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annotate fisher_test.xml @ 0:8cb991523c5a draft default tip

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planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/fisher_test commit f9c229fc39114e80cf01383d7240e4971b2e3c53
author drosofff
date Thu, 09 Mar 2017 12:31:03 -0500
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8cb991523c5a planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/fisher_test commit f9c229fc39114e80cf01383d7240e4971b2e3c53
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1 <tool id="fishertest" name="Fisher's exact test" version="0.9.0">
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2 <description>on two gene hit lists</description>
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3 <requirements>
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4 <requirement type="package" version="3.1.2">R</requirement>
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5 <requirement type="package" version="2.14">biocbasics</requirement>
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6 <requirement type="package" version="2.4.2=r3.3.1_0">bioconductor-qvalue</requirement>
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7 </requirements>
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8 <command><![CDATA[
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9 Rscript '$fisher_test' "\${GALAXY_SLOTS:-1}"
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10 ]]></command>
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11 <configfiles>
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12 <configfile name="fisher_test">
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13 <![CDATA[
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14 ## Setup R error handling to go to stderr
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15 options( show.error.messages=F, error = function () { cat( geterrmessage(), file=stderr() ); q( "no", 1, F ) } )
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16 options(warn=-1)
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17 suppressMessages(library(qvalue))
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18 library(parallel)
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19 args = commandArgs(trailingOnly = TRUE)
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20 slots = as.numeric(args[1])
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21 countsTable = read.delim("${input}", header=TRUE, check.names=FALSE, stringsAsFactor = TRUE)
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22 depth1 = sum(countsTable[,2])
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23 depth2 = sum(countsTable[,3])
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24 float_table=data.frame(countsTable[,2], countsTable[,3])
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25
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26 calc_pvalue <- function(row, depth1, depth2, ... ){
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27 thearray = array( c(row, (depth1 - row[1]), (depth2 - row[2])), dim=c(2,2))
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28 current_test = fisher.test( thearray )
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29 return(current_test\$p.value)
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30 }
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31
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32 cl <- makePSOCKcluster(slots)
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33 clusterExport(cl=cl, varlist=c("calc_pvalue", "depth1", "depth2"))
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34 ptm <- proc.time()
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35 p_val = parApply(cl, float_table, 1, function(x) calc_pvalue(x, depth1, depth2))
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36 stopCluster(cl)
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37 proc.time() - ptm
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38 p_val[p_val>1]=1
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39 p = qvalue(p_val)
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40 finalTable = cbind(countsTable, data.frame(p\$pvalues), data.frame(p\$qvalues))
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41 write.table ( finalTable, file = "${output}", row.names=FALSE, col.names=TRUE, quote= FALSE, dec = ".", sep = "\t", eol = "\n")
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42 ]]>
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43 </configfile>
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44 </configfiles>
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45 <inputs>
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46 <param name="input" type="data" format="tabular" label="gene hit lists, 2 samples"/>
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47 </inputs>
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48 <outputs>
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49 <data name="output" format="tabular" label="Fisher test p-values" />
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50 </outputs>
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51 <tests>
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52 <test>
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53 <param name="input" value="counts.tab" ftype="tabular"/>
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54 <output name="output" file="fisher.tab" ftype="tabular"/>
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55 </test>
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56 </tests>
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57 <help>
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58
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59 **What it does**
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60
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61 Runs Fisher's exact test for testing the null of independence of rows and columns in a contingency table of two columns.
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62
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63 p.pvalues: the chance of getting this data if it is independent between columns (false negative); the p-value.
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64
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65 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.
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66
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67 Be aware that this test does not take into account the biological noise that would be visible if replicates were available.
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68
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69
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70 </help>
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71 <citations>
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72 <citation type="doi">10.1111/1467-9868.00346</citation>
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73 </citations>
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74
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75 </tool>