# HG changeset patch # User workflow4metabolomics # Date 1738594089 0 # Node ID 3990a65b45a4361a0db5baeb110af0076ca9a8ca # Parent 6550698fe60f530fb6634f2d300607c2c53b205e planemo upload for repository https://github.com/workflow4metabolomics/tools-metabolomics/ commit 95721ced8347c09e79340e6d67ecb41c5cc64163 diff -r 6550698fe60f -r 3990a65b45a4 abims_xcms_xcmsSet.xml --- a/abims_xcms_xcmsSet.xml Mon Jul 15 16:02:04 2024 +0000 +++ b/abims_xcms_xcmsSet.xml Mon Feb 03 14:48:09 2025 +0000 @@ -7,10 +7,14 @@ + + + + 1) { - names(group_colors) <- unique(xdata$sample_group) - plotAdjustedRtime(xdata, col = group_colors[xdata$sample_group]) - legend("topright", legend = names(group_colors), col = group_colors, cex = 0.8, lty = 1) - } + # Color by group + if (length(unique(xdata$sample_group)) < 10) { + group_colors <- brewer.pal(length(unique(xdata$sample_group)), "Set1") + } else { + group_colors <- hcl.colors(length(unique(xdata$sample_group)), palette = "Dark 3") + } + if (length(group_colors) > 1) { + names(group_colors) <- unique(xdata$sample_group) + plotAdjustedRtime(xdata, col = group_colors[xdata$sample_group]) + legend("topright", legend = names(group_colors), col = group_colors, cex = 0.8, lty = 1) + } - # Color by sample - plotAdjustedRtime(xdata, col = rainbow(length(xdata@phenoData@data$sample_name))) - legend("topright", legend = xdata@phenoData@data$sample_name, col = rainbow(length(xdata@phenoData@data$sample_name)), cex = 0.8, lty = 1) + # Color by sample + plotAdjustedRtime(xdata, col = rainbow(length(xdata@phenoData@data$sample_name))) + legend("topright", legend = xdata@phenoData@data$sample_name, col = rainbow(length(xdata@phenoData@data$sample_name)), cex = 0.8, lty = 1) - dev.off() + dev.off() } -#@author G. Le Corguille +# @author G. Le Corguille # value: intensity values to be used into, maxo or intb getPeaklistW4M <- function(xdata, intval = "into", convertRTMinute = FALSE, numDigitsMZ = 4, numDigitsRT = 0, naTOzero = TRUE, variableMetadataOutput, dataMatrixOutput, sampleNamesList) { - dataMatrix <- featureValues(xdata, method = "medret", value = intval) - colnames(dataMatrix) <- make.names(tools::file_path_sans_ext(colnames(dataMatrix))) - dataMatrix <- cbind(name = groupnames(xdata), dataMatrix) - variableMetadata <- featureDefinitions(xdata) - colnames(variableMetadata)[1] <- "mz" - colnames(variableMetadata)[4] <- "rt" - variableMetadata <- data.frame(name = groupnames(xdata), variableMetadata) + dataMatrix <- featureValues(xdata, method = "medret", value = intval) + colnames(dataMatrix) <- make.names(tools::file_path_sans_ext(colnames(dataMatrix))) + dataMatrix <- cbind(name = groupnames(xdata), dataMatrix) + variableMetadata <- featureDefinitions(xdata) + colnames(variableMetadata)[1] <- "mz" + colnames(variableMetadata)[4] <- "rt" + variableMetadata <- data.frame(name = groupnames(xdata), variableMetadata) - variableMetadata <- RTSecondToMinute(variableMetadata, convertRTMinute) - variableMetadata <- formatIonIdentifiers(variableMetadata, numDigitsRT = numDigitsRT, numDigitsMZ = numDigitsMZ) - dataMatrix <- naTOzeroDataMatrix(dataMatrix, naTOzero) + variableMetadata <- RTSecondToMinute(variableMetadata, convertRTMinute) + variableMetadata <- formatIonIdentifiers(variableMetadata, numDigitsRT = numDigitsRT, numDigitsMZ = numDigitsMZ) + dataMatrix <- naTOzeroDataMatrix(dataMatrix, naTOzero) - # FIX: issue when the vector at peakidx is too long and is written in a new line during the export - variableMetadata[, "peakidx"] <- vapply(variableMetadata[, "peakidx"], FUN = paste, FUN.VALUE = character(1), collapse = ",") + # FIX: issue when the vector at peakidx is too long and is written in a new line during the export + variableMetadata[, "peakidx"] <- vapply(variableMetadata[, "peakidx"], FUN = paste, FUN.VALUE = character(1), collapse = ",") - write.table(variableMetadata, file = variableMetadataOutput, sep = "\t", quote = FALSE, row.names = FALSE) - write.table(dataMatrix, file = dataMatrixOutput, sep = "\t", quote = FALSE, row.names = FALSE) - + write.table(variableMetadata, file = variableMetadataOutput, sep = "\t", quote = FALSE, row.names = FALSE) + write.table(dataMatrix, file = dataMatrixOutput, sep = "\t", quote = FALSE, row.names = FALSE) } -#@author G. Le Corguille +# @author G. Le Corguille # It allow different of field separators getDataFrameFromFile <- function(filename, header = TRUE) { - myDataFrame <- read.table(filename, header = header, sep = ";", stringsAsFactors = FALSE) - if (ncol(myDataFrame) < 2) myDataFrame <- read.table(filename, header = header, sep = "\t", stringsAsFactors = FALSE) - if (ncol(myDataFrame) < 2) myDataFrame <- read.table(filename, header = header, sep = ",", stringsAsFactors = FALSE) - if (ncol(myDataFrame) < 2) { - error_message <- "Your tabular file seems not well formatted. The column separators accepted are ; , and tabulation" - print(error_message) - stop(error_message) - } - return(myDataFrame) + myDataFrame <- read.table(filename, header = header, sep = ";", stringsAsFactors = FALSE) + if (ncol(myDataFrame) < 2) myDataFrame <- read.table(filename, header = header, sep = "\t", stringsAsFactors = FALSE) + if (ncol(myDataFrame) < 2) myDataFrame <- read.table(filename, header = header, sep = ",", stringsAsFactors = FALSE) + if (ncol(myDataFrame) < 2) { + error_message <- "Your tabular file seems not well formatted. The column separators accepted are ; , and tabulation" + print(error_message) + stop(error_message) + } + return(myDataFrame) } -#@author G. Le Corguille +# @author G. Le Corguille # Draw the BPI and TIC graphics # colored by sample names or class names getPlotChromatogram <- function(chrom, xdata, pdfname = "Chromatogram.pdf", aggregationFun = "max") { - - if (aggregationFun == "sum") - type <- "Total Ion Chromatograms" - else - type <- "Base Peak Intensity Chromatograms" + if (aggregationFun == "sum") { + type <- "Total Ion Chromatograms" + } else { + type <- "Base Peak Intensity Chromatograms" + } - adjusted <- "Raw" - if (hasAdjustedRtime(xdata)) - adjusted <- "Adjusted" + adjusted <- "Raw" + if (hasAdjustedRtime(xdata)) { + adjusted <- "Adjusted" + } - main <- paste(type, ":", adjusted, "data") + main <- paste(type, ":", adjusted, "data") - pdf(pdfname, width = 16, height = 10) + pdf(pdfname, width = 16, height = 10) - # Color by group - if (length(unique(xdata$sample_group)) < 10) { - group_colors <- brewer.pal(length(unique(xdata$sample_group)), "Set1") - } else { - group_colors <- hcl.colors(length(unique(xdata$sample_group)), palette = "Dark 3") - } - if (length(group_colors) > 1) { - names(group_colors) <- unique(xdata$sample_group) - plot(chrom, col = group_colors[chrom$sample_group], main = main, peakType = "none") - legend("topright", legend = names(group_colors), col = group_colors, cex = 0.8, lty = 1) - } + # Color by group + if (length(unique(xdata$sample_group)) < 10) { + group_colors <- brewer.pal(length(unique(xdata$sample_group)), "Set1") + } else { + group_colors <- hcl.colors(length(unique(xdata$sample_group)), palette = "Dark 3") + } + if (length(group_colors) > 1) { + names(group_colors) <- unique(xdata$sample_group) + plot(chrom, col = group_colors[chrom$sample_group], main = main, peakType = "none") + legend("topright", legend = names(group_colors), col = group_colors, cex = 0.8, lty = 1) + } - # Color by sample - plot(chrom, col = rainbow(length(xdata@phenoData@data$sample_name)), main = main, peakType = "none") - legend("topright", legend = xdata@phenoData@data$sample_name, col = rainbow(length(xdata@phenoData@data$sample_name)), cex = 0.8, lty = 1) + # Color by sample + plot(chrom, col = rainbow(length(xdata@phenoData@data$sample_name)), main = main, peakType = "none") + legend("topright", legend = xdata@phenoData@data$sample_name, col = rainbow(length(xdata@phenoData@data$sample_name)), cex = 0.8, lty = 1) - dev.off() + dev.off() } # Get the polarities from all the samples of a condition -#@author Misharl Monsoor misharl.monsoor@sb-roscoff.fr ABiMS TEAM -#@author Gildas Le Corguille lecorguille@sb-roscoff.fr ABiMS TEAM +# @author Misharl Monsoor misharl.monsoor@sb-roscoff.fr ABiMS TEAM +# @author Gildas Le Corguille lecorguille@sb-roscoff.fr ABiMS TEAM getSampleMetadata <- function(xdata = NULL, sampleMetadataOutput = "sampleMetadata.tsv") { - cat("Creating the sampleMetadata file...\n") + cat("Creating the sampleMetadata file...\n") - #Create the sampleMetada dataframe - sampleMetadata <- xdata@phenoData@data - rownames(sampleMetadata) <- NULL - colnames(sampleMetadata) <- c("sample_name", "class") + # Create the sampleMetada dataframe + sampleMetadata <- xdata@phenoData@data + rownames(sampleMetadata) <- NULL + colnames(sampleMetadata) <- c("sample_name", "class") - sampleNamesOrigin <- sampleMetadata$sample_name - sampleNamesMakeNames <- make.names(sampleNamesOrigin) + sampleNamesOrigin <- sampleMetadata$sample_name + sampleNamesMakeNames <- make.names(sampleNamesOrigin) - if (any(duplicated(sampleNamesMakeNames))) { - write("\n\nERROR: Usually, R has trouble to deal with special characters in its column names, so it rename them using make.names().\nIn your case, at least two columns after the renaming obtain the same name, thus XCMS will collapse those columns per name.", stderr()) - for (sampleName in sampleNamesOrigin) { - write(paste(sampleName, "\t->\t", make.names(sampleName)), stderr()) + if (any(duplicated(sampleNamesMakeNames))) { + write("\n\nERROR: Usually, R has trouble to deal with special characters in its column names, so it rename them using make.names().\nIn your case, at least two columns after the renaming obtain the same name, thus XCMS will collapse those columns per name.", stderr()) + for (sampleName in sampleNamesOrigin) { + write(paste(sampleName, "\t->\t", make.names(sampleName)), stderr()) + } + stop("\n\nERROR: One or more of your files will not be import by xcmsSet. It may due to bad characters in their filenames.") } - stop("\n\nERROR: One or more of your files will not be import by xcmsSet. It may due to bad characters in their filenames.") - } - if (!all(sampleNamesOrigin == sampleNamesMakeNames)) { - cat("\n\nWARNING: Usually, R has trouble to deal with special characters in its column names, so it rename them using make.names()\nIn your case, one or more sample names will be renamed in the sampleMetadata and dataMatrix files:\n") - for (sampleName in