# format DE genes into named vector suitable for goseq +dge_table = read.delim(dge_file, header = FALSE, sep="\t") +genes = as.numeric(as.logical(dge_table[,ncol(dge_table)])) # Last column contains TRUE/FALSE +names(genes) = dge_table[,1] # Assuming first column contains gene names + +# gene lengths, assuming last column +if (length_file != "FALSE" ) { + first_line = read.delim(dge_file, header = FALSE, nrow=1) + if (is.numeric(first_line[, ncol(first_line)])) { + length_table = read.delim(length_file, header=FALSE, sep="\t", check.names=FALSE) + } else { + 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),][,ncol(length_table)] + } else { + gene_lengths = getlength(names(genes), genome, gene_id) + } + +# Estimate PWF + +if (make_plots == TRUE) { + pdf(length_bias_plot) +} +pwf=nullp(genes, genome = genome, id = gene_id, bias.data = gene_lengths, plot.fit=make_plots) +graphics.off() + +# Fetch GO annotations if category_file hasn't been supplied: +if (category_file == "FALSE") { + go_map=getgo(genes = names(genes), genome = genome, id = gene_id, fetch.cats=c("GO:CC", "GO:BP", "GO:MF", "KEGG")) + } else { + # check for header: first entry in first column must be present in genes, else it's a header + first_line = read.delim(category_file, header = FALSE, nrow=1) + if (first_line[,1] %in% names(genes)) { + go_map = read.delim(category_file, header = FALSE) + } else { + go_map = read.delim(category_file, header= TRUE) + } +} + +# wallenius approximation of p-values +if (wallenius_tab != "" && wallenius_tab!="None") { + GO.wall=goseq(pwf, genome = genome, id = gene_id, use_genes_without_cat = use_genes_without_cat, gene2cat=go_map) + GO.wall$p.adjust.over_represented = p.adjust(GO.wall$over_represented_pvalue, method=p_adj_method) + GO.wall$p.adjust.under_represented = p.adjust(GO.wall$under_represented_pvalue, method=p_adj_method) + write.table(GO.wall, wallenius_tab, sep="\t", row.names = FALSE, quote = FALSE) +} + +# hypergeometric (no length bias correction) +if (nobias_tab != "" && nobias_tab != "None") { + GO.nobias=goseq(pwf, genome = genome, id = gene_id, method="Hypergeometric", use_genes_without_cat = use_genes_without_cat, gene2cat=go_map) + GO.nobias$p.adjust.over_represented = p.adjust(GO.nobias$over_represented_pvalue, method=p_adj_method) + GO.nobias$p.adjust.under_represented = p.adjust(GO.nobias$under_represented_pvalue, method=p_adj_method) + write.table(GO.nobias, nobias_tab, sep="\t", row.names = FALSE, quote = FALSE) +} + +# Sampling distribution +if (repcnt > 0) { + GO.samp=goseq(pwf, genome = genome, id = gene_id, method="Sampling", repcnt=repcnt, use_genes_without_cat = use_genes_without_cat, gene2cat=go_map) + GO.samp$p.adjust.over_represented = p.adjust(GO.samp$over_represented_pvalue, method=p_adj_method) + GO.samp$p.adjust.under_represented = p.adjust(GO.samp$under_represented_pvalue, method=p_adj_method) + write.table(GO.samp, sampling_tab, sep="\t", row.names = FALSE, quote = FALSE) + # Compare sampling with wallenius + if (make_plots == TRUE) { + 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) + graphics.off() + } +} + +sessionInfo() diff -r 000000000000 -r ade933eff007 goseq.xml --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/goseq.xml Thu Nov 17 16:40:19 2016 -0500 @@ -0,0 +1,140 @@ + + tests for overrepresented gene categories + + r-optparse + bioconductor-goseq + + + + + + + + + + + + +
+ + + +
+ + + + + + + + + + + + + make_plots + methods['hypergeometric'] + + + methods['repcnt'] != 0 + methods['wallenius'] + make_plots + + + methods['hypergeometric'] + + + methods['repcnt'] != 0 + + + methods['wallenius'] + + + + + + + + + + + + + + **What it does** + + Detects Gene Ontology and/or other user defined categories which are over/under-represented in RNA-seq data. + + Options map closely to the excellent manual_ + + + **Input files** + + *DGE list:* + goseq needs a tabular file with genes in the first column, and TRUE or FALSE in the last column. + TRUE means the gene should count as differentially expressed, FALSE means it is not differentially expressed. + You can use the "Compute an expression on every row" tool to create a TRUE / FALSE column