Mercurial > repos > yhoogstrate > edger_with_design_matrix

comparison edgeR_Convert_DGE_Table_to_Bedgraph.xml @ 1:a4a4c88783ea draft

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planemo upload for repository https://bitbucket.org/EMCbioinf/galaxy-tool-shed-tools/raw/master/edger_with_design_matrix commit 2700e500a4fb135a20ede7d52221a9d31f1aaa5e-dirty
author yhoogstrate
date Tue, 01 Sep 2015 04:59:05 -0400
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0:acb56603b268 1:a4a4c88783ea
1 <?xml version="1.0" encoding="UTF-8"?>
2 <tool id="edger_dge_table_to_bedgraph" name="edgeR: Convert 'differentially expressed genes'-table to bedgraph(s)" version="1.0.0">
3 <description>EdgeR's "differentially expressed genes" table to bedgraph(s)</description>
4
5 <macros>
6 <import>edgeR_macros.xml</import>
7 </macros>
8
9 <requirements>
10 <requirement type="package" version="1.0.0">edger_dge_table_to_bedgraph</requirement>
11 </requirements>
12
13 <command interpreter="python">
14 edger_dge_table_to_bedgraph
15 -t $cpm_table
16 -g $geneset
17
18 #if $logfc:
19 -c3 $logfc
20 #end if
21
22 #if $logcpm:
23 -c4 $logcpm
24 #end if
25
26 #if $lr:
27 -c5 $lr
28 #end if
29
30 #if $pvalue:
31 -c6 $pvalue
32 #end if
33
34 #if $fdr:
35 -c7 $fdr
36 #end if
37 </command>
38
39 <inputs>
40 <param format="tabular" name="cpm_table" type="data" label="'differentially expressed genes'-table as result from EdgeR" help="must have 7 columns of which the 2nd are gene names matching the GTF file" />
41 <param format="gtf,gff,gff3" name="geneset" type="data" label="Geneset used for estimating expression levels prior to expression analysis" />
42
43 <param name="columns" type="select" label="Desired columns" multiple="true" display="checkboxes">
44 <option value="c3" selected="true">logFC</option>
45 <option value="c4">logCPM</option>
46 <option value="c5">LR</option>
47 <option value="c6">PValue</option>
48 <option value="c7" selected="true">FDR</option>
49 </param>
50 </inputs>
51
52 <outputs>
53 <data format="bedgraph" name="logfc" label="logFC from ${cpm_table.name}">
54 <filter>"c3" in columns</filter>
55 </data>
56
57 <data format="bedgraph" name="logcpm" label="logCPM from ${cpm_table.name}">
58 <filter>"c4" in columns</filter>
59 </data>
60
61 <data format="bedgraph" name="lr" label="LR from ${cpm_table.name}">
62 <filter>"c5" in columns</filter>
63 </data>
64
65 <data format="bedgraph" name="pvalue" label="PValue from ${cpm_table.name}">
66 <filter>"c6" in columns</filter>
67 </data>
68
69 <data format="bedgraph" name="fdr" label="FDR from ${cpm_table.name}">
70 <filter>"c7" in columns</filter>
71 </data>
72 </outputs>
73
74 <tests>
75 <test>
76 <param name="cpm_table" value="Convert_DGE_Table_to_Bedgraph/table_01.tabular.txt" />
77 <param name="geneset" value="Convert_DGE_Table_to_Bedgraph/genes_01.gtf" />
78
79 <param name="columns" value="c3,c7" />
80
81 <output name="logfc" file="Convert_DGE_Table_to_Bedgraph/logFC.output.bedgraph" />
82 <output name="fdr" file="Convert_DGE_Table_to_Bedgraph/FDR.output.bedgraph" />
83 </test>
84 </tests>
85
86 <help>
87 P-values and FDRs are swapped from 1 to 0, and 0 to 1, because this way the most siginificant genes will obtain the highest values which is convenient for visualisation.
88
89 @CONTACT@
90 </help>
91
92 <expand macro="citations" />
93 </tool>