sampleNamesOrigin) { - cat(paste(sampleName, "\t->\t", make.names(sampleName), "\n")) + if (!all(sampleNamesOrigin == sampleNamesMakeNames)) { + cat("\n\nWARNING: Usually, R has trouble to deal with special characters in its column names, so it rename them using make.names()\nIn your case, one or more sample names will be renamed in the sampleMetadata and dataMatrix files:\n") + for (sampleName in sampleNamesOrigin) { + cat(paste(sampleName, "\t->\t", make.names(sampleName), "\n")) + } } - } - sampleMetadata$sample_name <- sampleNamesMakeNames + sampleMetadata$sample_name <- sampleNamesMakeNames - #For each sample file, the following actions are done - for (fileIdx in seq_len(length(fileNames(xdata)))) { - #Check if the file is in the CDF format - if (!mzR:::netCDFIsFile(fileNames(xdata))) { - - # If the column isn't exist, with add one filled with NA - if (is.null(sampleMetadata$polarity)) sampleMetadata$polarity <- NA + # For each sample file, the following actions are done + for (fileIdx in seq_len(length(fileNames(xdata)))) { + # Check if the file is in the CDF format + if (!mzR:::netCDFIsFile(fileNames(xdata))) { + # If the column isn't exist, with add one filled with NA + if (is.null(sampleMetadata$polarity)) sampleMetadata$polarity <- NA - #Extract the polarity (a list of polarities) - polarity <- fData(xdata)[fData(xdata)$fileIdx == fileIdx, "polarity"] - #Verify if all the scans have the same polarity - uniq_list <- unique(polarity) - if (length(uniq_list) > 1) { - polarity <- "mixed" - } else { - polarity <- as.character(uniq_list) - } + # Extract the polarity (a list of polarities) + polarity <- fData(xdata)[fData(xdata)$fileIdx == fileIdx, "polarity"] + # Verify if all the scans have the same polarity + uniq_list <- unique(polarity) + if (length(uniq_list) > 1) { + polarity <- "mixed" + } else { + polarity <- as.character(uniq_list) + } - #Set the polarity attribute - sampleMetadata$polarity[fileIdx] <- polarity + # Set the polarity attribute + sampleMetadata$polarity[fileIdx] <- polarity + } } - } + write.table(sampleMetadata, sep = "\t", quote = FALSE, row.names = FALSE, file = sampleMetadataOutput) - write.table(sampleMetadata, sep = "\t", quote = FALSE, row.names = FALSE, file = sampleMetadataOutput) - - return(list("sampleNamesOrigin" = sampleNamesOrigin, "sampleNamesMakeNames" = sampleNamesMakeNames)) - + return(list("sampleNamesOrigin" = sampleNamesOrigin, "sampleNamesMakeNames" = sampleNamesMakeNames)) } # This function will compute MD5 checksum to check the data integrity -#@author Gildas Le Corguille lecorguille@sb-roscoff.fr +# @author Gildas Le Corguille lecorguille@sb-roscoff.fr getMd5sum <- function(files) { - cat("Compute md5 checksum...\n") - library(tools) - return(as.matrix(md5sum(files))) + cat("Compute md5 checksum...\n") + library(tools) + return(as.matrix(md5sum(files))) } # This function retrieve the raw file in the working directory # - if zipfile: unzip the file with its directory tree # - if singlefiles: set symlink with the good filename -#@author Gildas Le Corguille lecorguille@sb-roscoff.fr +# @author Gildas Le Corguille lecorguille@sb-roscoff.fr retrieveRawfileInTheWorkingDir <- function(singlefile, zipfile, args, prefix = "") { - - if (!(prefix %in% c("", "Positive", "Negative", "MS1", "MS2"))) stop("prefix must be either '', 'Positive', 'Negative', 'MS1' or 'MS2'") + if (!