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changeset 9:ef2ad746b589 draft

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"planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/goseq commit e230a8db9e090c6e0ea9577863ec6153df79e145"
author iuc
date Sun, 06 Jun 2021 22:47:36 +0000
parents 8b3e3657034e
children 43798b4caee0
files goseq.r goseq.xml test-data/nobias.tab test-data/samp.tab
diffstat 4 files changed, 148 insertions(+), 126 deletions(-) [+]
line wrap: on
line diff
--- a/goseq.r	Fri Sep 06 07:50:46 2019 -0400
+++ b/goseq.r	Sun Jun 06 22:47:36 2021 +0000
@@ -1,170 +1,183 @@
-options( show.error.messages=F, error = function () { cat( geterrmessage(), file=stderr() ); q( "no", 1, F ) } )
+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")
-    library("dplyr")
-    library("ggplot2")
+  library("goseq")
+  library("optparse")
+  library("dplyr")
+  library("ggplot2")
 })
 
 sessionInfo()
 
 option_list <- list(
-    make_option(c("-d", "--dge_file"), type="character", help="Path to file with differential gene expression result"),
-    make_option(c("-lf", "--length_file"), type="character", default=NULL, help="Path to tabular file mapping gene id to length"),
-    make_option(c("-g", "--genome"), type="character", default=NULL, help="Genome [used for looking up correct gene length]"),
-    make_option(c("-i", "--gene_id"), type="character", default=NULL, help="Gene ID format of genes in DGE file"),
-    make_option(c("-fc", "--fetch_cats"), type="character", default=NULL, help="Categories to get can include one or more of GO:CC, GO:BP, GO:MF, KEGG"),
-    make_option(c("-cat_file", "--category_file"), type="character", default=NULL, help="Path to tabular file with gene_id <-> category mapping"),
-    make_option(c("-w","--wallenius_tab"), type="character", default=NULL, help="Path to output file with P-values estimated using wallenius distribution"),
-    make_option(c("-n","--nobias_tab"), type="character", default=NULL, help="Path to output file with P-values estimated using hypergeometric distribution and no correction for gene length bias"),
-    make_option(c("-r", "--repcnt"), type="integer", default=0, help="Number of repeats for sampling"),
-    make_option(c("-s","--sampling_tab"), type="character", default=NULL, help="Path to output file with P-values estimated using sampling distribution"),
-    make_option(c("-p", "--p_adj_method"), type="character", default="BH", help="Multiple hypothesis testing correction method to use"),
-    make_option(c("-cat", "--use_genes_without_cat"), type="logical", default=FALSE, 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("-tp", "--top_plot"), type="character", default=NULL, help="Path to output PDF with top10 over-rep GO terms"),
-    make_option(c("-plots", "--make_plots"), default=FALSE, type="logical", help="Produce diagnostic plots?"),
-    make_option(c("-l","--length_bias_plot"), type="character", default=NULL, help="Path to length-bias plot"),
-    make_option(c("-sw","--sample_vs_wallenius_plot"), type="character", default=NULL, help="Path to plot comparing sampling with wallenius p-values"),
-    make_option(c("-rd", "--rdata"), type="character", default=NULL, help="Path to RData output file"),
-    make_option(c("-g2g", "--categories_genes_out_fp"), type="character", default=NULL, help="Path to file with categories (GO/KEGG terms) and associated DE genes")
-    )
+  make_option("--dge_file", type = "character", help = "Path to file with differential gene expression result"),
+  make_option("--length_file", type = "character", default = NULL, help = "Path to tabular file mapping gene id to length"),
+  make_option("--genome", type = "character", default = NULL, help = "Genome [used for looking up correct gene length]"),
+  make_option("--gene_id", type = "character", default = NULL, help = "Gene ID format of genes in DGE file"),
+  make_option("--fetch_cats", type = "character", default = NULL, help = "Categories to get can include one or more of GO:CC, GO:BP, GO:MF, KEGG"),
+  make_option("--category_file", type = "character", default = NULL, help = "Path to tabular file with gene_id <-> category mapping"),
+  make_option("--wallenius_tab", type = "character", default = NULL, help = "Path to output file with P-values estimated using wallenius distribution"),
+  make_option("--nobias_tab", type = "character", default = NULL, help = "Path to output file with P-values estimated using hypergeometric distribution and no correction for gene length bias"),
+  make_option("--repcnt", type = "integer", default = 0, help = "Number of repeats for sampling"),
+  make_option("--sampling_tab", type = "character", default = NULL, help = "Path to output file with P-values estimated using sampling distribution"),
+  make_option("--p_adj_method", type = "character", default = "BH", help = "Multiple hypothesis testing correction method to use"),
+  make_option("--use_genes_without_cat", type = "logical", default = FALSE, 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("--top_plot", type = "character", default = NULL, help = "Path to output PDF with top10 over-rep GO terms"),
+  make_option("--make_plots", default = FALSE, type = "logical", help = "Produce diagnostic plots?"),
+  make_option("--length_bias_plot", type = "character", default = NULL, help = "Path to length-bias plot"),
+  make_option("--sample_vs_wallenius_plot", type = "character", default = NULL, help = "Path to plot comparing sampling with wallenius p-values"),
+  make_option("--rdata", type = "character", default = NULL, help = "Path to RData output file"),
+  make_option("--categories_genes_out_fp", type = "character", default = NULL, help = "Path to file with categories (GO/KEGG terms) and associated DE genes")
+)
 
