Mercurial > repos > yhoogstrate > edger_with_design_matrix

<?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>
author	yhoogstrate
date	Fri, 13 Mar 2015 05:45:09 -0400
parents
children	31335aa52b2e