comparison edgeR_Convert_DGE_Table_to_Bedgraph.xml @ 99:450c1c9a2938 draft

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99:450c1c9a2938

<?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,gff,gff3" 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 format="bedgraph" name="logfc" label="logFC from ${cpm_table.name}">
			<filter>"c3" in columns</filter>
		</data>
		
		<data format="bedgraph" name="logcpm" label="logCPM from ${cpm_table.name}">
			<filter>"c4" in columns</filter>
		</data>
		
		<data format="bedgraph" name="lr" label="LR from ${cpm_table.name}">
			<filter>"c5" in columns</filter>
		</data>
		
		<data format="bedgraph" name="pvalue" label="PValue from ${cpm_table.name}">
			<filter>"c6" in columns</filter>
		</data>
		
		<data format="bedgraph" name="fdr" label="FDR from ${cpm_table.name}">
			<filter>"c7" in columns</filter>
		</data>
	</outputs>
	
	<tests>
		<test>
			<param name="cpm_table" value="Convert_DGE_Table_to_Bedgraph/table_01.tabular.txt" />
			<param name="geneset" value="Convert_DGE_Table_to_Bedgraph/genes_01.gtf" />
			
			<param name="columns" value="c3,c7" />
			
			<output name="logfc" file="Convert_DGE_Table_to_Bedgraph/logFC.output.bedgraph" />
			<output name="fdr" file="Convert_DGE_Table_to_Bedgraph/FDR.output.bedgraph" />
		</test>
	</tests>
	
	<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>
	
	<citations>
		<citation type="doi">10.1093/bioinformatics/btp616</citation>
		<citation type="doi">10.1093/bioinformatics/btt688</citation>
	</citations>
</tool>