-parser <- OptionParser(usage = "%prog [options] file", option_list=option_list)
-args = parse_args(parser)
+parser <- OptionParser(usage = "%prog [options] file", option_list = option_list)
+args <- parse_args(parser)
 
 if (!is.null(args$fetch_cats)) {
-  fetch_cats = unlist(strsplit(args$fetch_cats, ","))
+  fetch_cats <- unlist(strsplit(args$fetch_cats, ","))
 } else {
-  fetch_cats = "Custom"
+  fetch_cats <- "Custom"
 }
 
 # format DE genes into named vector suitable for goseq
 # check if header is present
-first_line = read.delim(args$dge_file, header=FALSE, nrow=1)
-second_col = toupper(first_line[, ncol(first_line)])
+first_line <- read.delim(args$dge_file, header = FALSE, nrow = 1)
+second_col <- toupper(first_line[, ncol(first_line)])
 if (second_col == TRUE || second_col == FALSE) {
-  dge_table = read.delim(args$dge_file, header=FALSE, sep="\t")
+  dge_table <- read.delim(args$dge_file, header = FALSE, sep = "\t")
 } else {
-  dge_table = read.delim(args$dge_file, header=TRUE, sep="\t")
+  dge_table <- read.delim(args$dge_file, header = TRUE, 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
+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
-first_line = read.delim(args$length_file, header=FALSE, nrow=1)
+first_line <- read.delim(args$length_file, header = FALSE, nrow = 1)
 if (is.numeric(first_line[, ncol(first_line)])) {
-  length_table = read.delim(args$length_file, header=FALSE, sep="\t", check.names=FALSE)
+  length_table <- read.delim(args$length_file, header = FALSE, sep = "\t", check.names = FALSE)
 } else {
-  length_table = read.delim(args$length_file, header=TRUE, sep="\t", check.names=FALSE)
+  length_table <- read.delim(args$length_file, header = TRUE, sep = "\t", check.names = FALSE)
 }
-row.names(length_table) = length_table[,1]
+row.names(length_table) <- length_table[, 1]
 # get vector of gene length in same order as the genes
-gene_lengths = length_table[names(genes),][, ncol(length_table)]
+gene_lengths <- length_table[names(genes), ][, ncol(length_table)]
 
 # Estimate PWF
 if (args$make_plots) {
   pdf(args$length_bias_plot)
 }
-pwf=nullp(genes, genome=args$genome, id=args$gene_id, bias.data=gene_lengths, plot.fit=args$make_plots)
+pwf <- nullp(genes, genome = args$genome, id = args$gene_id, bias.data = gene_lengths, plot.fit = args$make_plots)
 if (args$make_plots) {
   dev.off()
 }
 
