annotate xcms_xcmsSet.r @ 33:c363b9f1caef draft

planemo upload for repository https://github.com/workflow4metabolomics/xcms commit 7b226c3ba91a3cf654ec1c14b3ef85090968bb0f
author lecorguille
date Mon, 05 Mar 2018 04:15:34 -0500
parents 2bf1cb023c94
children efd23113d5f4
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1 #!/usr/bin/env Rscript
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3 # ----- LOG FILE -----
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4 log_file <- file("log.txt", open="wt")
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5 sink(log_file)
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6 sink(log_file, type = "output")
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9 # ----- PACKAGE -----
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10 cat("\tSESSION INFO\n")
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12 #Import the different functions
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13 source_local <- function(fname){ argv <- commandArgs(trailingOnly=FALSE); base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)); source(paste(base_dir, fname, sep="/")) }
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14 source_local("lib.r")
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16 pkgs <- c("xcms","batch")
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17 loadAndDisplayPackages(pkgs)
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18 cat("\n\n");
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21 # ----- ARGUMENTS -----
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22 cat("\tARGUMENTS INFO\n")
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23 args <- parseCommandArgs(evaluate = FALSE) #interpretation of arguments given in command line as an R list of objects
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24 write.table(as.matrix(args), col.names=F, quote=F, sep='\t')
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26 cat("\n\n")
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29 # ----- PROCESSING INFILE -----
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30 cat("\tARGUMENTS PROCESSING INFO\n")
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32 #saving the commun parameters
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33 BPPARAM <- MulticoreParam(1)
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34 if (!is.null(args$BPPARAM)){
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35 BPPARAM <- MulticoreParam(args$BPPARAM); args$BPPARAM <- NULL
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36 }
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37 register(BPPARAM)
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39 #saving the specific parameters
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40 if (!is.null(args$filterAcquisitionNum)){
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41 filterAcquisitionNumParam <- args$filterAcquisitionNum; args$filterAcquisitionNum <- NULL
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42 }
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43 if (!is.null(args$filterRt)){
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44 filterRtParam <- args$filterRt; args$filterRt <- NULL
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45 }
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46 if (!is.null(args$filterMz)){
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47 filterMzParam <- args$filterMz; args$filterMz <- NULL
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48 }
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49
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50 method <- args$method; args$method <- NULL
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52 cat("\n\n")
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54 # ----- INFILE PROCESSING -----
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55 cat("\tINFILE PROCESSING INFO\n")
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57 # Handle infiles
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58 if (!exists("singlefile")) singlefile <- NULL
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59 if (!exists("zipfile")) zipfile <- NULL
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60 rawFilePath <- getRawfilePathFromArguments(singlefile, zipfile, args)
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61 zipfile <- rawFilePath$zipfile
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62 singlefile <- rawFilePath$singlefile
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63 args <- rawFilePath$args
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64 directory <- retrieveRawfileInTheWorkingDirectory(singlefile, zipfile)
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66 # Check some character issues
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67 md5sumList <- list("origin" = getMd5sum(directory))
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68 checkXmlStructure(directory)
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69 checkFilesCompatibilityWithXcms(directory)
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72 cat("\n\n")
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75 # ----- MAIN PROCESSING INFO -----
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76 cat("\tMAIN PROCESSING INFO\n")
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79 cat("\t\tCOMPUTE\n")
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81 ## Get the full path to the files
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82 files <- getMSFiles(directory)
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83
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84 cat("\t\t\tCreate a phenodata data.frame\n")
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85 s_groups <- sapply(files, function(x) tail(unlist(strsplit(dirname(x),"/")), n=1))
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86 s_name <- tools::file_path_sans_ext(basename(files))
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87 pd <- data.frame(sample_name=s_name, sample_group=s_groups, stringsAsFactors=FALSE)
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88 print(pd)
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89
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90 cat("\t\t\tLoad Raw Data\n")
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91 raw_data <- readMSData(files=files, pdata = new("NAnnotatedDataFrame", pd), mode="onDisk")
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92
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93 cat("\t\t\tApply filter[s] (if asked)\n")
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94 if (exists("filterAcquisitionNumParam")) {
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95 raw_data <- filterAcquisitionNum(raw_data, filterAcquisitionNumParam[1]:filterAcquisitionNumParam[2])
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96 }
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97 if (exists("filterRtParam")) {
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98 raw_data <- filterRt(raw_data, filterRtParam)
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99 }
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100 if (exists("filterMzParam")) {
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101 raw_data <- filterMz(raw_data, filterMzParam)
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102 }
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103
32
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104 cat("\t\t\tChromatographic peak detection\n")
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105 findChromPeaksParam <- do.call(paste0(method,"Param"), args)
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106 print(findChromPeaksParam)
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107 xdata <- findChromPeaks(raw_data, param=findChromPeaksParam)
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108
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109 # Check if there are no peaks
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110 if (nrow(chromPeaks(xdata)) == 0) stop("No peaks were detected. You should review your settings")
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111
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112 # Transform the files absolute pathways into relative pathways
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113 xdata@processingData@files <- sub(paste(getwd(), "/", sep="") , "", xdata@processingData@files)
33
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114
32
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115 # Create a sampleMetada file
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116 sampleNamesList <- getSampleMetadata(xdata=xdata, sampleMetadataOutput="sampleMetadata.tsv")
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117
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118 # Get the legacy xcmsSet object
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119 xset <- getxcmsSetObject(xdata)
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120
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121 cat("\n\n")
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122
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123
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124 # -- TIC --
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125 cat("\t\tGET TIC GRAPH\n")
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126 #@TODO: one day, use xdata instead of xset to draw the TICs and BPC or a complete other method
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127 getTICs(xcmsSet=xset, rt="raw", pdfname="TICs.pdf")
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128 getBPCs(xcmsSet=xset, rt="raw", pdfname="BICs.pdf")
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129
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130 cat("\n\n")
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131
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132 # ----- EXPORT -----
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133
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134 cat("\tXCMSnExp OBJECT INFO\n")
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135 print(xdata)
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136 cat("\n\n")
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137
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138 cat("\txcmsSet OBJECT INFO\n")
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139 print(xset)
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140 cat("\n\n")
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141
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142 #saving R data in .Rdata file to save the variables used in the present tool
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143 objects2save <- c("xdata", "zipfile", "singlefile", "md5sumList", "sampleNamesList")
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144 save(list=objects2save[objects2save %in% ls()], file="xcmsSet.RData")
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145
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146
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147 cat("\tDONE\n")