Mercurial > repos > lecorguille > xcms_xcmsset

annotate xcms_xcmsSet.r @ 32:b02d1992a43a draft

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"planemo upload for repository https://github.com/workflow4metabolomics/xcms commit dcc90f9cf76e6980c0a7d9698c89fab826e7adae"
author workflow4metabolomics
date Wed, 07 Apr 2021 16:47:14 +0000
parents eb15a3841da4
children f5d51091cf84
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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) {
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14 argv <- commandArgs(trailingOnly = FALSE); base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)); source(paste(base_dir, fname, sep = "/"))
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15 }
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16 source_local("lib.r")
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18 pkgs <- c("xcms", "batch")
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19 loadAndDisplayPackages(pkgs)
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20 cat("\n\n");
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23 # ----- ARGUMENTS -----
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24 cat("\tARGUMENTS INFO\n")
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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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26 write.table(as.matrix(args), col.names = F, quote = F, sep = "\t")
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28 cat("\n\n")
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31 # ----- PROCESSING INFILE -----
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32 cat("\tARGUMENTS PROCESSING INFO\n")
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34 #saving the commun parameters
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35 BPPARAM <- MulticoreParam(1)
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36 if (!is.null(args$BPPARAM)) {
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37 BPPARAM <- MulticoreParam(args$BPPARAM)
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38 }
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39 register(BPPARAM)
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41 #saving the specific parameters
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42 if (!is.null(args$filterAcquisitionNum)) filterAcquisitionNumParam <- args$filterAcquisitionNum
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43 if (!is.null(args$filterRt)) filterRtParam <- args$filterRt
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44 if (!is.null(args$filterMz)) filterMzParam <- args$filterMz
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45 if (!is.null(args$peaklist)) peaklistParam <- args$peaklist
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47 method <- args$method
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49 if (!is.null(args$roiList)) {
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50 cat("\t\troiList provided\n")
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51 args$roiList <- list(getDataFrameFromFile(args$roiList))
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52 print(args$roiList)
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53 }
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55 cat("\n\n")
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57 # ----- INFILE PROCESSING -----
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58 cat("\tINFILE PROCESSING INFO\n")
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60 #image is an .RData file necessary to use xset variable given by previous tools
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61 load(args$image)
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62 if (!exists("raw_data")) stop("\n\nERROR: The RData doesn't contain any object called 'raw_data' which is provided by the tool: MSnbase readMSData")
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64 # Handle infiles
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65 rawFilePath <- retrieveRawfileInTheWorkingDir(singlefile, zipfile, args)
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66 zipfile <- rawFilePath$zipfile
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67 singlefile <- rawFilePath$singlefile
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70 cat("\n\n")
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73 # ----- MAIN PROCESSING INFO -----
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74 cat("\tMAIN PROCESSING INFO\n")
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77 cat("\t\tCOMPUTE\n")
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79 cat("\t\t\tApply filter[s] (if asked)\n")
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80 if (exists("filterAcquisitionNumParam")) raw_data <- filterAcquisitionNum(raw_data, filterAcquisitionNumParam[1]:filterAcquisitionNumParam[2])
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81 if (exists("filterRtParam")) raw_data <- filterRt(raw_data, filterRtParam)
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82 if (exists("filterMzParam")) raw_data <- filterMz(raw_data, filterMzParam)
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83 #Apply this filter only if file contain MS and MSn
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84 if (length(unique(msLevel(raw_data))) != 1) {
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85 raw_data <- filterMsLevel(raw_data, msLevel = 1)
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86 }
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88 cat("\t\t\tChromatographic peak detection\n")
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89 # clear the arguement list to remove unexpected key/value as singlefile_galaxyPath or method ...
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90 args <- args[names(args) %in% slotNames(do.call(paste0(method, "Param"), list()))]
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91
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92 findChromPeaksParam <- do.call(paste0(method, "Param"), args)
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93 print(findChromPeaksParam)
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94 xdata <- findChromPeaks(raw_data, param = findChromPeaksParam)
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96 # Check if there are no peaks
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97 if (nrow(chromPeaks(xdata)) == 0) stop("No peaks were detected. You should review your settings")
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98
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99 # Create a sampleMetada file
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100 sampleNamesList <- getSampleMetadata(xdata = xdata, sampleMetadataOutput = "sampleMetadata.tsv")
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101
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102 # Create a chromPeaks table if required
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103 if (exists("peaklistParam")) {
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104 if (peaklistParam) {
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105 cat("\nCreating the chromatographic peaks' table...\n")
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106 write.table(chromPeaks(xdata), file = "chromPeak_table.tsv", sep = "\t", quote = F, row.names = F)
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107 }
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108 }
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109
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110 cat("\n\n")
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111
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112 # ----- EXPORT -----
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113
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114 cat("\tXCMSnExp OBJECT INFO\n")
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115 print(xdata)
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116 cat("\n\n")
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117
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118 cat("\txcmsSet OBJECT INFO\n")
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119 # Get the legacy xcmsSet object
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120 xset <- getxcmsSetObject(xdata)
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121 print(xset)
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122 cat("\n\n")
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123
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124 #saving R data in .Rdata file to save the variables used in the present tool
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125 objects2save <- c("xdata", "zipfile", "singlefile", "md5sumList", "sampleNamesList")
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126 save(list = objects2save[objects2save %in% ls()], file = "xcmsSet.RData")
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127
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128
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129 cat("\tDONE\n")