Mercurial > repos > mvdbeek > r_goseq_1_22_0

changeset 7:9ffae7bc23c2 draft

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planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/goseq_1_22_0 commit f95b47ed1a09ce14d3b565e8ea56d8bf12c35814-dirty
author mvdbeek
date Mon, 07 Mar 2016 13:57:32 -0500
parents 0e9424413ab0
children fb95db039592
files goseq.r goseq.xml test-data/dge_list.tab test-data/wal.tab tool_dependencies.xml
diffstat 5 files changed, 1096 insertions(+), 1043 deletions(-) [+]
line wrap: on
line diff
--- a/goseq.r	Thu Mar 03 09:56:51 2016 -0500
+++ b/goseq.r	Mon Mar 07 13:57:32 2016 -0500
@@ -15,14 +15,12 @@
     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("-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?")
@@ -34,8 +32,6 @@
 # Vars:
 dge_file = args$dge_file
 category_file = args$category_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$gene_id
@@ -45,20 +41,14 @@
 length_bias_plot = args$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
-first_line = read.delim(dge_file, header = FALSE, nrow=1)
-# check if header [character where numeric is expected]
-if (is.numeric(first_line[,p_adj_column])) {
-  dge_table = read.delim(dge_file, header = FALSE, sep="\t")
-  } else {
-  dge_table = read.delim(dge_file, header = TRUE, sep="\t")
-  }
-
-genes = as.integer(dge_table[,p_adj_column]<p_adj_cutoff)
-names(genes) = dge_table[,1] # Assuming first row contains gene names
+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" ) {
@@ -96,13 +86,27 @@
 }
 
 # wallenius approximation of p-values
-GO.wall=goseq(pwf, genome = genome, id = gene_id, use_genes_without_cat = use_genes_without_cat, gene2cat=go_map)
+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)
+}
 
-GO.nobias=goseq(pwf, genome = genome, id = gene_id, method="Hypergeometric", use_genes_without_cat = use_genes_without_cat, gene2cat=go_map)
+# 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)
@@ -112,17 +116,22 @@
      abline(0,1,col=3,lty=2)
   graphics.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)
+# supported_genomes = subset(supportedGenomes(), AvailableGeneIDs != "")
+# write.table(supported_genomes, "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)
+
+## get a list of genome db packages to install:
+# library("stringr")
+# orglist = unique(sapply(supported_genomes$db, function(x) str_extract(x, "[a-zA-Z]+" )))
+## install all genome packages
+# sapply(orglist, function(x) biocLite(paste("org", x, "eg.db", sep=".")))
+## get list of packages:
+# org_packages = sapply(orglist, function(x) paste("org", x, "eg.db", sep="."))
+# write.table(org_packages, "org_packages.tab", row.names = FALSE, col.names=FALSE, quote = FALSE)
\ No newline at end of file
--- a/goseq.xml	Thu Mar 03 09:56:51 2016 -0500
+++ b/goseq.xml	Mon Mar 07 13:57:32 2016 -0500
@@ -1,4 +1,4 @@
-<tool id="goseq" name="goseq" version="0.2.0">
+<tool id="goseq" name="goseq" version="0.2.2">
     <description>tests for overrepresented gene categories</description>
     <macros>
         <import>go_macros.xml</import>
@@ -7,43 +7,62 @@
     <expand macro="stdio" />
     <command interpreter="Rscript">
         goseq.r --dge_file "$dge_file"
-        --p_adj_column "$p_adj_column"
-        --cutoff "$p_adj_cutoff"
         --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"
-        --nobias_tab "$nobias_tab"
+        --p_adj_method "$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"
-        --repcnt "$repcnt"
-        --use_genes_without_cat "$use_genes_without_cat"
-        --make_plots "$make_plots"
     </command>
     <inputs>
-        <param help="deseq2/edger/limma differential gene expression list" label="DGE list" name="dge_file" type="data" format="tabular" />
-        <param help="Select the column that contains the multiple-testing corrected p-value" label="p adjust column" name="p_adj_column" type="data_column" numeric="true" data_ref="dge_file"/>
+        <param 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" name="dge_file" type="data" format="tabular" />
         <param label="Gene length file for length bias correction" help="You can calculate the gene length using the get length and gc content tool" name="length_file" type="data" format="tabular" required="true" />
         <param label="Gene category file" help="You can obtain a mapping of gene id to gene ontology using the getgo tool" name="category_file" type="data" format="tabular" required="true" />
         <param 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"
                name="use_genes_without_cat" label="Count genes without any category?" type="boolean"/>
-        <param help="Typically 0.05 after multiple testing correction" max="1" label="Minimum p adjust value to consider genes as differentially expressed" name="p_adj_cutoff" type="float" value="0.05" />
+        <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 help="Draw this many random control gene sets. Set to 0 to not do sampling. Larger values take a long time" label="sampling depth" name="repcnt" size="3" type="integer" min="0" max="10000" value="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>
-        <param help="Draw this many random control gene sets. Set to 0 to not do sampling. Larger values take a long time" label="sampling depth" name="repcnt" size="3" type="integer" min="0" max="10000" value="0" />
     </inputs>
     <outputs>
         <data format="pdf" label="length bias plot" name="length_bias_plot">
             <filter>make_plots</filter>
+            <filter>methods['hypergeometric']</filter>
         </data>
         <data format="pdf" label="Plot P-value from sampling against wallenius distribution" name="sample_vs_wallenius_plot">
-            <filter>repcnt != 0</filter>
+            <filter>methods['repcnt'] != 0</filter>
+            <filter>methods['wallenius']</filter>
             <filter>make_plots</filter>
         </data>
-        <data format="tabular" label="Ranked category list - no length bias correction" name="nobias_tab" />
+        <data format="tabular" label="Ranked category list - no length bias correction" name="nobias_tab">
+            <filter>methods['hypergeometric']</filter>
+        </data>
         <data format="tabular" label="Ranked category list - sampling" name="sampling_tab">
-            <filter>repcnt != 0</filter>
+            <filter>methods['repcnt'] != 0</filter>
         </data>
-        <data format="tabular" label="Ranked category list - wallenius approx. of p-values" name="wallenius_tab" />
+        <data format="tabular" label="Ranked category list - wallenius method" name="wallenius_tab">
+            <filter>methods['wallenius']</filter>
+        </data>
     </outputs>
     <tests>
         <test>
@@ -66,14 +85,39 @@
 
