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changeset 2:ab492df30cdf draft

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planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/goseq commit 4a3c9f195ba5d899b1a1ce5e80281cdf230f456a
author iuc
date Mon, 23 Oct 2017 11:19:12 -0400
parents 9d1256d9ef0b
children 783e8b70b047
files goseq.r goseq.xml test-data/dge_list_zf.tab test-data/gc.tab test-data/gene_length_zf.tab test-data/getgo.danRer10.tab test-data/getgo.hg38.tab test-data/go_terms.tab test-data/goseq_analysis.RData test-data/length.tab test-data/length_bias_plot.pdf test-data/nobias.tab test-data/samp.tab test-data/sample_vs_wallenius_plot.pdf test-data/wal.tab
diffstat 15 files changed, 1625 insertions(+), 180 deletions(-) [+]
line wrap: on
line diff
--- a/goseq.r	Sun Jun 11 08:57:39 2017 -0400
+++ b/goseq.r	Mon Oct 23 11:19:12 2017 -0400
@@ -11,8 +11,8 @@
 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("-s","--sampling_tab"), type="character", default=FALSE, help="Path to output file with P-values estimated using sampling distribution."),
+    make_option(c("-n","--nobias_tab"), type="character", default=FALSE, help="Path to output file with P-values estimated using hypergeometric 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"),
@@ -23,7 +23,9 @@
     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?")
+    make_option(c("-plots", "--make_plots"), default=FALSE, type="logical", help="produce diagnostic plots?"),
+    make_option(c("-fc", "--fetch_cats"), default=NULL, type="character", help="Categories to get can include one or more of GO:CC, GO:BP, GO:MF, KEGG"),
+    make_option(c("-rd", "--rdata"), default=NULL, type="character", help="Path to RData output file.")
     )
 
 parser <- OptionParser(usage = "%prog [options] file", option_list=option_list)
@@ -44,15 +46,27 @@
 p_adj_method = args$p_adj_method
 use_genes_without_cat = args$use_genes_without_cat
 make_plots = args$make_plots
+rdata = args$rdata
+
+if (!is.null(args$fetch_cats)) {
+  fetch_cats = unlist(strsplit(args$fetch_cats, ","))
+}
 
 # format DE genes into named vector suitable for goseq
-dge_table = read.delim(dge_file, header = FALSE, sep="\t")
+# check if header is present
+first_line = read.delim(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(dge_file, header = FALSE, sep="\t")
+} else {
+    dge_table = read.delim(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
 
 # gene lengths, assuming last column
 if (length_file != "FALSE" ) {
-  first_line = read.delim(dge_file, header = FALSE, nrow=1)
+  first_line = read.delim(length_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 {
@@ -66,7 +80,7 @@
 
 # Estimate PWF
 
-if (make_plots == TRUE) {
+if (make_plots != 'false') {
   pdf(length_bias_plot)
 }
 pwf=nullp(genes, genome = genome, id = gene_id, bias.data = gene_lengths, plot.fit=make_plots)
@@ -74,7 +88,7 @@
 
 # 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"))
+  go_map=getgo(genes = names(genes), genome=genome, id=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(category_file, header = FALSE, nrow=1)
@@ -103,7 +117,13 @@
 
 # Sampling distribution
 if (repcnt > 0) {
+
+  # capture the sampling progress so it doesn't fill stdout  
+  zz <- file("/dev/null", open = "wt")
+  sink(zz)
   GO.samp=goseq(pwf, genome = genome, id = gene_id, method="Sampling", repcnt=repcnt, use_genes_without_cat = use_genes_without_cat, gene2cat=go_map)
+  sink()
+  
   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)
@@ -118,4 +138,10 @@
   }
 }
 