(prefix %in% c("", "Positive", "Negative", "MS1", "MS2"))) stop("prefix must be either '', 'Positive', 'Negative', 'MS1' or 'MS2'") - # single - if the file are passed in the command arguments -> refresh singlefile - if (!is.null(args[[paste0("singlefile_galaxyPath", prefix)]])) { - singlefile_galaxyPaths <- unlist(strsplit(args[[paste0("singlefile_galaxyPath", prefix)]], "\\|")) - singlefile_sampleNames <- unlist(strsplit(args[[paste0("singlefile_sampleName", prefix)]], "\\|")) + # single - if the file are passed in the command arguments -> refresh singlefile + if (!is.null(args[[paste0("singlefile_galaxyPath", prefix)]])) { + singlefile_galaxyPaths <- unlist(strsplit(args[[paste0("singlefile_galaxyPath", prefix)]], "\\|")) + singlefile_sampleNames <- unlist(strsplit(args[[paste0("singlefile_sampleName", prefix)]], "\\|")) - singlefile <- NULL - for (singlefile_galaxyPath_i in seq_len(length(singlefile_galaxyPaths))) { - singlefile_galaxyPath <- singlefile_galaxyPaths[singlefile_galaxyPath_i] - singlefile_sampleName <- singlefile_sampleNames[singlefile_galaxyPath_i] - # In case, an url is used to import data within Galaxy - singlefile_sampleName <- tail(unlist(strsplit(singlefile_sampleName, "/")), n = 1) - singlefile[[singlefile_sampleName]] <- singlefile_galaxyPath + singlefile <- NULL + for (singlefile_galaxyPath_i in seq_len(length(singlefile_galaxyPaths))) { + singlefile_galaxyPath <- singlefile_galaxyPaths[singlefile_galaxyPath_i] + singlefile_sampleName <- singlefile_sampleNames[singlefile_galaxyPath_i] + # In case, an url is used to import data within Galaxy + singlefile_sampleName <- tail(unlist(strsplit(singlefile_sampleName, "/")), n = 1) + singlefile[[singlefile_sampleName]] <- singlefile_galaxyPath + } } - } - # zipfile - if the file are passed in the command arguments -> refresh zipfile - if (!is.null(args[[paste0("zipfile", prefix)]])) - zipfile <- args[[paste0("zipfile", prefix)]] + # zipfile - if the file are passed in the command arguments -> refresh zipfile + if (!is.null(args[[paste0("zipfile", prefix)]])) { + zipfile <- args[[paste0("zipfile", prefix)]] + } - # single - if (!is.null(singlefile) && (length("singlefile") > 0)) { - files <- vector() - for (singlefile_sampleName in names(singlefile)) { - singlefile_galaxyPath <- singlefile[[singlefile_sampleName]] - if (!file.exists(singlefile_galaxyPath)) { - error_message <- paste("Cannot access the sample:", singlefile_sampleName, "located:", singlefile_galaxyPath, ". Please, contact your administrator ... if you have one!") - print(error_message) - stop(error_message) - } + # single + if (!is.null(singlefile) && (length("singlefile") > 0)) { + files <- vector() + for (singlefile_sampleName in names(singlefile)) { + singlefile_galaxyPath <- singlefile[[singlefile_sampleName]] + if (!file.exists(singlefile_galaxyPath)) { + error_message <- paste("Cannot access the sample:", singlefile_sampleName, "located:", singlefile_galaxyPath, ". Please, contact your administrator ... if you have one!") + print(error_message) + stop(error_message) + } - if (!suppressWarnings(try(file.link(singlefile_galaxyPath, singlefile_sampleName), silent = TRUE))) - file.copy(singlefile_galaxyPath, singlefile_sampleName) - files <- c(files, singlefile_sampleName) + if (!suppressWarnings(try(file.link(singlefile_galaxyPath, singlefile_sampleName), silent = TRUE))) { + file.copy(singlefile_galaxyPath, singlefile_sampleName) + } + files <- c(files, singlefile_sampleName) + } } - } - # zipfile - if (!is.null(zipfile) && (zipfile != "")) { - if (!file.exists(zipfile)) { - error_message <- paste("Cannot