         **Input files**
 
-        goseq needs information about the length of a gene to correct for potential length bias in differentially expressed genes.
+        *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
 
 
--- a/test-data/dge_list.tab	Thu Mar 03 09:56:51 2016 -0500
+++ b/test-data/dge_list.tab	Mon Mar 07 13:57:32 2016 -0500
@@ -1,1000 +1,1000 @@
-ENSG00000140459	0.72654265501997
-ENSG00000236824	0.621241793648661
-ENSG00000162526	0.104072112354657
-ENSG00000090402	0.00550590320364419
-ENSG00000169188	0.752973943574106
-ENSG00000124103	0.508292390900193
-ENSG00000241680	0.297679791800193
-ENSG00000089009	0.300444395667807
-ENSG00000196696	0.374747091864761
-ENSG00000006837	0.883750148448997
-ENSG00000112312	0.00157610534964364
-ENSG00000240392	0.302701874577034
-ENSG00000010932	0.118981349588869
-ENSG00000167685	0.076500408607647
-ENSG00000237101	0.748031404245103
-ENSG00000244270	0.567972685627182
-ENSG00000104331	0.00579192580215921
-ENSG00000242858	0.0378412177811479
-ENSG00000148484	0.718026595230658
-ENSG00000057608	0.964227972088948
-ENSG00000182841	0.0884209354151656
-ENSG00000230903	0.350797225752382
-ENSG00000106868	0.788981237232149
-ENSG00000214564	0.655009438199043
-ENSG00000169762	0.255621294102106
-ENSG00000168758	0.163373910729433
-ENSG00000182827	0.880121187926376
-ENSG00000125637	0.0396047898199658
-ENSG00000118873	0.259118545361492
-ENSG00000186532	0.884943302417759
-ENSG00000106771	0.107076952807406
-ENSG00000204348	0.38585136650363
-ENSG00000197062	0.244378087660012
-ENSG00000171067	0.860339995928752
-ENSG00000228118	0.837580099847927
-ENSG00000213077	0.0346627558595947
-ENSG00000188549	0.0364688234065438
-ENSG00000135537	0.818437150201755
-ENSG00000173715	0.313716721815305
-ENSG00000227742	0.00693864770618258
-ENSG00000148158	0.00356590491562172
-ENSG00000134461	0.0799694519824768
-ENSG00000174442	0.9104363820863
-ENSG00000198648	5.66237569853738e-54
-ENSG00000228599	0.171370116774069
-ENSG00000167842	1.68461902141834e-06
-ENSG00000108953	0.018535085127156
-ENSG00000185504	0.000252088854916783
-ENSG00000178950	0.374511091101791
-ENSG00000160051	0.837754660842895
-ENSG00000130787	0.627567039717229
-ENSG00000154146	0.21971850994087
-ENSG00000204956	0.922155399062633
-ENSG00000231181	0.798470252573313
-ENSG00000149308	0.205056998763193
-ENSG00000151748	0.960438036765227
-ENSG00000141510	0.843199243028581
-ENSG00000105325	0.256030223197636
-ENSG00000173163	0.307924645611919
-ENSG00000064545	0.0294202433903509
-ENSG00000236946	0.787953789147351
-ENSG00000104450	0.0261557859283198
-ENSG00000174469	0.371325165629903
-ENSG00000010322	0.0208260631889359
-ENSG00000126562	0.788271827203178
-ENSG00000143919	0.883536889885289
-ENSG00000236285	0.652881364924924
-ENSG00000160213	0.891666551921221
-ENSG00000185798	0.808815635747676
-ENSG00000073614	0.730900557418546
-ENSG00000138587	0.892556542035936
-ENSG00000090273	0.485697340128452
-ENSG00000123384	0.182965348704756
-ENSG00000070961	5.54110180984277e-14
-ENSG00000159346	0.577707704641258
-ENSG00000141425	0.209299850711904
-ENSG00000072071	0.264953967987316
-ENSG00000057935	0.0876841507255324
-ENSG00000226790	0.739812259382103
-ENSG00000117410	0.0991426717444789
-ENSG00000100038	5.5224120355487e-05