+# Output RData file
+if (!is.null(args$rdata)) {
+  save.image(file = "goseq_analysis.RData")
+}
+
+
 sessionInfo()
--- a/goseq.xml	Sun Jun 11 08:57:39 2017 -0400
+++ b/goseq.xml	Mon Oct 23 11:19:12 2017 -0400
@@ -1,8 +1,12 @@
-<tool id="goseq" name="goseq" version="0.2.2">
+<tool id="goseq" name="goseq" version="1.26.0">
     <description>tests for overrepresented gene categories</description>
     <requirements>
         <requirement type="package" version="1.3.2">r-optparse</requirement>
-        <requirement type="package" version="1.22.0">bioconductor-goseq</requirement>
+        <requirement type="package" version="1.26.0">bioconductor-goseq</requirement>
+        <requirement type="package" version="3.3.0">bioconductor-org.hs.eg.db</requirement>
+        <requirement type="package" version="3.4.0">bioconductor-org.dm.eg.db</requirement>
+        <requirement type="package" version="3.4.1">bioconductor-org.dr.eg.db</requirement>
+        <requirement type="package" version="3.4.0">bioconductor-org.mm.eg.db</requirement>
     </requirements>
     <stdio>
         <regex match="Execution halted"
@@ -18,122 +22,334 @@
                level="fatal"
                description="An undefined error occured, please check your input carefully and contact your administrator." />
     </stdio>
+    <version_command><![CDATA[
+echo $(R --version | grep version | grep -v GNU)", goseq version" $(R --vanilla --slave -e "library(goseq); cat(sessionInfo()\$otherPkgs\$goseq\$Version)" 2> /dev/null | grep -v -i "WARNING: ")", optparse version" $(R --vanilla --slave -e "library(optparse); cat(sessionInfo()\$otherPkgs\$optparse\$Version)" 2> /dev/null | grep -v -i "WARNING: ")", org.Hs.eg.db version" $(R --vanilla --slave -e "library(org.Hs.eg.db); cat(sessionInfo()\$otherPkgs\$org.Hs.eg.db\$Version)" 2> /dev/null | grep -v -i "WARNING: ")", org.Dr.eg.db version" $(R --vanilla --slave -e "library(org.Dr.eg.db); cat(sessionInfo()\$otherPkgs\$org.Dr.eg.db\$Version)" 2> /dev/null | grep -v -i "WARNING: ")", org.Dm.eg.db version" $(R --vanilla --slave -e "library(org.Dm.eg.db); cat(sessionInfo()\$otherPkgs\$org.Dm.eg.db\$Version)" 2> /dev/null | grep -v -i "WARNING: ")", org.Mm.eg.db version" $(R --vanilla --slave -e "library(org.Mm.eg.db); cat(sessionInfo()\$otherPkgs\$org.Mm.eg.db\$Version)" 2> /dev/null | grep -v -i "WARNING: ")
+    ]]></version_command>
     <command><![CDATA[
-        Rscript '$__tool_directory__'/goseq.r --dge_file '$dge_file'
-        --length_file '$length_file'
-        --category_file '$category_file'
-        #if $methods['wallenius']:
-        --wallenius_tab '$wallenius_tab'
-        #end if
-        #if $methods['hypergeometric']:
-        --nobias_tab '$nobias_tab'
-        #end if
-        --repcnt '$methods.repcnt'
-        --sampling_tab '$sampling_tab'
-        --p_adj_method '$p_adj_method'
-        --use_genes_without_cat '$use_genes_without_cat'
-        --make_plots '$make_plots'
-        --length_bias_plot '$length_bias_plot'
-        --sample_vs_wallenius_plot '$sample_vs_wallenius_plot'
+Rscript '$__tool_directory__/goseq.r'
+
+--dge_file '$dge_file'
+--length_file '$length_file'
+
+#if $categorySource.catSource == 'getgo':
+    --genome $categorySource.genome
+    --gene_id $categorySource.gene_id
+    --fetch_cats '$categorySource.fetchcats'
+#elif $categorySource.catSource == 'history':
+    --category_file '$categorySource.category_file'
+#end if
+
+#if $methods['wallenius']:
+    --wallenius_tab '$wallenius_tab'
+#end if
+#if $methods['hypergeometric']:
+    --nobias_tab '$nobias_tab'
+#end if
+--repcnt '$methods.repcnt'
+--sampling_tab '$sampling_tab'
+
+--make_plots '$out.make_plots'
+--length_bias_plot '$length_bias_plot'
+--sample_vs_wallenius_plot '$sample_vs_wallenius_plot'
+--rdata '$out.rdata_out'
+
+--p_adj_method '$adv.p_adj_method'
+--use_genes_without_cat '$adv.use_genes_without_cat'
+
     ]]></command>
+
+    <!-- Input Files-->
     <inputs>
-        <param name="dge_file" help="A tabular file with gene names in the first column, and TRUE or FALSE in the last column. TRUE means a gene is differentially expressed. See help section for details." label="Differentially expressed gene file" type="data" format="tabular" />
-        <param name="length_file" label="Gene length file for length bias correction" help="You can calculate the gene length using the get length and gc content tool" type="data" format="tabular" />
-        <param name="category_file" label="Gene category file" help="You can obtain a mapping of gene id to gene ontology using the getgo tool" type="data" format="tabular" />
-        <param name="use_genes_without_cat" help="For example, a large number of gene may have no GO term annotated. If this option is set to FALSE, those genes will be ignored in the calculation of p-values. If this option is set to TRUE, then these genes will count towards the total number of genes outside the category being tested"
-               label="Count genes without any category?" type="boolean"/>
-        <section name="methods" title="Method options" expanded="True">
-            <param name="wallenius" type="boolean" checked="true" label="Use wallenius method" help="See help for details" />
-            <param name="hypergeometric" type="boolean" checked="false" label="Use hypergeometric method" help="Does not use gene length information. See help for details" />
-            <param name="repcnt" help="Draw this many random control gene sets. Set to 0 to not do sampling. Larger values take a long time" label="sampling depth" size="3" type="integer" min="0" max="10000" value="0" />
+        <param name="dge_file" type="data" format="tabular" label="Differentially expressed genes file" help="A tabular file with Gene IDs in the first column, and True or False in the second column. True means a gene is differentially expressed. See Help section for details."/>
+        <param name="length_file" type="data" format="tabular" label="Gene lengths file" help="You can calculate the gene lengths using featureCounts or the Gene length and GC content tool."/>
+        <conditional name="categorySource">
+            <param name="catSource" type="select" format="tabular" label="Gene categories" help="You can obtain a mapping of genes to categories (for some genomes only) or you can provide your own category file.">
+                <option value="getgo" selected="true">Get categories</option>
+                <option value="history">Use a category file from history</option>
+            </param>
+            <when value="getgo">
+                <param name="genome" type="select" label="Select a genome to use">
+                    <option value="hg38">Human (hg38)</option>
+                    <option value="mm10">Mouse (mm10)</option>
+                    <option value="dm6">Fruit fly (dm6)</option>
+                    <option value="danRer10">Zebrafish (danRer10)</option>
+                </param>
+                <param name="gene_id" type="select" label="Select Gene ID format" help="Supported Gene IDs to automatically fetch categories should either be Entrez, Ensembl, or gene symbols.">
+                    <option value="ensGene">Ensembl Gene ID</option>
+                    <option value="knownGene">Entrez Gene ID</option>
+                    <option value="geneSymbol">Gene Symbol</option>
+                </param>
+                <param name="fetchcats" type="select" multiple="True" display="checkboxes" label="Select one or more categories" help="By default, goseq tests all three major Gene Ontology branches; Cellular Component, Biological Process and Molecular Function. However, it is possible to limit testing to any combination and/or to also use KEGG pathways.">
+                    <option value="GO:CC" selected="True">GO: Cellular Component</option>
+                    <option value="GO:BP" selected="True">GO: Biological Process</option>
+                    <option value="GO:MF" selected="True">GO: Molecular Function</option>
+                    <option value="KEGG">KEGG</option>
+                </param>
+            </when>
+            <when value="history">
+                <param name="category_file" type="data" format="tabular" label="Gene category file"/>
+            </when>
+        </conditional>
+
+        <!-- Method Options -->
+        <section name="methods" title="Method Options">
+            <param name="wallenius" type="boolean" checked="true" label="Use Wallenius method" help="See help for details. Default: Yes" />
+            <param name="hypergeometric" type="boolean" checked="false" label="Use Hypergeometric method" help="Does not use gene length information. See help for details. Default: No" />
+            <param name="repcnt" type="integer" size="3" min="0" max="10000" value="0" label="Sampling number" help="Number of random samples to be calculated when sampling is used. Set to 0 to not do sampling. Larger values take a long time. Default: 0" />
         </section>
-        <param name="p_adj_method" type="select" label="Select a method for multiple hypothesis testing correction">
-            <option value="BH" selected="true">Benjamini-Hochberg [FDR] (1995)</option>
-            <option value="holm">Holm (1979)</option>
