diff edgeR_Convert_DGE_Table_to_Bedgraph.xml @ 92:86c3aaa205b5 draft

Added bedgraph exporting function for the DGE tables

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/edgeR_Convert_DGE_Table_to_Bedgraph.xml	Fri Mar 13 05:45:09 2015 -0400
@@ -0,0 +1,73 @@
+<?xml version="1.0" encoding="UTF-8"?>
+	<tool id="edger_dge_table_to_bedgraph" name="edgeR: convert 'differentially expressed genes'-table to bedgraph(s)" version="1.0.0">
+	<description>EdgeR's "differentially expressed genes" table to bedgraph(s)</description>
+	
+	<requirements>
+		<requirement type="package" version="1.0.0">edger_dge_table_to_bedgraph</requirement>
+	</requirements>
+	
+	<command interpreter="python">
+		edger_dge_table_to_bedgraph
+			-t $cpm_table
+			-g $geneset
+			
+			#if $logfc:
+				-c3 $logfc
+			#end if
+			
+			#if $logcpm:
+				-c4 $logcpm
+			#end if
+			
+			#if $lr:
+				-c5 $lr
+			#end if
+			
+			#if $pvalue:
+				-c6 $pvalue
+			#end if
+			
+			#if $fdr:
+				-c7 $fdr
+			#end if
+	</command>
+	
+	<inputs>
+		<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" />
+		<param format="gtf" name="geneset" type="data" label="Geneset used for estimating expression levels prior to expression analysis" />
+	
+		<param name="columns" type="select" label="Desired columns" multiple="true" display="checkboxes">
+			<option value="c3" selected="true">logFC</option>
+			<option value="c4">logCPM</option>
+			<option value="c5">LR</option>
+			<option value="c6">PValue</option>
+			<option value="c7" selected="true">FDR</option>
+		</param>
+	</inputs>
+	
+	<outputs>
+		<data fromat="bedgraph" name="logfc" label="logFC from ${cpm_table.name}">
+			<filter>"c3" in columns</filter>
+		</data>
+		
+		<data fromat="bedgraph" name="logcpm" label="logCPM from ${cpm_table.name}">
+			<filter>"c4" in columns</filter>
+		</data>
+		
+		<data fromat="bedgraph" name="lr" label="LR from ${cpm_table.name}">
+			<filter>"c5" in columns</filter>
+		</data>
+		
+		<data fromat="bedgraph" name="pvalue" label="PValue from ${cpm_table.name}">
+			<filter>"c6" in columns</filter>
+		</data>
+		
+		<data fromat="bedgraph" name="fdr" label="FDR from ${cpm_table.name}">
+			<filter>"c7" in columns</filter>
+		</data>
+	</outputs>
+	
+	<help>
+		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.
+	</help>
+</tool>
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