Mercurial > repos > mvdbeek > deseq2
diff deseq2.xml @ 0:a903407e3ca0 draft default tip
planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/deseq2 commit f95b47ed1a09ce14d3b565e8ea56d8bf12c35814-dirty
author | mvdbeek |
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date | Sat, 05 Mar 2016 07:05:06 -0500 |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/deseq2.xml Sat Mar 05 07:05:06 2016 -0500 @@ -0,0 +1,56 @@ +<tool id="DESeq2" name="DESeq2 Profiling" version="1.0.2" hidden="true"> + <description>of readcount lists</description> + <requirements> + <requirement type="package" version="3.1.2">R</requirement> + <requirement type="package" version="2.14">biocbasics</requirement> + </requirements> + <command>Rscript $DESeq2 </command> + <inputs> + <param name="input" type="data" format="tabular" label="miR hit lists, more thant 2 samples"/> + <param name="expPlan" type="text" label="experimental plan" help="Use a string of Cs and Ts. exemple: CCCTTT means 3 control samples versus 3 test samples"/> + </inputs> + <outputs> + <data name="output" format="tabular" label="DESeq2 differential calling" /> + </outputs> + <tests> + <test> + <param name="input" value="counts.tab" ftype="tabular"/> + <param name="expPlan" value="CCTTT"/> + <output name="output" file="dge.tab.re_match.modified" ftype="tabular" compare="re_match" lines_diff="50"/> + </test> + </tests> +<configfiles> + <configfile name="DESeq2"> + ## Setup R error handling to go to stderr + options( show.error.messages=F, error = function () { cat( geterrmessage(), file=stderr() ); q( "no", 1, F ) } ) + suppressMessages(require(DESeq2)) + ## suppressMessages(require(ReportingTools)) + countData = read.delim("${input}", header=TRUE, check.names=FALSE) + rownames( countData )= countData[,1] + countData= countData[ , -1 ] + stringconds = "${expPlan}" + conds = unlist(strsplit(stringconds, split="")) + colData=data.frame(row.names=colnames(countData), condition=conds) + dds = DESeqDataSetFromMatrix(countData = countData, colData = colData, design = ~ condition) + colData(dds)\$condition = factor(colData(dds)\$condition, levels=c("C","T")) + dds = DESeq(dds, quiet=TRUE) + res = results(dds) + res = res[order(res\$padj),] + baseMeanA = rowMeans(counts(dds, normalized=TRUE)[rownames(res),colData(dds)\$condition== "C"]) + baseMeanB = rowMeans(counts(dds, normalized=TRUE)[rownames(res),colData(dds)\$condition== "T"]) + res2 = data.frame (gene=rownames(res), baseMeanA=baseMeanA, baseMeanB=baseMeanB, res) + ## resNA = res[-which(is.na(res[,8])),] ## omit the NA lignes + write.table ( res2, file = "${output}", row.names=FALSE, col.names=TRUE, quote= FALSE, dec = ".", sep = "\t", eol = "\n") + ## write.csv(as.data.frame(res), file="${output}") + </configfile> + </configfiles> + <help> + +**What it does** + +DESeq2 differential calling (order by padj, ascending). +Still in development and testing for replicates/no replicates + + + </help> +</tool>