 # Fetch GO annotations if category_file hasn't been supplied:
 if (is.null(args$category_file)) {
-  go_map=getgo(genes=names(genes), genome=args$genome, id=args$gene_id, fetch.cats=fetch_cats)
+  go_map <- getgo(genes = names(genes), genome = args$genome, id = args$gene_id, fetch.cats = fetch_cats)
 } else {
   # check for header: first entry in first column must be present in genes, else it's a header
-  first_line = read.delim(args$category_file, header=FALSE, nrow=1)
-  if (first_line[,1] %in% names(genes)) {
-    go_map = read.delim(args$category_file, header=FALSE)
+  first_line <- read.delim(args$category_file, header = FALSE, nrow = 1)
+  if (first_line[, 1] %in% names(genes)) {
+    go_map <- read.delim(args$category_file, header = FALSE)
   } else {
-    go_map = read.delim(args$category_file, header=TRUE)
+    go_map <- read.delim(args$category_file, header = TRUE)
   }
 }
 
 results <- list()
 
-runGoseq <- function(pwf, genome, gene_id, goseq_method, use_genes_without_cat, repcnt, gene2cat, p_adj_method, out_fp){
-  out=goseq(pwf, genome=genome, id=gene_id, method=goseq_method, use_genes_without_cat=use_genes_without_cat, gene2cat=go_map)
-  out$p.adjust.over_represented = p.adjust(out$over_represented_pvalue, method=p_adj_method)
-  out$p.adjust.under_represented = p.adjust(out$under_represented_pvalue, method=p_adj_method)
-  write.table(out, out_fp, sep="\t", row.names=FALSE, quote=FALSE)
+run_goseq <- function(pwf, genome, gene_id, goseq_method, use_genes_without_cat, repcnt, gene2cat, p_adj_method, out_fp) {
+  out <- goseq(pwf, genome = genome, id = gene_id, method = goseq_method, use_genes_without_cat = use_genes_without_cat, gene2cat = go_map)
+  out$p_adjust_over_represented <- p.adjust(out$over_represented_pvalue, method = p_adj_method)
+  out$p_adjust_under_represented <- p.adjust(out$under_represented_pvalue, method = p_adj_method)
+  write.table(out, out_fp, sep = "\t", row.names = FALSE, quote = FALSE)
   return(out)
 }
 
 # wallenius approximation of p-values
-if (!is.null(args$wallenius_tab)) results[['Wallenius']] <- runGoseq(
-  pwf,
-  genome=args$genome,
-  gene_id=args$gene_id,
-  goseq_method="Wallenius",
-  use_genes_without_cat=args$use_genes_without_cat,
-  repcnt=args$repcnt,
-  gene2cat=go_map,
-  p_adj_method=args$p_adj_method,
-  out_fp=args$wallenius_tab)
+if (!is.null(args$wallenius_tab)) {
+  results[["Wallenius"]] <- run_goseq(
+    pwf,
+    genome = args$genome,
+    gene_id = args$gene_id,
+    goseq_method = "Wallenius",
+    use_genes_without_cat = args$use_genes_without_cat,
+    repcnt = args$repcnt,
+    gene2cat = go_map,
+    p_adj_method = args$p_adj_method,
+    out_fp = args$wallenius_tab
+  )
+}
 
 
 # hypergeometric (no length bias correction)
-if (!is.null(args$nobias_tab)) results[['Hypergeometric']] <- runGoseq(
-  pwf,
-  genome=args$genome,
-  gene_id=args$gene_id,
-  goseq_method="Hypergeometric",
-  use_genes_without_cat=args$use_genes_without_cat,
-  repcnt=args$repcnt,
-  gene2cat=go_map,
-  p_adj_method=args$p_adj_method,
-  out_fp=args$nobias_tab)
+if (!is.null(args$nobias_tab)) {
+  results[["Hypergeometric"]] <- run_goseq(
+    pwf,
+    genome = args$genome,
+    gene_id = args$gene_id,
+    goseq_method = "Hypergeometric",
+    use_genes_without_cat = args$use_genes_without_cat,
+    repcnt = args$repcnt,
+    gene2cat = go_map,
+    p_adj_method = args$p_adj_method,
+    out_fp = args$nobias_tab
+  )
+}
 
