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annotate msnbase_readmsdata.r @ 18:35b6fe4d481c 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 14:49:24 +0000
parents 7faf9b2d83f6
children
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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)
35b6fe4d481c 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))
35b6fe4d481c 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("MSnbase", "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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37 cat("\n\n")
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39 # ----- INFILE PROCESSING -----
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40 cat("\tINFILE PROCESSING INFO\n")
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42 # Handle infiles
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43 if (!exists("singlefile")) singlefile <- NULL
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44 if (!exists("zipfile")) zipfile <- NULL
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45 rawFilePath <- retrieveRawfileInTheWorkingDir(singlefile, zipfile, args)
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46 zipfile <- rawFilePath$zipfile
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47 singlefile <- rawFilePath$singlefile
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48 files <- rawFilePath$files
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50 md5sumList <- list("origin" = getMd5sum(files))
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52 cat("\n\n")
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55 # ----- MAIN PROCESSING INFO -----
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56 cat("\tMAIN PROCESSING INFO\n")
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59 cat("\t\tCOMPUTE\n")
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61 cat("\t\t\tCreate a phenodata data.frame\n")
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62 s_groups <- sapply(files, function(x) tail(unlist(strsplit(dirname(x), "/")), n = 1))
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63 s_name <- tools::file_path_sans_ext(basename(files))
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64 pd <- data.frame(sample_name = s_name, sample_group = s_groups, stringsAsFactors = FALSE)
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65 print(pd)
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67 cat("\t\t\tLoad Raw Data\n")
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68 raw_data <- readMSData(files = files, pdata = new("NAnnotatedDataFrame", pd), mode = "onDisk")
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70 # Transform the files absolute pathways into relative pathways
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71 raw_data@processingData@files <- sub(paste(getwd(), "/", sep = ""), "", raw_data@processingData@files)
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73 # Create a sampleMetada file
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74 sampleNamesList <- getSampleMetadata(xdata = raw_data, sampleMetadataOutput = "sampleMetadata.tsv")
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76 cat("\n\n")
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78 # ----- EXPORT -----
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80 cat("\tMSnExp OBJECT INFO\n")
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81 print(raw_data)
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82 cat("\t\tphenoData\n")
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83 print(raw_data@phenoData@data)
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84 cat("\n\n")
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85
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86 # saving R data in .Rdata file to save the variables used in the present tool
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87 objects2save <- c("raw_data", "zipfile", "singlefile", "md5sumList", "sampleNamesList") # , "chromTIC", "chromBPI")
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88 save(list = objects2save[objects2save %in% ls()], file = "readmsdata.RData")
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91 cat("\tDONE\n")