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annotate batch_correction_wrapper.R @ 0:78cb1efd7606 draft

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planemo upload for repository https://github.com/workflow4metabolomics/batch_correction.git commit 400138235741cbb21fd7c7ddeeb572235fa769c2-dirty
author ethevenot
date Thu, 30 Mar 2017 12:10:43 -0400
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78cb1efd7606 planemo upload for repository https://github.com/workflow4metabolomics/batch_correction.git commit 400138235741cbb21fd7c7ddeeb572235fa769c2-dirty
ethevenot
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1 #!/usr/bin/Rscript --vanilla --slave --no-site-file
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ethevenot
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3 ################################################################################################
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4 # batch_correction_wrapper #
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5 # #
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6 # Author: Marion LANDI / Jean-Francois MARTIN / Melanie Petera #
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7 # User: Galaxy #
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8 # Original data: -- #
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ethevenot
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9 # Starting date: 22-07-2014 #
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10 # Version 1: 22-07-2014 #
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11 # Version 2: 08-12-2014 #
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12 # Version 2.1: 09-01-2015 modification in Error message of sample matching #
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13 # Version 2.2: 16-03-2015 inclusion of miniTools' functions for special characters #
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14 # Version 2.90: 18-08-2015 new parameter valnull #
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15 # Version 2.91: 25-08-2016 error message improvment #
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16 # #
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17 # #
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18 # Input files: dataMatrix.txt ; sampleMetadata.txt ; variableMetadata.txt (for DBC) #
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19 # Output files: graph_output.pdf ; corrected table ; diagnostic table #
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20 # #
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21 ################################################################################################
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24 library(batch) #necessary for parseCommandArgs function
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25 args = parseCommandArgs(evaluate=FALSE) #interpretation of arguments given in command line as an R list of objects
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27 source_local <- function(...){
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28 argv <- commandArgs(trailingOnly = FALSE)
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29 base_dir <- dirname(substring(argv[grep("--file=", argv)], 8))
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30 for(i in 1:length(list(...))){source(paste(base_dir, list(...)[[i]], sep="/"))}
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31 }
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32 #Import the different functions
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33 source_local("Normalisation_QCpool.r","easyrlibrary-lib/RcheckLibrary.R","easyrlibrary-lib/miniTools.R")
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36 ## Reading of input files
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37 idsample=read.table(args$sampleMetadata,header=T,sep='\t',check.names=FALSE)
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38 iddata=read.table(args$dataMatrix,header=T,sep='\t',check.names=FALSE)
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39
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40 ### Table match check
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41 table.check <- match2(iddata,idsample,"sample")
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42 if(length(table.check)>1){check.err(table.check)}
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43
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44 ### StockID
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45 samp.id <- stockID(iddata,idsample,"sample")
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46 iddata<-samp.id$dataMatrix ; idsample<-samp.id$Metadata ; samp.id<-samp.id$id.match
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47
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48 ### Checking mandatory variables
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49 mand.check <- ""
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50 for(mandcol in c("sampleType","injectionOrder","batch")){
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51 if(!(mandcol%in%colnames(idsample))){
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52 mand.check <- c(mand.check,"\nError: no '",mandcol,"' column in sample metadata.\n",
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53 "Note: table must include this exact column name (it is case-sensitive).\n")
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54 }
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55 }
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56 if(length(mand.check)>1){
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57 mand.check <- c(mand.check,"\nFor more information, see the help section or:",
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58 "\n http://workflow4metabolomics.org/sites/",
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59 "workflow4metabolomics.org/files/files/w4e-2016-data_processing.pdf\n")
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60 check.err(mand.check)
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61 }
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62
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63 ### Formating
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64 idsample[[1]]=make.names(idsample[[1]])
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65 dimnames(iddata)[[1]]=iddata[[1]]
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66
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67 ### Transposition of ions data
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68 idTdata=t(iddata[,2:dim(iddata)[2]])
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69 idTdata=data.frame(dimnames(idTdata)[[1]],idTdata)
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70
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71 ### Merge of 2 files (ok even if the two dataframe are not sorted on the same key)
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72 id=merge(idsample, idTdata, by.x=1, by.y=1)
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74 id$batch=as.factor(id$batch)
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75 ids=id[id$sampleType == 'pool' | id$sampleType == 'sample',]
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76 nbid=dim(idsample)[2]
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78 ### Checking the number of sample and pool
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79
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80 # least 2 samples
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81 if(length(which(ids$sampleType == "sample"))<2){
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82 table.check <- c(table.check,"\nError: less than 2 samples specified in sample metadata.",
78cb1efd7606 planemo upload for repository https://github.com/workflow4metabolomics/batch_correction.git commit 400138235741cbb21fd7c7ddeeb572235fa769c2-dirty
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83 "\nMake sure this is not due to errors in sampleType coding.\n")
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84 }
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85
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86 # least 2 pools per batch for all batchs
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87 B <- rep(0,length(levels(ids$batch)))
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88 for(nbB in length(levels(ids$batch))){
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89 B[nbB]<-length(which(ids[which(ids$batch==(levels(ids$batch)[nbB])),]$sampleType == "pool"))
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90 }
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91 if(length(which(B>1))==0){
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92 table.check <- c(table.check,"\nError: less than 2 pools specified in each batch in sample metadata.",
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93 "\nMake sure this is not due to errors in sampleType coding.\n")
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94 }
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95
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96 ### Factor of interest
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97 factbio=args$ref_factor
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98
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99
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100 if(args$analyse == "batch_correction") {
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101 ## Reading of Metadata Ions file
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102 metaion=read.table(args$variableMetadata,header=T,sep='\t',check.names=FALSE)
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103 ## Table match check
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104 table.check <- c(table.check,match2(iddata,metaion,"variable"))
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105 check.err(table.check)
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106
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107 ## variables
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108 detail=args$detail
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109 method=args$method
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110
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111 ## outputs
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112 outlog=args$graph_output
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113
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114 ## Launch
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115 res = norm_QCpool(ids,nbid,outlog,factbio,metaion,detail,F,F,method,args$span,args$valnull)
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116 save(res, file=args$rdata_output)
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117 write.table(reproduceID(res[[1]],res[[3]],"sample",samp.id)$dataMatrix, file=args$dataMatrix_out, sep = '\t', row.names=F, quote=F)
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118 write.table(res[[2]], file=args$variableMetadata_out, sep = '\t', row.names=F, quote=F)
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119 }else{
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120 ## error check
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121 check.err(table.check)
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122
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123 ## outputs
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124 out_graph_pdf=args$out_graph_pdf
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125 out_preNormSummary=args$out_preNormSummary
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126
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127 ## Launch
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128 plotsituation(ids,nbid,out_graph_pdf,out_preNormSummary,factbio,args$span)
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129 }
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130
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131 rm(args)