-            <option value="hommel">Hommel (1988)</option>
-            <option value="hochberg">Hochberg (1988)</option>
-            <option value="bonferroni">Bonferroni</option>
-            <option value="BY">Benjamini - Yekutieli (2001)</option>
-        </param>
-        <param help="These plots may help you compare the different p-value estimation methods that goseq can use." label="Produce diagnostic plots?" name="make_plots" type="boolean"></param>
+
+        <!-- Output Options -->
+        <section name="out" title="Output Options">
+            <param name="make_plots" type="boolean" checked="false" label="Produce diagnostic plots?" help="This will produce the length bias (PWF) plot. If both sampling and wallenius methods are selected, it will also produce a plot comparing their p-values. These plots may help you compare the different p-value estimation methods that goseq can use. Default: No" />
+            <param name="rdata_out" type="boolean" checked="false" label="Output RData file?" help="Output all the data used by R to construct the tables and plots, can be loaded into R. Default: No" />
+        </section>
+
+        <!-- Advanced Options -->
+        <section name="adv" title="Advanced Options">
+            <param name="p_adj_method" type="select" label="Select a method for multiple hypothesis testing correction">
+                <option value="BH" selected="True">Benjamini-Hochberg [FDR] (1995)</option>
+                <option value="holm">Holm (1979)</option>
+                <option value="hommel">Hommel (1988)</option>
+                <option value="hochberg">Hochberg (1988)</option>
+                <option value="bonferroni">Bonferroni</option>
+                <option value="BY">Benjamini - Yekutieli (2001)</option>
+            </param>
+            <param name="use_genes_without_cat" type="boolean" checked="false" label="Count genes without any category?" help="For example, a large number of genes may have no GO term annotated. If this option is set to No, those genes will be ignored in the calculation of p-values. If this option is set to Yes, then these genes will count towards the total number of genes outside the category being tested. This was the default behaviour for version 1.15.1 and earlier. Default: No"/>
+        </section>
     </inputs>
+
     <outputs>
-        <data name="length_bias_plot" format="pdf" label="length bias plot">
-            <filter>make_plots</filter>
-            <filter>methods['hypergeometric']</filter>
+        <data name="wallenius_tab" format="tabular" label="${tool.name} on ${on_string}: Ranked category list - Wallenius method">
+            <filter>methods['wallenius]'</filter>
         </data>
-        <data name="sample_vs_wallenius_plot" format="pdf" label="Plot P-value from sampling against wallenius distribution">
-            <filter>methods['repcnt'] != 0</filter>
-            <filter>methods['wallenius']</filter>
-            <filter>make_plots</filter>
-        </data>
-        <data name="nobias_tab" format="tabular" label="Ranked category list - no length bias correction">
-            <filter>methods['hypergeometric']</filter>
-        </data>
-        <data name="sampling_tab" format="tabular" label="Ranked category list - sampling">
+        <data name="sampling_tab" format="tabular" label="${tool.name} on ${on_string}: Ranked category list - Sampling method">
             <filter>methods['repcnt'] != 0</filter>
         </data>
-        <data name="wallenius_tab" format="tabular" label="Ranked category list - wallenius method">
+        <data name="nobias_tab" format="tabular" label="${tool.name} on ${on_string}: Ranked category list - Hypergeometric method">
+            <filter>methods['hypergeometric']</filter>
+        </data>
+        <data name="length_bias_plot" format="pdf" label="${tool.name} on ${on_string}: Length bias plot">
+            <filter>out['make_plots']</filter>
+        </data>
+        <data name="sample_vs_wallenius_plot" format="pdf" label="${tool.name} on ${on_string}: Sampling vs Wallenius P-values plot">
+            <filter>methods['repcnt'] != 0</filter>
             <filter>methods['wallenius']</filter>
+            <filter>out['make_plots']</filter>
+        </data>
+        <data name="rdata" format="rdata" from_work_dir="goseq_analysis.RData" label="${tool.name} on ${on_string}: RData file">
+            <filter>out['rdata_out']</filter>
         </data>
     </outputs>
+
     <tests>
-        <test>
+        <!-- Ensure Wallenius table is output -->
+        <test expect_num_outputs="1">
+            <param name="dge_file" value="dge_list.tab" ftype="tabular" />
+            <param name="length_file" value="gene_length.tab" ftype="tabular" />
+            <param name="catSource" value="history" />
+            <param name="category_file" value="category.tab" ftype="tabular" />
+            <param name="use_genes_without_cat" value="true" />
+            <output name="wallenius_tab" file="wal.tab" compare="contains" />
+        </test>
+        <!-- Ensure getting GO categories works -->
+        <test expect_num_outputs="1">
             <param name="dge_file" value="dge_list.tab" ftype="tabular"/>
             <param name="length_file" value="gene_length.tab" ftype="tabular"/>
-            <param name="category_file" value="category.tab" ftype="tabular"/>
+            <param name="catSource" value="getgo" />
+            <param name="genome" value="hg38" />
+            <param name="gene_id" value="ensGene" />
+            <param name="use_genes_without_cat" value="true" />
+            <output name="wallenius_tab" ftype="tabular" file="getgo.hg38.tab" compare="contains"/>
+        </test>
+        <!-- Ensure getting GO categories for another genome (zebrafish) works -->
+        <test expect_num_outputs="1">
+            <param name="dge_file" value="dge_list_zf.tab" ftype="tabular"/>
+            <param name="length_file" value="gene_length_zf.tab" ftype="tabular"/>
+            <param name="catSource" value="getgo" />
+            <param name="genome" value="danRer10"/>
+            <param name="gene_id" value="ensGene" />
+            <param name="use_genes_without_cat" value="true" />
+            <output name="wallenius_tab" ftype="tabular" file="getgo.danRer10.tab" compare="contains"/>
+        </test>
+        <!-- Ensure length bias plot works -->
+        <test expect_num_outputs="2">
+            <param name="dge_file" value="dge_list.tab" ftype="tabular" />
+            <param name="length_file" value="gene_length.tab" ftype="tabular" />
+            <param name="catSource" value="history" />
+            <param name="category_file" value="category.tab" ftype="tabular" />
+            <param name="make_plots" value="true" />
             <param name="use_genes_without_cat" value="true" />
-            <output name="wallenius_tab" file="wal.tab" compare="re_match"/>
+            <output name="length_bias_plot" ftype="pdf" file="length_bias_plot.pdf" compare="sim_size" />
+        </test>
+        <!-- Ensure hypergeometric works -->
+        <test expect_num_outputs="2">
+            <param name="dge_file" value="dge_list.tab" ftype="tabular" />
+            <param name="length_file" value="gene_length.tab" ftype="tabular" />
+            <param name="catSource" value="history" />
+            <param name="category_file" value="category.tab" ftype="tabular" />
+            <param name="use_genes_without_cat" value="true" />
+            <param name="hypergeometric" value="true" />
+            <output name="nobias_tab" file="nobias.tab" compare="contains" />
+        </test>
+        <!-- Ensure sampling vs wallenius works -->
+        <test expect_num_outputs="4">
+            <param name="dge_file" value="dge_list.tab" ftype="tabular" />
+            <param name="length_file" value="gene_length.tab" ftype="tabular" />
+            <param name="catSource" value="history" />
+            <param name="category_file" value="category.tab" ftype="tabular" />
+            <param name="use_genes_without_cat" value="true" />
+            <param name="make_plots" value="true" />
+            <param name="repcnt" value="1000" />
+            <output name="sampling_tab" file="samp.tab" compare="sim_size" />
+            <output name="length_bias_plot" ftype="pdf" file="length_bias_plot.pdf" compare="sim_size" />
+            <output name="sample_vs_wallenius_plot" ftype="pdf" file="sample_vs_wallenius_plot.pdf" compare="sim_size" />
+        </test>
+        <!-- Ensure RData output works -->
+        <test expect_num_outputs="2">
+            <param name="dge_file" value="dge_list.tab" ftype="tabular" />
+            <param name="length_file" value="gene_length.tab" ftype="tabular" />
+            <param name="catSource" value="history" />
+            <param name="category_file" value="category.tab" ftype="tabular" />
+            <param name="use_genes_without_cat" value="true" />
+            <param name="rdata_out" value="true" />
+            <output name="rdata" file="goseq_analysis.RData" compare="sim_size" />
         </test>
     </tests>
-    <help>
+
+    <help><![CDATA[
+
+.. class:: infomark
+
+**What it does**
 
