|
99
|
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 <requirements>
|
|
|
6 <requirement type="package" version="1.0.0">edger_dge_table_to_bedgraph</requirement>
|
|
|
7 </requirements>
|
|
|
8
|
|
|
9 <command interpreter="python">
|
|
|
10 edger_dge_table_to_bedgraph
|
|
|
11 -t $cpm_table
|
|
|
12 -g $geneset
|
|
|
13
|
|
|
14 #if $logfc:
|
|
|
15 -c3 $logfc
|
|
|
16 #end if
|
|
|
17
|
|
|
18 #if $logcpm:
|
|
|
19 -c4 $logcpm
|
|
|
20 #end if
|
|
|
21
|
|
|
22 #if $lr:
|
|
|
23 -c5 $lr
|
|
|
24 #end if
|
|
|
25
|
|
|
26 #if $pvalue:
|
|
|
27 -c6 $pvalue
|
|
|
28 #end if
|
|
|
29
|
|
|
30 #if $fdr:
|
|
|
31 -c7 $fdr
|
|
|
32 #end if
|
|
|
33 </command>
|
|
|
34
|
|
|
35 <inputs>
|
|
|
36 <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" />
|
|
|
37 <param format="gtf,gff,gff3" name="geneset" type="data" label="Geneset used for estimating expression levels prior to expression analysis" />
|
|
|
38
|
|
|
39 <param name="columns" type="select" label="Desired columns" multiple="true" display="checkboxes">
|
|
|
40 <option value="c3" selected="true">logFC</option>
|
|
|
41 <option value="c4">logCPM</option>
|
|
|
42 <option value="c5">LR</option>
|
|
|
43 <option value="c6">PValue</option>
|
|
|
44 <option value="c7" selected="true">FDR</option>
|
|
|
45 </param>
|
|
|
46 </inputs>
|
|
|
47
|
|
|
48 <outputs>
|
|
|
49 <data format="bedgraph" name="logfc" label="logFC from ${cpm_table.name}">
|
|
|
50 <filter>"c3" in columns</filter>
|
|
|
51 </data>
|
|
|
52
|
|
|
53 <data format="bedgraph" name="logcpm" label="logCPM from ${cpm_table.name}">
|
|
|
54 <filter>"c4" in columns</filter>
|
|
|
55 </data>
|
|
|
56
|
|
|
57 <data format="bedgraph" name="lr" label="LR from ${cpm_table.name}">
|
|
|
58 <filter>"c5" in columns</filter>
|
|
|
59 </data>
|
|
|
60
|
|
|
61 <data format="bedgraph" name="pvalue" label="PValue from ${cpm_table.name}">
|
|
|
62 <filter>"c6" in columns</filter>
|
|
|
63 </data>
|
|
|
64
|
|
|
65 <data format="bedgraph" name="fdr" label="FDR from ${cpm_table.name}">
|
|
|
66 <filter>"c7" in columns</filter>
|
|
|
67 </data>
|
|
|
68 </outputs>
|
|
|
69
|
|
|
70 <tests>
|
|
|
71 <test>
|
|
|
72 <param name="cpm_table" value="Convert_DGE_Table_to_Bedgraph/table_01.tabular.txt" />
|
|
|
73 <param name="geneset" value="Convert_DGE_Table_to_Bedgraph/genes_01.gtf" />
|
|
|
74
|
|
|
75 <param name="columns" value="c3,c7" />
|
|
|
76
|
|
|
77 <output name="logfc" file="Convert_DGE_Table_to_Bedgraph/logFC.output.bedgraph" />
|
|
|
78 <output name="fdr" file="Convert_DGE_Table_to_Bedgraph/FDR.output.bedgraph" />
|
|
|
79 </test>
|
|
|
80 </tests>
|
|
|
81
|
|
|
82 <help>
|
|
|
83 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.
|
|
|
84 </help>
|
|
|
85
|
|
|
86 <citations>
|
|
|
87 <citation type="doi">10.1093/bioinformatics/btp616</citation>
|
|
|
88 <citation type="doi">10.1093/bioinformatics/btt688</citation>
|
|
|
89 </citations>
|
|
|
90 </tool>
|