-ENSG00000169660	0.957344873331126
-ENSG00000227968	0.968126132117202
-ENSG00000220483	0.834400227373994
-ENSG00000186130	0.0886115611903655
-ENSG00000018607	0.892228191251005
-ENSG00000142676	3.05327141290058e-07
-ENSG00000226144	0.15035721878846
-ENSG00000233454	0.535010072830088
-ENSG00000230006	0.993550786209047
-ENSG00000225405	0.51182760145349
-ENSG00000206192	0.998818135341878
-ENSG00000141012	0.675869428835717
-ENSG00000133138	0.596116982047846
-ENSG00000240418	0.0414032135189338
-ENSG00000230074	0.176837449607711
-ENSG00000106803	0.110457736393565
-ENSG00000134987	0.419483726256258
-ENSG00000179119	0.90886027052608
-ENSG00000130770	0.797934384822854
-ENSG00000213760	0.733546382048368
-ENSG00000167785	0.819823215696948
-ENSG00000152782	0.187934176357927
-ENSG00000103121	0.000116075418643732
-ENSG00000167614	0.97150896023414
-ENSG00000145990	0.600668890368056
-ENSG00000233846	0.617587088091658
-ENSG00000137285	0.762128131856854
-ENSG00000186743	0.390864600953697
-ENSG00000130717	0.786671083021599
-ENSG00000235363	0.310504546625491
-ENSG00000152642	0.762465600065342
-ENSG00000239377	0.214012002346404
-ENSG00000231245	0.737683816033356
-ENSG00000188295	0.750895945796621
-ENSG00000228195	0.529749476495161
-ENSG00000158669	0.729783348308454
-ENSG00000198929	0.261192558212211
-ENSG00000112306	0.00468906205664554
-ENSG00000134324	0.0572864697533481
-ENSG00000143256	0.906787427531995
-ENSG00000175322	0.914734455086495
-ENSG00000110092	1.03715044519433e-05
-ENSG00000175176	0.000120982104535695
-ENSG00000176407	0.0477581143523351
-ENSG00000156050	0.539813926743088
-ENSG00000223068	1.51936638042074e-06
-ENSG00000115221	0.430770408315799
-ENSG00000070495	0.053913958740154
-ENSG00000151718	0.123382838291759
-ENSG00000198752	0.637401967175991
-ENSG00000196747	0.835333183773412
-ENSG00000204253	0.00530466739928374
-ENSG00000176593	0.256140584508036
-ENSG00000106789	0.0134644631782369
-ENSG00000100526	4.70087255096658e-05
-ENSG00000004534	1.35379973849169e-08
-ENSG00000158470	0.0835263687151232
-ENSG00000213062	0.341979029879746
-ENSG00000151876	0.881499319093158
-ENSG00000213493	0.178233355277396
-ENSG00000083720	0.0393544959439121
-ENSG00000155621	0.0426855161809279
-ENSG00000164985	0.910782859354861
-ENSG00000109610	0.420752781670774
-ENSG00000183530	0.878676002571331
-ENSG00000137776	1.82559407448247e-06
-ENSG00000184216	0.746675936949786
-ENSG00000156831	0.819155853391606
-ENSG00000213906	0.414509140036116
-ENSG00000105438	0.770380304577372
-ENSG00000175220	0.251478246764494
-ENSG00000170638	0.224686934956879
-ENSG00000227401	0.140044824079938
-ENSG00000164597	7.11766516655365e-35
-ENSG00000011638	0.0280594017062844
-ENSG00000135124	0.585774291040765
-ENSG00000105568	0.00790613784568182
-ENSG00000178229	0.854639645006855
-ENSG00000126858	0.702461621197166
-ENSG00000018408	0.619684410069585
-ENSG00000143816	0.571937260154613
-ENSG00000124496	0.000175359165347661
-ENSG00000136238	0.296018892018342
-ENSG00000131051	0.00342940812276493
-ENSG00000235444	0.505126429085709
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+ENSG00000203837	True
+ENSG00000118507	False
+ENSG00000184319	False
+ENSG00000130349	True
+ENSG00000100478	False
+ENSG00000185189	False
+ENSG00000113621	True