 # Sampling distribution
-if (args$repcnt > 0){
-  results[['Sampling']] <- runGoseq(
+if (args$repcnt > 0) {
+  results[["Sampling"]] <- run_goseq(
     pwf,
-    genome=args$genome,
-    gene_id=args$gene_id,
-    goseq_method="Sampling",
-    use_genes_without_cat=args$use_genes_without_cat,
-    repcnt=args$repcnt,
-    gene2cat=go_map,
-    p_adj_method=args$p_adj_method,
-    out_fp=args$sampling_tab)
+    genome = args$genome,
+    gene_id = args$gene_id,
+    goseq_method = "Sampling",
+    use_genes_without_cat = args$use_genes_without_cat,
+    repcnt = args$repcnt,
+    gene2cat = go_map,
+    p_adj_method = args$p_adj_method,
+    out_fp = args$sampling_tab
+  )
 
   # Compare sampling with wallenius
   if (args$make_plots & !is.null(args$wallenius_tab)) {
     pdf(args$sample_vs_wallenius_plot)
-    plot(log10(results[['Wallenius']][,2]), 
-      log10(results[['Sampling']][match(results[['Sampling']][,1], results[['Wallenius']][,1]), 2]),
-      xlab="log10(Wallenius p-values)",
-      ylab="log10(Sampling p-values)",
-      xlim=c(-3,0))
-    abline(0,1,col=3,lty=2)
+    plot(log10(results[["Wallenius"]][, 2]),
+      log10(results[["Sampling"]][match(results[["Sampling"]][, 1], results[["Wallenius"]][, 1]), 2]),
+      xlab = "log10(Wallenius p-values)",
+      ylab = "log10(Sampling p-values)",
+      xlim = c(-3, 0)
+    )
+    abline(0, 1, col = 3, lty = 2)
     dev.off()
   }
 }
 
 # Plot the top 10
 if (!is.null(args$top_plot)) {
-  cats_title <- gsub("GO:","", args$fetch_cats)
+  cats_title <- gsub("GO:", "", args$fetch_cats)
   # modified from https://bioinformatics-core-shared-training.github.io/cruk-summer-school-2018/RNASeq2018/html/06_Gene_set_testing.nb.html
   pdf(args$top_plot)
   for (m in names(results)) {
     p <- results[[m]] %>%
-      top_n(10, wt=-over_represented_pvalue)  %>%
-      mutate(hitsPerc=numDEInCat*100/numInCat) %>%
-      ggplot(aes(x=hitsPerc,
-                   y=reorder(substr(term, 1, 40), -over_represented_pvalue), # only use 1st 40 chars of terms otherwise squashes plot
-                   colour=p.adjust.over_represented,
-                   size=numDEInCat)) +
+      top_n(10, wt = -over_represented_pvalue) %>%
+      mutate(hitsPerc = numDEInCat * 100 / numInCat) %>%
+      ggplot(aes(
+        x = hitsPerc,
+        y = reorder(substr(term, 1, 40), -over_represented_pvalue), # only use 1st 40 chars of terms otherwise squashes plot
+        colour = p_adjust_over_represented,
+        size = numDEInCat
+      )) +
       geom_point() +
-      expand_limits(x=0) +
-      labs(x="% DE in category", y="Category", colour="Adj P value", size="Count", title=paste("Top over-represented categories in", cats_title), subtitle=paste(m, " method")) +
-      theme(plot.title=element_text(hjust = 0.5), plot.subtitle=element_text(hjust = 0.5))
+      expand_limits(x = 0) +
+      labs(x = "% DE in category", y = "Category", colour = "Adj P value", size = "Count", title = paste("Top over-represented categories in", cats_title), subtitle = paste(m, " method")) +
+      theme(plot.title = element_text(hjust = 0.5), plot.subtitle = element_text(hjust = 0.5))
     print(p)
   }
   dev.off()
@@ -172,27 +185,27 @@
 
