Mercurial > repos > lecorguille > xcms_xcmsset

annotate xcms_xcmsSet.r @ 52:3d01d97f7335 draft default tip

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planemo upload for repository https://github.com/workflow4metabolomics/tools-metabolomics/ commit 95721ced8347c09e79340e6d67ecb41c5cc64163
author workflow4metabolomics
date Mon, 03 Feb 2025 14:41:55 +0000
parents 44ab040fffa0
children
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2bf1cb023c94 planemo upload for repository https://github.com/workflow4metabolomics/xcms commit e384d6dd5f410799ec211f73bca0b5d5d7bc651e
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1 #!/usr/bin/env Rscript
2bf1cb023c94 planemo upload for repository https://github.com/workflow4metabolomics/xcms commit e384d6dd5f410799ec211f73bca0b5d5d7bc651e
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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)
3d01d97f7335 planemo upload for repository https://github.com/workflow4metabolomics/tools-metabolomics/ commit 95721ced8347c09e79340e6d67ecb41c5cc64163
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15 base_dir <- dirname(substring(argv[grep("--file=", argv)], 8))
3d01d97f7335 planemo upload for repository https://github.com/workflow4metabolomics/tools-metabolomics/ commit 95721ced8347c09e79340e6d67ecb41c5cc64163
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16 source(paste(base_dir, fname, sep = "/"))
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17 }
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18 source_local("lib.r")
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20 pkgs <- c("xcms", "batch")
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21 loadAndDisplayPackages(pkgs)
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22 cat("\n\n")
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25 # ----- ARGUMENTS -----
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26 cat("\tARGUMENTS INFO\n")
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27 args <- parseCommandArgs(evaluate = FALSE) # interpretation of arguments given in command line as an R list of objects
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28 write.table(as.matrix(args), col.names = FALSE, quote = FALSE, sep = "\t")
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30 cat("\n\n")
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33 # ----- PROCESSING INFILE -----
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34 cat("\tARGUMENTS PROCESSING INFO\n")
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36 # saving the commun parameters
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37 BPPARAM <- MulticoreParam(1)
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38 if (!is.null(args$BPPARAM)) {
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39 BPPARAM <- MulticoreParam(args$BPPARAM)
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40 }
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41 register(BPPARAM)
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43 # saving the specific parameters
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44 if (!is.null(args$filterAcquisitionNum)) filterAcquisitionNumParam <- args$filterAcquisitionNum
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45 if (!is.null(args$filterRt)) filterRtParam <- args$filterRt
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46 if (!is.null(args$filterMz)) filterMzParam <- args$filterMz
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47 if (!is.null(args$peaklist)) peaklistParam <- args$peaklist
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49 method <- args$method
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51 if (!is.null(args$roiList)) {
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52 cat("\t\troiList provided\n")
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53 args$roiList <- list(getDataFrameFromFile(args$roiList))
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54 print(args$roiList)
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55 }
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57 cat("\n\n")
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59 # ----- INFILE PROCESSING -----
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60 cat("\tINFILE PROCESSING INFO\n")
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61
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62 # image is an .RData file necessary to use xset variable given by previous tools
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63 load(args$image)
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64 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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65
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66 # Handle infiles
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67 rawFilePath <- retrieveRawfileInTheWorkingDir(singlefile, zipfile, args)
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68 zipfile <- rawFilePath$zipfile
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69 singlefile <- rawFilePath$singlefile
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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 cat("\t\t\tApply filter[s] (if asked)\n")
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82 if (exists("filterAcquisitionNumParam")) raw_data <- filterAcquisitionNum(raw_data, filterAcquisitionNumParam[1]:filterAcquisitionNumParam[2])
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83 if (exists("filterRtParam")) raw_data <- filterRt(raw_data, filterRtParam)
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84 if (exists("filterMzParam")) raw_data <- filterMz(raw_data, filterMzParam)
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85 # Apply this filter only if file contain MS and MSn
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86 if (length(unique(msLevel(raw_data))) != 1) {
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87 raw_data <- filterMsLevel(raw_data, msLevel = 1)
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88 }
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89
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90 cat("\t\t\tChromatographic peak detection\n")
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91 # clear the arguement list to remove unexpected key/value as singlefile_galaxyPath or method ...
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92 args <- args[names(args) %in% slotNames(do.call(paste0(method, "Param"), list()))]
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93
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94 findChromPeaksParam <- do.call(paste0(method, "Param"), args)
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95 print(findChromPeaksParam)
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96 xdata <- findChromPeaks(raw_data, param = findChromPeaksParam)
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97
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98 # Check if there are no peaks
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99 if (nrow(chromPeaks(xdata)) == 0) stop("No peaks were detected. You should review your settings")
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101 # Create a sampleMetada file
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102 sampleNamesList <- getSampleMetadata(xdata = xdata, sampleMetadataOutput = "sampleMetadata.tsv")
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103
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104 # Create a chromPeaks table if required
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105 if (exists("peaklistParam")) {
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106 if (peaklistParam) {
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107 cat("\nCreating the chromatographic peaks' table...\n")
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108 write.table(chromPeaks(xdata), file = "chromPeak_table.tsv", sep = "\t", quote = FALSE, row.names = FALSE)
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109 }
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110 }
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111
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112 cat("\n\n")
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113
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114 # ----- EXPORT -----
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115
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116 cat("\tXCMSnExp OBJECT INFO\n")
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117 print(xdata)
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118 cat("\n\n")
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119
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120 cat("\txcmsSet OBJECT INFO\n")
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121 # Get the legacy xcmsSet object
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122 xset <- getxcmsSetObject(xdata)
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123 print(xset)
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124 cat("\n\n")
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125
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126 # saving R data in .Rdata file to save the variables used in the present tool
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127 objects2save <- c("xdata", "zipfile", "singlefile", "md5sumList", "sampleNamesList")
1c63d9d402e6 "planemo upload for repository https://github.com/workflow4metabolomics/xcms commit dcc90f9cf76e6980c0a7d9698c89fab826e7adae"
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128 save(list = objects2save[objects2save %in% ls()], file = "xcmsSet.RData")
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131 cat("\tDONE\n")