-        **What it does**
+`Gene Ontology`_ (GO) analysis is widely used to reduce complexity and highlight biological processes in genome-wide expression studies, but standard methods give biased results on RNA-seq data due to over-detection of differential expression for long and highly expressed transcripts. This tool provides methods for performing GO analysis of RNA-seq data, taking length bias into account. The methods and software used by goseq are equally applicable to other category based tests of RNA-seq data, such as KEGG_ pathway analysis.
+
+Options map closely to the excellent goseq manual_.
+
+-----
+
+**Inputs**
 
-        Detects Gene Ontology and/or other user defined categories which are over/under-represented in RNA-seq data.
+*Differentially expressed genes file*
+
+goseq needs a tabular file containing information on differentially expressed genes. This should contain all genes assayed in the RNA-seq experiment. The file should have two columns with an optional header row. The first column should contain the Gene IDs, which must be unique within the file and not repeated. The second column should contain True or False. 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.
+
+Example:
 
-        Options map closely to the excellent manual_
+    =============== =====
+    ENSG00000236824 False
+    ENSG00000162526 False
+    ENSG00000090402 True
+    ENSG00000169188 False
+    ENSG00000124103 False
+    =============== =====
 
+*Gene lengths file*
 
-        **Input files**
+goseq needs information about the length of a gene to correct for potential length bias in differentially expressed genes using a Probability Weight Function (PWF). The PWF can be thought of, as a function which gives the probability that a gene will be differentially expressed, based on its length alone. The gene length file should have two columns with an optional header row. The first column should contain the Gene IDs, and the second column should contain the gene length in bp. If length data is unavailable for some genes, that entry should be set to NA. The goseq authors recommend using the gene lengths obtained from upstream summarization programs, such as **featureCounts**, if provided. Alternatively, the **Gene length and GC content** tool can produce such a file.
 
-        *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.
+Example:
+
+    =============== =====
+    ENSG00000236824 13458
+    ENSG00000162526 2191
+    ENSG00000090402 6138
+    ENSG00000169188 3245
+    ENSG00000124103 1137
+    =============== =====
+
+*Gene categories file*
+
+This tool can get GO and KEGG categories for some genomes. The three GO categories are GO:MF (Molecular Function - molecular activities of gene products), GO:CC (Cellular Component - where gene products are active), GO:BP (Biological Process - pathways and larger processes made up of the activities of multiple gene products). If your genome is not available, you will also need a file describing the membership of genes in categories. The category file should have two columns with an optional header row. with Gene ID in the first column and category identifier in the second column. As the mapping between categories and genes is usually many-to-many, this table will usually have multiple rows with the same Gene ID and category identifier.
+
+Example:
 