 # Extract the genes to the categories (GO/KEGG terms)
 if (!is.null(args$categories_genes_out_fp)) {
-  cat2gene = split(rep(names(go_map), sapply(go_map, length)), unlist(go_map, use.names = FALSE))
+  cat2gene <- split(rep(names(go_map), sapply(go_map, length)), unlist(go_map, use.names = FALSE))
   # extract categories (GO/KEGG terms) for all results
-  categories = c()
+  categories <- c()
   for (m in names(results)) {
-    categories = c(categories, results[[m]]$category)
+    categories <- c(categories, results[[m]]$category)
   }
-  categories = unique(categories)
+  categories <- unique(categories)
   # extract the DE genes for each catge term
-  categories_genes = data.frame(Categories=categories, DEgenes=rep('', length(categories)))
-  categories_genes$DEgenes = as.character(categories_genes$DEgenes)
-  rownames(categories_genes) = categories
-  for (cat in categories){
-    tmp = pwf[cat2gene[[cat]],]
-    tmp = rownames(tmp[tmp$DEgenes > 0, ])
-    categories_genes[cat, 'DEgenes'] = paste(tmp, collapse=',')
+  categories_genes <- data.frame(category = categories, de_genes = rep("", length(categories)))
+  categories_genes$de_genes <- as.character(categories_genes$de_genes)
+  rownames(categories_genes) <- categories
+  for (cat in categories) {
+    tmp <- pwf[cat2gene[[cat]], ]
+    tmp <- rownames(tmp[tmp$DEgenes > 0, ])
+    categories_genes[cat, "de_genes"] <- paste(tmp, collapse = ",")
   }
   # output
-  write.table(categories_genes, args$categories_genes_out_fp, sep = "\t", row.names=FALSE, quote=FALSE)
+  write.table(categories_genes, args$categories_genes_out_fp, sep = "\t", row.names = FALSE, quote = FALSE)
 }
 
 # Output RData file
 if (!is.null(args$rdata)) {
-  save.image(file=args$rdata)
+  save.image(file = args$rdata)
 }
--- a/goseq.xml	Fri Sep 06 07:50:46 2019 -0400
+++ b/goseq.xml	Sun Jun 06 22:47:36 2021 +0000
@@ -1,18 +1,27 @@
 <tool id="goseq" name="goseq" version="@VERSION@+@GALAXY_VERSION@">
     <description>tests for overrepresented gene categories</description>
+    <xrefs>
+        <xref type="bio.tools">goseq</xref>
+    </xrefs>
+    <edam_topics>
+        <edam_topic>topic_3308</edam_topic>
+    </edam_topics>
+    <edam_operations>
+        <edam_operation>operation_2436</edam_operation>
+    </edam_operations>
     <macros>
-        <token name="@VERSION@">1.36.0</token>
+        <token name="@VERSION@">1.44.0</token>
         <token name="@GALAXY_VERSION@">galaxy0</token>
     </macros>
     <requirements>
         <requirement type="package" version="@VERSION@">bioconductor-goseq</requirement>
-        <requirement type="package" version="3.8.2">bioconductor-org.hs.eg.db</requirement>
-        <requirement type="package" version="3.8.2">bioconductor-org.dm.eg.db</requirement>
-        <requirement type="package" version="3.8.2">bioconductor-org.dr.eg.db</requirement>
-        <requirement type="package" version="3.8.2">bioconductor-org.mm.eg.db</requirement>
-        <requirement type="package" version="0.8.3">r-dplyr</requirement>
-        <requirement type="package" version="3.2.1">r-ggplot2</requirement>
-        <requirement type="package" version="1.6.2">r-optparse</requirement>
+        <requirement type="package" version="3.13.0">bioconductor-org.hs.eg.db</requirement>
+        <requirement type="package" version="3.13.0">bioconductor-org.dm.eg.db</requirement>
+        <requirement type="package" version="3.13.0">bioconductor-org.dr.eg.db</requirement>
+        <requirement type="package" version="3.13.0">bioconductor-org.mm.eg.db</requirement>
+        <requirement type="package" version="1.0.6">r-dplyr</requirement>
+        <requirement type="package" version="3.3.3">r-ggplot2</requirement>
+        <requirement type="package" version="1.6.6">r-optparse</requirement>
     </requirements>
     <stdio>
         <regex match="Execution halted"
@@ -194,7 +203,7 @@
             <output name="top_plot" ftype="pdf" file="topgo.pdf" compare="sim_size"/>
             <output name="wallenius_tab">
                 <assert_contents>
-                    <has_text_matching expression="category.*over_represented_pvalue.*under_represented_pvalue.*numDEInCat.*numInCat.*term.*ontology.*p.adjust.over_represented.*p.adjust.under_represented" />
+                    <has_text_matching expression="category.*over_represented_pvalue.*under_represented_pvalue.*numDEInCat.*numInCat.*term.*ontology.*p_adjust_over_represented.*p_adjust_under_represented" />
                     <has_text_matching expression="GO:0000278.*0.01" />
                 </assert_contents>
             </output>
@@ -226,13 +235,13 @@
             </section>
             <output name="wallenius_tab">
                 <assert_contents>
-                    <has_text_matching expression="category.*over_represented_pvalue.*under_represented_pvalue.*numDEInCat.*numInCat.*term.*ontology.*p.adjust.over_represented.*p.adjust.under_represented" />
-                    <has_text_matching expression="GO:0005576.*9.0" />
+                    <has_text_matching expression="category.*over_represented_pvalue.*under_represented_pvalue.*numDEInCat.*numInCat.*term.*ontology.*p_adjust_over_represented.*p_adjust_under_represented" />
+                    <has_text_matching expression="GO:0005576.*0.9" />
                 </assert_contents>
             </output>
             <output name="cat_genes_tab">
                 <assert_contents>
-                    <has_text_matching expression="Categories.*DEgenes" />
+                    <has_text_matching expression="category.*de_genes" />
                     <has_text_matching expression="GO:0005615.*ENSG00000090402,ENSG00000108953,ENSG00000070961" />
                 </assert_contents>
             </output>
@@ -264,8 +273,8 @@
             </section>
             <output name="wallenius_tab">
                 <assert_contents>
-                    <has_text_matching expression="category.*over_represented_pvalue.*under_represented_pvalue.*numDEInCat.*numInCat.*term.*ontology.*p.adjust.over_represented.*p.adjust.under_represented" />
-                    <has_text_matching expression="GO:0016569.*0.8" />
+                    <has_text_matching expression="category.*over_represented_pvalue.*under_represented_pvalue.*numDEInCat.*numInCat.*term.*ontology.*p_adjust_over_represented.*p_adjust_under_represented" />
+                    <has_text_matching expression="GO:0016569.*0.90" />
                 </assert_contents>
             </output>
         </test>
@@ -438,7 +447,7 @@
 Example:
 
