Mercurial > repos > workflow4metabolomics > camera_groupfwhm

annotate CAMERA_groupFWHM.R @ 0:6aea0427511e draft default tip

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planemo upload commit 24d44ee26b7c23380c2b42fae2f7f6e58472100d
author workflow4metabolomics
date Sun, 24 Nov 2024 21:28:57 +0000
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1 #!/usr/bin/env Rscript
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2
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3 # ----- PACKAGE -----
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4 cat("\tSESSION INFO\n")
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5
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6 # Import the different functions
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7 source_local <- function(fname) {
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8 argv <- commandArgs(trailingOnly = FALSE)
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9 base_dir <- dirname(substring(argv[grep("--file=", argv)], 8))
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10 source(paste(base_dir, fname, sep = "/"))
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11 }
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12 source_local("lib.r")
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13
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14 pkgs <- c("CAMERA", "xcms", "multtest", "batch")
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15 loadAndDisplayPackages(pkgs)
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16 cat("\n\n")
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17 # ----- ARGUMENTS -----
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18 cat("\tARGUMENTS INFO\n")
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19
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20 args <- parseCommandArgs(evaluate = FALSE) # interpretation of arguments given in command line as an R list of objects
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21 write.table(as.matrix(args), col.names = FALSE, quote = FALSE, sep = "\t")
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22
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23 cat("\n\n")
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24
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25 print("Arguments retrieved from the command line:")
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26 print(args)
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27
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28 # Function to convert "NA" strings to actual NA values and string lists to numeric lists
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29 convertStringToNumeric <- function(x) {
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30 # Force conversion to character
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31 x <- as.character(x)
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32
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33 if (x == "NA") {
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34 return(NA)
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35 } else if (grepl("^[0-9]+$", x)) {
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36 # If the string represents a single numeric value
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37 return(as.numeric(x))
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38 } else {
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39 # Convert string representation of a list to a numeric vector
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40 # Use a regular expression to split by common separators
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41 return(as.numeric(unlist(strsplit(x, "[,;\\s]+"))))
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42 }
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43 }
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44
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45 # Convert only the 'sample' element in args
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46 args$sample <- convertStringToNumeric(args$sample)
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47
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48 print("Argument types:")
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49 print(sapply(args, class))
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50
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51 # Check if the image file exists
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52 if (!file.exists(args$image)) {
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53 stop("The RData file does not exist: ", args$image)
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54 }
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55
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56 # ----- PROCESSING INFILE -----
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57
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58 # Load the RData file (it should contain the xset object, typically an xcmsSet or XCMSnExp)
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59 load(args$image)
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60 args$image <- NULL
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61
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62 # Save arguments to generate a report
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63 if (!exists("listOFlistArguments")) listOFlistArguments <- list()
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64 listOFlistArguments[[format(Sys.time(), "%y%m%d-%H:%M:%S_groupFWHM")]] <- args
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65
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66 # We unzip automatically the chromatograms from the zip files.
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67 if (!exists("zipfile")) zipfile <- NULL
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68 if (!exists("singlefile")) singlefile <- NULL
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69 rawFilePath <- getRawfilePathFromArguments(singlefile, zipfile, args)
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70 zipfile <- rawFilePath$zipfile
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71 singlefile <- rawFilePath$singlefile
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72 args <- rawFilePath$args
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73
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74 print(paste("singlefile :", singlefile))
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75 if (!is.null(singlefile)) {
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76 directory <- retrieveRawfileInTheWorkingDir(singlefile, zipfile)
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77 }
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78
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79 # If the xdata object exists, convert it to xcmsSet
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80 if (exists("xdata")) {
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81 phenoData <- xdata@phenoData
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82 xset <- getxcmsSetObject(xdata)
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83 }
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84
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85 if (!exists("xdata")) stop("\n\nERROR: The RData doesn't contain any object called 'xdata'. This RData should have been created by an old version of XMCS 2.*")
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86
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87 # Verification of a group step before doing the fillpeaks job.
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88 if (dim(xdata@phenoData@data)[1] > 1) {
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89 if (!hasFeatures(xdata)) stop("You must always do a group step after a retcor. Otherwise it won't work for the groupFWHM step")
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90 } else {
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91 print("Only one file in the phenoData keep xset as is")
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92 }
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93
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94 # Convert the xset object to xsAnnotate using CAMERA
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95 cat("Converting xset object to xsAnnotate...\n")
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96 xsa <- xsAnnotate(xset, sample = args$sample, nSlaves = as.numeric(args$nSlaves), polarity = args$polarity)
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97
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98 print(paste0("All samples in xset object: ", paste(seq_along(xset@filepaths), collapse = ", ")))
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99 print(paste0("Selected samples: ", paste(xsa@sample, collapse = ", ")))
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100 print(paste0("Run in parallel mode (0 = disabled): ", paste(xsa@runParallel)))
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101 print(paste0("Polarity: ", xsa@polarity))
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102
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103 # Apply the groupFWHM function with the parameters
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104 cat("Applying groupFWHM...\n")
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105 xa <- groupFWHM(xsa, sigma = as.numeric(args$sigma), perfwhm = as.numeric(args$perfwhm), intval = args$intval)
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106
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107 # Extract the list of annotated peaks
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108 peakList <- getPeaklist(xa, intval = args$intval)
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109
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110 if (length(phenoData@data$sample_name) == 1) {
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111 peakList$name <- make.unique(paste0("M", round(peakList[, "mz"], 0), "T", round(peakList[, "rt"], 0)), "_")
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112 variableMetadata <- peakList[, c("name", setdiff(names(peakList), "name"))]
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113 variableMetadata <- formatIonIdentifiers(variableMetadata, numDigitsRT = args$numDigitsRT, numDigitsMZ = args$numDigitsMZ)
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114 } else {
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115 names_default <- groupnames(xa@xcmsSet, mzdec = 0, rtdec = 0) # Names without decimals
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116 names_custom <- groupnames(xa@xcmsSet, mzdec = args$numDigitsMZ, rtdec = args$numDigitsRT) # Names with "x" decimals
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117
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118 variableMetadata <- data.frame(
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119 name = names_default,
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120 name_custom = names_custom,
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121 stringsAsFactors = FALSE
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122 )
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123 variableMetadata <- cbind(variableMetadata, peakList[, !(make.names(colnames(peakList)) %in% c(make.names(sampnames(xa@xcmsSet))))])
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124 }
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125
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126 if (!exists("RTinMinute")) RTinMinute <- FALSE
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127
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128 if (args$convertRTMinute && RTinMinute == FALSE) {
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129 RTinMinute <- TRUE
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130 variableMetadata <- RTSecondToMinute(variableMetadata = variableMetadata, convertRTMinute = args$convertRTMinute)
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131 }
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132
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133 # Save the peak list to a TSV file
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134 output_file_tsv <- "variableMetadata.tsv"
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135 write.table(variableMetadata, file = output_file_tsv, sep = "\t", row.names = FALSE, quote = FALSE)
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136
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137 # Save the xsAnnotate object
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138 output_file_RData <- "camera_fwhm.RData"
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139 objects2save <- c("xa", "variableMetadata", "listOFlistArguments", "zipfile", "singlefile", "RTinMinute", "phenoData")
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140 save(list = objects2save[objects2save %in% ls()], file = output_file_RData)
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141
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142 cat("Output files generated:", output_file_tsv, "and", output_file_RData, "\n")