-        *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.
+    =============== ===========
+    ENSG00000162526 GO\:0000003
+    ENSG00000198648 GO\:0000278
+    ENSG00000112312 GO\:0000278
+    ENSG00000174442 GO\:0000278
+    ENSG00000108953 GO\:0000278
+    =============== ===========
+
+-----
+
+**Outputs**
+
+* This tool outputs a tabular file containing a ranked list of gene categories, similar to below. The default output is the Wallenius method table. If the Sampling and/or Hypergeometric methods are also selected, additional tables are produced.
+* Optionally, this tool can also output some diagnostic plots and an RData file, see **Output Options** above.
+
+Example:
 
-        *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 identifier in the second column.
+=========== =============== ================ ============ ========== ======================================== ========== =================== ====================
+*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
+GO\:0044763  0.000252        0.999858         148          473       single-organism cellular process         BP         0.394825             1
+GO\:0044699  0.000279        0.999844         158          513       single-organism process                  BP         0.394825             1
+GO\:0065010  0.000428        0.999808         43           108       extracellular membrane-bounded organelle CC         0.394825             1
+GO\:0070062  0.000428        0.999808         43           108       extracellular exosome                    CC         0.394825             1
+=========== =============== ================ ============ ========== ======================================== ========== =================== ====================
 
-        **Method options**
+-----
+
+**Method options**
 
-        3 methods, "Wallenius", "Sampling" and "Hypergeometric", can be used to calculate the p-values as follows.
+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. This is the method used by default.
+
+*Sampling*
 
-        *"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.
+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 number, its use quickly becomes computationally prohibitive. It may sometimes be desirable to use random sampling to generate the null distribution for category
+membership. For example, to check consistency against results from the Wallenius approximation. This is easily accomplished by using the method option to additionally specify sampling and the number of samples to generate.
+
+*Hypergeometric*
+
+assumes there is no bias in power to detect differential expression at all and calculates the p-values using a standard hypergeometric distribution (no length bias correction is performed). Useful if you wish to test the effect of length bias on your results.
+Caution: Hypergeometric should NEVER be used for producing results for biological interpretation of RNA-seq data. If length bias is truly not present in your data, goseq will produce a nearly flat PWF plot, no length bias correction will be applied to your data, and all methods will produce the same results.
 
-        *"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.
+-----
+
+**More Information**
 
-        *"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.
+In order to account for the length bias inherent to RNA-seq data when performing a GO analysis
+(or other category based tests), one cannot simply use the hypergeometric distribution as the null
+distribution for category membership, which is appropriate for data without DE length bias, such
+as microarray data. GO analysis of RNA-seq data requires the use of random sampling in order
+to generate a suitable null distribution for GO category membership and calculate each categories
+significance for over representation amongst DE genes.
+
+However, this random sampling is computationally expensive. In most cases, the Wallenius
+distribution can be used to approximate the true null distribution, without any significant loss in
+accuracy. The goseq package implements this approximation as its default option. The option
+to generate the null distribution using random sampling is also included as an option, but users
+should be aware that the default number of samples generated will not be enough to accurately
+call enrichment when there are a large number of go terms.
 
-        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.
+Having established a null distribution, each category is then tested for over and under
+representation amongst the set of differentially expressed genes and the null is used to calculate a
+p-value for under and over representation.
+
+Having performed a GO analysis, you may now wish to interpret the results. If you wish to
+identify categories significantly enriched/unenriched below some p-value cutoff, it is necessary to
+first apply some kind of multiple hypothesis testing correction. For example, you can identify GO categories over
+enriched using a 0.05 FDR (p.adjust) cutoff [Benjamini and Hochberg, 1995].
 
-        .. _manual: https://bioconductor.org/packages/release/bioc/vignettes/goseq/inst/doc/goseq.pdf
+Unless you are a machine, GO and KEGG category identifiers are probably not very meaningful to you.
+Information about each identifier can be obtained from the `Gene Ontology`_ and KEGG_ websites.
 
+.. _manual: https://bioconductor.org/packages/release/bioc/vignettes/goseq/inst/doc/goseq.pdf
+.. _Gene Ontology: http://www.geneontology.org
+.. _KEGG: http://www.genome.jp/kegg
 
