<tool id="fishertest" name="Fisher's exact test" version="1.0.0">
	<description>on two gene hit lists</description>
        <requirements>
<!--            <requirement type="package" version="3.1.2">R</requirement> -->
            <requirement type="package" version="2.4.2=r3.3.1_0">bioconductor-qvalue</requirement>
        </requirements>
        <command><![CDATA[
            Rscript '$fisher_test' "\${GALAXY_SLOTS:-1}"
    ]]></command>
  <configfiles>
    <configfile name="fisher_test">
    <![CDATA[
      ## Setup R error handling to go to stderr
      options( show.error.messages=F,  error = function () { cat( geterrmessage(), file=stderr() ); q( "no", 1, F ) } )
      options(warn=-1)
      suppressMessages(library(qvalue))
      library(parallel)
      args = commandArgs(trailingOnly = TRUE)
      slots = as.numeric(args[1])
      countsTable = read.delim("${input}", header=TRUE, check.names=FALSE, stringsAsFactor = TRUE)
      depth1 = sum(countsTable[,2])
      depth2 = sum(countsTable[,3])
      float_table=data.frame(countsTable[,2], countsTable[,3])

      calc_pvalue <- function(row, depth1, depth2, ... ){
        thearray = array( c(row, (depth1 - row[1]), (depth2 - row[2])), dim=c(2,2))
        current_test = fisher.test( thearray )
        return(current_test\$p.value)
      }

      cl <- makePSOCKcluster(slots)
      clusterExport(cl=cl, varlist=c("calc_pvalue", "depth1", "depth2"))
      ptm <- proc.time()
      p_val = parApply(cl, float_table, 1, function(x) calc_pvalue(x, depth1, depth2))
      stopCluster(cl)
      proc.time() - ptm
      p_val[p_val>1]=1
      p = qvalue(p_val)
      finalTable = cbind(countsTable, data.frame(p\$pvalues), data.frame(p\$qvalues))
      write.table ( finalTable, file = "${output}", row.names=FALSE, col.names=TRUE, quote= FALSE, dec = ".", sep = "\t", eol = "\n")
    ]]>
    </configfile>
  </configfiles>
        <inputs>
                <param name="input" type="data" format="tabular" label="gene hit lists, 2 samples"/>
        </inputs>
        <outputs>
                <data name="output" format="tabular" label="Fisher test p-values" />
        </outputs>
<tests>
    <test>
        <param name="input" value="counts.tab" ftype="tabular"/>
        <output name="output" file="fisher.tab" ftype="tabular"/>
    </test>
</tests>
<help>

**What it does**

Runs Fisher's exact test for testing the null of independence of rows and columns in a contingency table of two columns.

p.pvalues: the chance of getting this data if it is independent between columns (false negative); the p-value.

q.qvalues: FDR (Faslse Detection Rate) adjusted p-values; a q-value of 0.05 implies that 5% of significant tests will result in false positives.

Be aware that this test does not take into account the biological noise that would be visible if replicates were available.


</help>
<citations>
    <citation type="doi">10.1111/1467-9868.00346</citation>
</citations>
    
</tool>