 =========== =============== ================ ============ ========== ======================================== ========== =================== ====================
-*category*  *over_rep_pval* *under_rep_pval* *numDEInCat* *numInCat* *term*                                   *ontology* *p.adjust.over_rep* *p.adjust.under_rep*
+*category*  *over_rep_pval* *under_rep_pval* *numDEInCat* *numInCat* *term*                                   *ontology* *p_adjust_over_rep* *p_adjust_under_rep*
 ----------- --------------- ---------------- ------------ ---------- ---------------------------------------- ---------- ------------------- --------------------
 GO\:0005576  0.000054        0.999975         56           142       extracellular region                     CC         0.394825             1
 GO\:0005840  0.000143        0.999988         9            12        ribosome                                 CC         0.394825             1
--- a/test-data/nobias.tab	Fri Sep 06 07:50:46 2019 -0400
+++ b/test-data/nobias.tab	Sun Jun 06 22:47:36 2021 +0000
@@ -1,3 +1,3 @@
-category	over_represented_pvalue	under_represented_pvalue	numDEInCat	numInCat	term	ontology	p.adjust.over_represented	p.adjust.under_represented
+category	over_represented_pvalue	under_represented_pvalue	numDEInCat	numInCat	term	ontology	p_adjust_over_represented	p_adjust_under_represented
 GO:0000278	0.0129827306163772	0.999244816412166	4	5	mitotic cell cycle	BP	0.0259654612327543	0.999244816412166
 GO:0000003	1	0.761	0	1	reproduction	BP	1	0.999244816412166
--- a/test-data/samp.tab	Fri Sep 06 07:50:46 2019 -0400
+++ b/test-data/samp.tab	Sun Jun 06 22:47:36 2021 +0000
@@ -1,3 +1,3 @@
-category	over_represented_pvalue	under_represented_pvalue	numDEInCat	numInCat	term	ontology	p.adjust.over_represented	p.adjust.under_represented
+category	over_represented_pvalue	under_represented_pvalue	numDEInCat	numInCat	term	ontology	p_adjust_over_represented	p_adjust_under_represented
 GO:0000278	0.016983016983017	1	4	5	mitotic cell cycle	BP	0.033966033966034	1
 GO:0000003	1	0.802197802197802	0	1	reproduction	BP	1	1