-    </help>
+    ]]></help>
     <citations>
         <citation type="doi">10.1186/gb-2010-11-2-r14</citation>
     </citations>
-</tool>
+</tool>
\ No newline at end of file
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/dge_list_zf.tab	Mon Oct 23 11:19:12 2017 -0400
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+ENSDARG00000045909	FALSE
+ENSDARG00000055917	FALSE
+ENSDARG00000070426	TRUE
+ENSDARG00000076110	TRUE
+ENSDARG00000090002	FALSE
+ENSDARG00000023111	FALSE
+ENSDARG00000012125	FALSE
+ENSDARG00000007172	FALSE
+ENSDARG00000026178	FALSE
+ENSDARG00000060445	FALSE
+ENSDARG00000018162	TRUE
+ENSDARG00000060661	FALSE
+ENSDARG00000013659	FALSE
+ENSDARG00000102744	FALSE
+ENSDARG00000071501	FALSE
+ENSDARG00000036090	FALSE
+ENSDARG00000045704	FALSE
+ENSDARG00000007221	TRUE
+ENSDARG00000041407	FALSE
+ENSDARG00000005356	FALSE
+ENSDARG00000102356	TRUE
+ENSDARG00000078479	TRUE
+ENSDARG00000029368	TRUE
+ENSDARG00000058992	FALSE
+ENSDARG00000027529	FALSE
+ENSDARG00000075369	TRUE
+ENSDARG00000063731	TRUE
+ENSDARG00000036542	TRUE
+ENSDARG00000014569	TRUE
+ENSDARG00000099298	FALSE
+ENSDARG00000091851	FALSE
+ENSDARG00000070698	FALSE
+ENSDARG00000088807	FALSE
+ENSDARG00000028725	FALSE
+ENSDARG00000039719	FALSE
+ENSDARG00000013732	FALSE
+ENSDARG00000037425	TRUE
+ENSDARG00000057151	FALSE
+ENSDARG00000092488	FALSE
+ENSDARG00000096454	FALSE
+ENSDARG00000070028	FALSE
+ENSDARG00000016710	FALSE
+ENSDARG00000075072	FALSE
+ENSDARG00000070867	TRUE
+ENSDARG00000037846	FALSE
+ENSDARG00000018600	FALSE
+ENSDARG00000013711	FALSE
+ENSDARG00000077081	FALSE
+ENSDARG00000067784	FALSE
+ENSDARG00000038731	TRUE
+ENSDARG00000035181	FALSE
+ENSDARG00000011240	FALSE
+ENSDARG00000075616	TRUE
+ENSDARG00000038442	TRUE
+ENSDARG00000002026	TRUE
+ENSDARG00000098618	FALSE
+ENSDARG00000069505	FALSE
+ENSDARG00000074892	FALSE
+ENSDARG00000055360	FALSE
+ENSDARG00000056797	FALSE
+ENSDARG00000017115	FALSE
+ENSDARG00000075533	FALSE
+ENSDARG00000091906	FALSE
+ENSDARG00000076501	TRUE
+ENSDARG00000017659	TRUE
+ENSDARG00000029660	FALSE
+ENSDARG00000004297	FALSE
+ENSDARG00000010280	FALSE
+ENSDARG00000022968	FALSE
+ENSDARG00000019033	TRUE
+ENSDARG00000015638	FALSE
+ENSDARG00000086550	FALSE
+ENSDARG00000007918	FALSE
+ENSDARG00000039677	TRUE
+ENSDARG00000073784	TRUE
+ENSDARG00000100862	FALSE
+ENSDARG00000003058	FALSE
+ENSDARG00000074644	TRUE
+ENSDARG00000013892	FALSE
+ENSDARG00000104348	FALSE
+ENSDARG00000053457	TRUE
+ENSDARG00000058351	FALSE
+ENSDARG00000034670	TRUE
+ENSDARG00000075169	FALSE
+ENSDARG00000078894	FALSE
+ENSDARG00000044090	FALSE
+ENSDARG00000092077	TRUE
+ENSDARG00000030694	TRUE
+ENSDARG00000016886	TRUE
+ENSDARG00000043339	FALSE
+ENSDARG00000103225	FALSE
+ENSDARG00000086411	TRUE
+ENSDARG00000104874	FALSE
+ENSDARG00000052747	FALSE
+ENSDARG00000075823	TRUE
+ENSDARG00000043843	FALSE
+ENSDARG00000077614	TRUE
+ENSDARG00000054220	FALSE
+ENSDARG00000009626	FALSE
+ENSDARG00000009023	TRUE
+ENSDARG00000045561	FALSE
+ENSDARG00000056559	FALSE
+ENSDARG00000017272	TRUE
+ENSDARG00000022788	FALSE
+ENSDARG00000018272	FALSE
+ENSDARG00000056473	FALSE
+ENSDARG00000099766	TRUE
+ENSDARG00000002991	FALSE
+ENSDARG00000104431	FALSE
+ENSDARG00000062465	FALSE
+ENSDARG00000054583	TRUE
+ENSDARG00000013802	FALSE
+ENSDARG00000057910	TRUE
+ENSDARG00000027984	FALSE
+ENSDARG00000045420	FALSE
+ENSDARG00000031359	FALSE
+ENSDARG00000056764	FALSE
+ENSDARG00000095594	FALSE
+ENSDARG00000076191	FALSE
+ENSDARG00000103251	FALSE
+ENSDARG00000039501	TRUE
+ENSDARG00000103589	FALSE
+ENSDARG00000051926	FALSE
+ENSDARG00000018681	FALSE
+ENSDARG00000014138	TRUE
+ENSDARG00000061462	TRUE
+ENSDARG00000102111	FALSE
+ENSDARG00000035819	FALSE
+ENSDARG00000076486	FALSE
+ENSDARG00000101799	FALSE
+ENSDARG00000008105	FALSE
+ENSDARG00000040387	FALSE
+ENSDARG00000060518	FALSE
+ENSDARG00000001244	FALSE
+ENSDARG00000005540	FALSE
+ENSDARG00000070055	FALSE
+ENSDARG00000073841	FALSE
+ENSDARG00000032117	FALSE
+ENSDARG00000087110	FALSE
+ENSDARG00000075641	TRUE
+ENSDARG00000001829	FALSE
+ENSDARG00000103786	TRUE
+ENSDARG00000058486	FALSE
+ENSDARG00000042272	FALSE
+ENSDARG00000000474	FALSE
+ENSDARG00000061635	FALSE
+ENSDARG00000095745	FALSE
+ENSDARG00000073801	FALSE
+ENSDARG00000028086	FALSE
+ENSDARG00000056583	FALSE
+ENSDARG00000033182	TRUE
+ENSDARG00000052703	FALSE
+ENSDARG00000051873	FALSE
+ENSDARG00000002267	FALSE
+ENSDARG00000091538	FALSE
+ENSDARG00000067713	FALSE
\ No newline at end of file
--- a/test-data/gc.tab	Sun Jun 11 08:57:39 2017 -0400
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,1 +0,0 @@
-ENSG00000162526	0.388349514563107
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/gene_length_zf.tab	Mon Oct 23 11:19:12 2017 -0400
@@ -0,0 +1,632 @@
+ENSDARG00000092696	6983
+ENSDARG00000104569	7302