for your dataset. + + *Gene length file:* + goseq needs information about the length of a gene to correct for potential length bias in differentially expressed genes + using a prodbability weight function (PWF). + The format of this file is tabular, with gene_id in the first column and length in the second column. + The "get length and gc content" tool can produce such a file. + + *Gene category file:* + You will also need a file describing the membership of genes in categories. The format of this file is gene_id in the first column, + category name in the second column. If you are interested in gene ontology categories you can use the getgo file to retrive + gene ontologies for model organisms, or you can construct your own file. + + **Method options** + + 3 methods, "Wallenius", "Sampling" and "Hypergeometric", can be used to calculate the p-values as follows. + + *"Wallenius"* approximates the true distribution of numbers of members of a category amongst DE genes by the Wallenius non-central hypergeometric distribution. + This distribution assumes that within a category all genes have the same probability of being chosen. + Therefore, this approximation works best when the range in probabilities obtained by the probability weighting function is small. + + *"Sampling"* uses random sampling to approximate the true distribution and uses it to calculate the p-values for over (and under) representation of categories. + Although this is the most accurate method given a high enough value of sampling depth, its use quickly becomes computationally prohibitive. + + *"Hypergeometric"* assumes there is no bias in power to detect differential expression at all and calculates the p-values using a standard hypergeometric distribution. + Useful if you wish to test the effect of selection bias on your results. + + CAUTION: "Hypergeometric" should NEVER be used for producing results for biological interpretation. + If there is genuinely no bias in power to detect DE in your experiment, the PWF will reflect this and the other methods will produce accuracte results. + + .. _manual: https://bioconductor.org/packages/release/bioc/vignettes/goseq/inst/doc/goseq.pdf + + + + + 10.1186/gb-2010-11-2-r14 + + diff -r 000000000000 -r ade933eff007 test-data/category.tab --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/category.tab Thu Nov 17 16:40:19 2016 -0500 @@ -0,0 +1,6 @@ +ENSG00000162526 GO:0000003 +ENSG00000198648 GO:0000278 +ENSG00000112312 GO:0000278 +ENSG00000174442 GO:0000278 +ENSG00000108953 GO:0000278 +ENSG00000167842 GO:0000278 diff -r 000000000000 -r ade933eff007 test-data/dge_list.tab --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/dge_list.tab Thu Nov 17 16:40:19 2016 -0500 @@ -0,0 +1,1000 @@ +ENSG00000140459 False +ENSG00000236824 False +ENSG00000162526 False +ENSG00000090402 True +ENSG00000169188 False +ENSG00000124103 False +ENSG00000241680 False +ENSG00000089009 False +ENSG00000196696 False +ENSG00000006837 False +ENSG00000112312 True +ENSG00000240392 False +ENSG00000010932 False +ENSG00000167685 False +ENSG00000237101 False +ENSG00000244270 False +ENSG00000104331 True +ENSG00000242858 True +ENSG00000148484 False +ENSG00000057608 False +ENSG00000182841 False +ENSG00000230903 False +ENSG00000106868 False +ENSG00000214564 False +ENSG00000169762 False +ENSG00000168758 False +ENSG00000182827 False +ENSG00000125637 True +ENSG00000118873 False +ENSG00000186532 False +ENSG00000106771 False +ENSG00000204348 False +ENSG00000197062 False +ENSG00000171067 False +ENSG00000228118 False 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/dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/length.tab Thu Nov 17 16:40:19 2016 -0500 @@ -0,0 +1,1 @@ +ENSG00000162526 103 diff -r 000000000000 -r ade933eff007 test-data/wal.tab --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/wal.tab Thu Nov 17 16:40:19 2016 -0500 @@ -0,0 +1,3 @@ +category over_represented_pvalue under_represented_pvalue numDEInCat numInCat term ontology p\.adjust.over_represented p\.adjust.under_represented +GO:0000278 0\.0122.+ 0\.999.+ 4 5 mitotic cell cycle BP 0\.0245.+ 0\.999.+ +GO:0000003 1 0\.796.+ 0 1 reproduction BP 1 0\.999.+