+ENSG00000238251	False
+ENSG00000198250	True
+ENSG00000232905	False
+ENSG00000206560	True
+ENSG00000225374	False
+ENSG00000236330	False
+ENSG00000136048	False
+ENSG00000146574	False
+ENSG00000129518	True
+ENSG00000111652	False
+ENSG00000136709	False
+ENSG00000159259	False
+ENSG00000205628	False
+ENSG00000236739	False
+ENSG00000118680	True
+ENSG00000174799	False
+ENSG00000227376	False
+ENSG00000079215	False
+ENSG00000224628	False
+ENSG00000197121	False
+ENSG00000151690	True
+ENSG00000230531	False
+ENSG00000126226	False
+ENSG00000074071	True
+ENSG00000100577	False
+ENSG00000086289	False
+ENSG00000205208	False
+ENSG00000134326	False
+ENSG00000157423	False
+ENSG00000239569	False
+ENSG00000164241	False
+ENSG00000161040	False
+ENSG00000174705	False
+ENSG00000197888	True
+ENSG00000141448	False
+ENSG00000181690	False
+ENSG00000166788	False
+ENSG00000101473	True
+ENSG00000204396	True
+ENSG00000168826	False
+ENSG00000155729	False
+ENSG00000142082	False
+ENSG00000143727	False
+ENSG00000203995	False
+ENSG00000165055	False
+ENSG00000213971	False
+ENSG00000224453	False
+ENSG00000108960	False
+ENSG00000183506	False
+ENSG00000099139	False
+ENSG00000111331	True
+ENSG00000133226	False
+ENSG00000217801	False
+ENSG00000130227	False
+ENSG00000164144	False
+ENSG00000128731	False
+ENSG00000079785	False
+ENSG00000106948	False
+ENSG00000115107	True
+ENSG00000236696	False
+ENSG00000198482	False
+ENSG00000173681	False
+ENSG00000204164	False
+ENSG00000228612	False
+ENSG00000003096	True
+ENSG00000180881	False
+ENSG00000205084	False
+ENSG00000159173	False
+ENSG00000197535	False
+ENSG00000223382	True
+ENSG00000183309	False
+ENSG00000215099	False
+ENSG00000116685	False
+ENSG00000181472	False
+ENSG00000132274	False
+ENSG00000145494	False
+ENSG00000122644	True
+ENSG00000157107	True
+ENSG00000145354	False
+ENSG00000158467	False
+ENSG00000164934	False
+ENSG00000134986	True
+ENSG00000121988	False
+ENSG00000178996	False
--- a/test-data/wal.tab	Thu Mar 03 09:56:51 2016 -0500
+++ b/test-data/wal.tab	Mon Mar 07 13:57:32 2016 -0500
@@ -1,3 +1,3 @@
-category	over_represented_pvalue	under_represented_pvalue	numDEInCat	numInCat	term	ontology
-GO:0000278	0.01123506125343	0.999376653834006	4	5	mitotic cell cycle	BP
-GO:0000003	1	0.805913166914891	0	1	reproduction	BP
+category	over_represented_pvalue	under_represented_pvalue	numDEInCat	numInCat	term	ontology	p.adjust.over_represented	p.adjust.under_represented
+GO:0000278	0.416311963944304	1	4	5	mitotic cell cycle	BP	0.832623927888609	1
+GO:0000003	1	0.416311963944305	0	1	reproduction	BP	1	0.83262392788861
--- a/tool_dependencies.xml	Thu Mar 03 09:56:51 2016 -0500
+++ b/tool_dependencies.xml	Mon Mar 07 13:57:32 2016 -0500
@@ -4,6 +4,6 @@
          <repository changeset_revision="9f31a291b305" name="package_r_3_2_1" owner="iuc" toolshed="https://testtoolshed.g2.bx.psu.edu" />
     </package>
     <package name="goseq" version="1.22.0">
-         <repository changeset_revision="6aec352282a6" name="package_r_3_2_1_goseq_1_22_0" owner="mvdbeek" toolshed="https://testtoolshed.g2.bx.psu.edu" />
+         <repository changeset_revision="4f43af0c6b44" name="package_r_3_2_1_goseq_1_22_0" owner="mvdbeek" toolshed="https://testtoolshed.g2.bx.psu.edu" />
     </package>
 </tool_dependency>