+ENSDARG00000008472	1848
+ENSDARG00000058451	5878
+ENSDARG00000035957	3057
+ENSDARG00000043514	6176
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+ENSDARG00000088807	4319
+ENSDARG00000028725	4065
+ENSDARG00000039719	9199
+ENSDARG00000013732	1092
+ENSDARG00000037425	6768
+ENSDARG00000057151	15144
+ENSDARG00000092488	2085
+ENSDARG00000096454	6749
+ENSDARG00000070028	2866
+ENSDARG00000016710	1806
+ENSDARG00000075072	7179
+ENSDARG00000070867	11000
+ENSDARG00000037846	2326
+ENSDARG00000018600	15242
+ENSDARG00000013711	3301
+ENSDARG00000077081	3115
+ENSDARG00000067784	15701
+ENSDARG00000038731	4003
+ENSDARG00000035181	8260
+ENSDARG00000011240	4901
+ENSDARG00000075616	2423
+ENSDARG00000038442	7459
+ENSDARG00000002026	3070
+ENSDARG00000098618	6180
+ENSDARG00000069505	2082
+ENSDARG00000074892	12773
+ENSDARG00000055360	7068
+ENSDARG00000056797	5199
+ENSDARG00000017115	3193
+ENSDARG00000075533	7239
+ENSDARG00000091906	8184
+ENSDARG00000076501	2093
+ENSDARG00000017659	3157
+ENSDARG00000029660	4699
+ENSDARG00000004297	3420
+ENSDARG00000010280	2807
+ENSDARG00000022968	2165
+ENSDARG00000019033	7868
+ENSDARG00000015638	3285
+ENSDARG00000086550	3859
+ENSDARG00000007918	5611
+ENSDARG00000039677	2769
+ENSDARG00000073784	2745
+ENSDARG00000100862	6157
+ENSDARG00000003058	2889
+ENSDARG00000074644	6922
+ENSDARG00000013892	5034
+ENSDARG00000104348	3245
+ENSDARG00000053457	7776
+ENSDARG00000058351	4276
+ENSDARG00000034670	5499
+ENSDARG00000075169	1365
+ENSDARG00000078894	4153
+ENSDARG00000044090	7828
+ENSDARG00000092077	7775
+ENSDARG00000030694	2395
+ENSDARG00000016886	5872
+ENSDARG00000043339	8700
+ENSDARG00000103225	3074
+ENSDARG00000086411	2266
+ENSDARG00000104874	2861
+ENSDARG00000052747	8005
+ENSDARG00000075823	2917
+ENSDARG00000043843	3153
+ENSDARG00000077614	4371
+ENSDARG00000054220	8511
+ENSDARG00000009626	8938
+ENSDARG00000009023	3406
+ENSDARG00000045561	3929
+ENSDARG00000056559	8333
+ENSDARG00000017272	7464
+ENSDARG00000022788	3285
+ENSDARG00000018272	1753
+ENSDARG00000056473	594
+ENSDARG00000099766	3391
+ENSDARG00000002991	3520
+ENSDARG00000104431	3327
+ENSDARG00000062465	497
+ENSDARG00000054583	3030
+ENSDARG00000013802	2392
+ENSDARG00000057910	3804
+ENSDARG00000027984	4204
+ENSDARG00000045420	4427
+ENSDARG00000031359	8630
+ENSDARG00000056764	3765
+ENSDARG00000095594	4175
+ENSDARG00000076191	4849
+ENSDARG00000103251	10864
+ENSDARG00000039501	6145
+ENSDARG00000103589	7977
+ENSDARG00000051926	8640
+ENSDARG00000018681	5479
+ENSDARG00000014138	6138
+ENSDARG00000061462	15787
+ENSDARG00000102111	9423
+ENSDARG00000035819	1981
+ENSDARG00000076486	7968
+ENSDARG00000101799	3670
+ENSDARG00000008105	8787
+ENSDARG00000040387	4616
+ENSDARG00000060518	8331
+ENSDARG00000001244	1781
+ENSDARG00000005540	1155
+ENSDARG00000070055	5411
+ENSDARG00000073841	4224
+ENSDARG00000032117	3659
+ENSDARG00000087110	5459
+ENSDARG00000075641	2527
+ENSDARG00000001829	2989
+ENSDARG00000103786	15155
+ENSDARG00000058486	5559
+ENSDARG00000042272	6005
+ENSDARG00000000474	2047
+ENSDARG00000061635	5731
+ENSDARG00000095745	2551
+ENSDARG00000073801	6118
+ENSDARG00000028086	8075
+ENSDARG00000056583	9656
+ENSDARG00000033182	2331
+ENSDARG00000052703	6689
+ENSDARG00000051873	4234
+ENSDARG00000002267	8114
+ENSDARG00000091538	8260
+ENSDARG00000067713	853
\ No newline at end of file
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/getgo.danRer10.tab	Mon Oct 23 11:19:12 2017 -0400
@@ -0,0 +1,10 @@
+category	over_represented_pvalue	under_represented_pvalue	numDEInCat	numInCat	term	ontology	p.adjust.over_represented	p.adjust.under_represented
+GO:0031324	0.019289727841568	0.997004018824821	6	9	negative regulation of cellular metabolic process	BP	1	1
+GO:0040011	0.0219399815699082	0.993554925323586	10	19	locomotion	BP	1	1
+GO:0048738	0.0232122438335162	1	3	3	cardiac muscle tissue development	BP	1	1
+GO:0031101	0.0232122438335199	1	3	3	fin regeneration	BP	1	1
+GO:0042246	0.0232122438335199	1	3	3	tissue regeneration	BP	1	1
+GO:0007050	0.023212243833521	1	3	3	cell cycle arrest	BP	1	1
+GO:0019783	0.0254384360641003	0.998148600664743	4	5	ubiquitin-like protein-specific protease activity	MF	1	1
+GO:0036459	0.0254384360641003	0.998148600664743	4	5	thiol-dependent ubiquitinyl hydrolase activity	MF	1	1
+GO:0101005	0.0254384360641003	0.998148600664743	4	5	ubiquitinyl hydrolase activity	MF	1	1
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/getgo.hg38.tab	Mon Oct 23 11:19:12 2017 -0400
@@ -0,0 +1,10 @@
+category	over_represented_pvalue	under_represented_pvalue	numDEInCat	numInCat	term	ontology	p.adjust.over_represented	p.adjust.under_represented
+GO:0005576	4.72734295222294e-05	0.999979271555286	56	142	extracellular region	CC	0.329456825863645	1
+GO:0005840	0.000150633625443482	0.999987765310632	9	12	ribosome	CC	0.329456825863645	1
+GO:0044763	0.000210237360853053	0.999883100939053	148	473	single-organism cellular process	BP	0.329456825863645	1
+GO:0044699	0.000229197548055812	0.999873090122854	158	513	single-organism process	BP	0.329456825863645	1
+GO:0065010	0.000394294879818402	0.999824474827037	43	108	extracellular membrane-bounded organelle	CC	0.329456825863645	1
+GO:0070062	0.000394294879818402	0.999824474827037	43	108	extracellular exosome	CC	0.329456825863645	1
+GO:0008150	0.000409074003076654	0.999785179807024	191	656	biological_process	BP	0.329456825863645	1
+GO:0005488	0.000447980265756431	0.99975072864471	175	589	binding	MF	0.329456825863645	1
+GO:0005198	0.000511195682086445	0.999905085898726	13	21	structural molecule activity	MF	0.329456825863645	1
--- a/test-data/go_terms.tab	Sun Jun 11 08:57:39 2017 -0400
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,85 +0,0 @@
-ENSG00000162526	GO:0000003
-ENSG00000162526	GO:0000166
-ENSG00000162526	GO:0000287
-ENSG00000162526	GO:0001882
-ENSG00000162526	GO:0001883
-ENSG00000162526	GO:0003674
-ENSG00000162526	GO:0003824
-ENSG00000162526	GO:0004672
-ENSG00000162526	GO:0004674
-ENSG00000162526	GO:0005488
-ENSG00000162526	GO:0005515
-ENSG00000162526	GO:0005524
-ENSG00000162526	GO:0005575
-ENSG00000162526	GO:0005622
-ENSG00000162526	GO:0005623
-ENSG00000162526	GO:0005737
-ENSG00000162526	GO:0006464
-ENSG00000162526	GO:0006468
-ENSG00000162526	GO:0006793
-ENSG00000162526	GO:0006796
-ENSG00000162526	GO:0007154
-ENSG00000162526	GO:0007165
-ENSG00000162526	GO:0007275
-ENSG00000162526	GO:0007276
-ENSG00000162526	GO:0007283
-ENSG00000162526	GO:0008150
-ENSG00000162526	GO:0008152
-ENSG00000162526	GO:0009987
-ENSG00000162526	GO:0016301
-ENSG00000162526	GO:0016310
-ENSG00000162526	GO:0016740
-ENSG00000162526	GO:0016772
-ENSG00000162526	GO:0016773
-ENSG00000162526	GO:0017076
-ENSG00000162526	GO:0019538
-ENSG00000162526	GO:0019953
-ENSG00000162526	GO:0022414
-ENSG00000162526	GO:0023052
-ENSG00000162526	GO:0030154
-ENSG00000162526	GO:0030554
-ENSG00000162526	GO:0032501
-ENSG00000162526	GO:0032502
-ENSG00000162526	GO:0032504
-ENSG00000162526	GO:0032549
-ENSG00000162526	GO:0032550
-ENSG00000162526	GO:0032553
-ENSG00000162526	GO:0032555
-ENSG00000162526	GO:0032559
-ENSG00000162526	GO:0035556
-ENSG00000162526	GO:0035639
-ENSG00000162526	GO:0036094
-ENSG00000162526	GO:0036211
-ENSG00000162526	GO:0043167
-ENSG00000162526	GO:0043168
-ENSG00000162526	GO:0043169
-ENSG00000162526	GO:0043170
-ENSG00000162526	GO:0043412
-ENSG00000162526	GO:0044237
-ENSG00000162526	GO:0044238
-ENSG00000162526	GO:0044260
-ENSG00000162526	GO:0044267
-ENSG00000162526	GO:0044424
-ENSG00000162526	GO:0044464
-ENSG00000162526	GO:0044699
-ENSG00000162526	GO:0044700
-ENSG00000162526	GO:0044702
-ENSG00000162526	GO:0044703
-ENSG00000162526	GO:0044707
-ENSG00000162526	GO:0044763
-ENSG00000162526	GO:0044767
-ENSG00000162526	GO:0046872
-ENSG00000162526	GO:0048232
-ENSG00000162526	GO:0048609
-ENSG00000162526	GO:0048869
-ENSG00000162526	GO:0050789
-ENSG00000162526	GO:0050794
-ENSG00000162526	GO:0050896
-ENSG00000162526	GO:0051704
-ENSG00000162526	GO:0051716
-ENSG00000162526	GO:0065007
-ENSG00000162526	GO:0071704
-ENSG00000162526	GO:0097159
-ENSG00000162526	GO:0097367
-ENSG00000162526	GO:1901265
-ENSG00000162526	GO:1901363
Binary file test-data/goseq_analysis.RData has changed
--- a/test-data/length.tab	Sun Jun 11 08:57:39 2017 -0400
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,1 +0,0 @@
-ENSG00000162526	103
Binary file test-data/length_bias_plot.pdf has changed
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/nobias.tab	Mon Oct 23 11:19:12 2017 -0400
@@ -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	0.0129827306163772	0.999244816412166	4	5	mitotic cell cycle	BP	0.0259654612327543	0.999244816412166
+GO:0000003	1	0.761	0	1	reproduction	BP	1	0.999244816412166
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/samp.tab	Mon Oct 23 11:19:12 2017 -0400
@@ -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	0.016983016983017	1	4	5	mitotic cell cycle	BP	0.033966033966034	1
+GO:0000003	1	0.802197802197802	0	1	reproduction	BP	1	1
Binary file test-data/sample_vs_wallenius_plot.pdf has changed
--- a/test-data/wal.tab	Sun Jun 11 08:57:39 2017 -0400
+++ b/test-data/wal.tab	Mon Oct 23 11:19:12 2017 -0400
@@ -1,3 +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.+
+category	over_represented_pvalue	under_represented_pvalue	numDEInCat	numInCat	term	ontology	p.adjust.over_represented	p.adjust.under_represented
+GO:0000278	0.0112350612534339	0.999376653834006	4	5	mitotic cell cycle	BP	0.0224701225068678	0.999376653834006
+GO:0000003	1	0.805913166914892	0	1	reproduction	BP	1	0.999376653834006