access the Zip file:", zipfile, ". Please, contact your administrator ... if you have one!") - print(error_message) - stop(error_message) - } - suppressWarnings(unzip(zipfile, unzip = "unzip")) + # zipfile + if (!is.null(zipfile) && (zipfile != "")) { + if (!file.exists(zipfile)) { + error_message <- paste("Cannot access the Zip file:", zipfile, ". Please, contact your administrator ... if you have one!") + print(error_message) + stop(error_message) + } + suppressWarnings(unzip(zipfile, unzip = "unzip")) - #get the directory name - suppressWarnings(filesInZip <- unzip(zipfile, list = TRUE)) - directories <- unique(unlist(lapply(strsplit(filesInZip$Name, "/"), function(x) x[1]))) - directories <- directories[!(directories %in% c("__MACOSX")) & file.info(directories)$isdir] - directory <- "." - if (length(directories) == 1) directory <- directories + # get the directory name + suppressWarnings(filesInZip <- unzip(zipfile, list = TRUE)) + directories <- unique(unlist(lapply(strsplit(filesInZip$Name, "/"), function(x) x[1]))) + directories <- directories[!(directories %in% c("__MACOSX")) & file.info(directories)$isdir] + directory <- "." + if (length(directories) == 1) directory <- directories - cat("files_root_directory\t", directory, "\n") + cat("files_root_directory\t", directory, "\n") - filepattern <- c("[Cc][Dd][Ff]", "[Nn][Cc]", "([Mm][Zz])?[Xx][Mm][Ll]", "[Mm][Zz][Dd][Aa][Tt][Aa]", "[Mm][Zz][Mm][Ll]") - filepattern <- paste(paste("\\.", filepattern, "$", sep = ""), collapse = "|") - info <- file.info(directory) - listed <- list.files(directory[info$isdir], pattern = filepattern, recursive = TRUE, full.names = TRUE) - files <- c(directory[!info$isdir], listed) - exists <- file.exists(files) - files <- files[exists] - - } - return(list(zipfile = zipfile, singlefile = singlefile, files = files)) + filepattern <- c("[Cc][Dd][Ff]", "[Nn][Cc]", "([Mm][Zz])?[Xx][Mm][Ll]", "[Mm][Zz][Dd][Aa][Tt][Aa]", "[Mm][Zz][Mm][Ll]") + filepattern <- paste(paste("\\.", filepattern, "$", sep = ""), collapse = "|") + info <- file.info(directory) + listed <- list.files(directory[info$isdir], pattern = filepattern, recursive = TRUE, full.names = TRUE) + files <- c(directory[!info$isdir], listed) + exists <- file.exists(files) + files <- files[exists] + } + return(list(zipfile = zipfile, singlefile = singlefile, files = files)) } # This function retrieve a xset like object -#@author Gildas Le Corguille lecorguille@sb-roscoff.fr +# @author Gildas Le Corguille lecorguille@sb-roscoff.fr getxcmsSetObject <- function(xobject) { - # XCMS 1.x - if (class(xobject) == "xcmsSet") - return(xobject) - # XCMS 3.x - if (class(xobject) == "XCMSnExp") { - # Get the legacy xcmsSet object - suppressWarnings(xset <- as(xobject, "xcmsSet")) - if (!is.null(xset@phenoData$sample_group)) - sampclass(xset) <- xset@phenoData$sample_group - else - sampclass(xset) <- "." - return(xset) - } + # XCMS 1.x + if (class(xobject) == "xcmsSet") { + return(xobject) + } + # XCMS 3.x + if (class(xobject) == "XCMSnExp") { + # Get the legacy xcmsSet object + suppressWarnings(xset <- as(xobject, "xcmsSet")) + if (!is.null(xset@phenoData$sample_group)) { + sampclass(xset) <- xset@phenoData$sample_group + } else { + sampclass(xset) <- "." + } + return(xset) + } } diff -r 6550698fe60f -r 3990a65b45a4 macros_xcms.xml --- a/macros_xcms.xml Mon Jul 15 16:02:04 2024 +0000 +++ b/macros_xcms.xml Mon Feb 03 14:48:09 2025 +0000 @@ -2,7 +2,7 @@ 3.12.0 - 1 + 3 21.09 diff -r 6550698fe60f -r 3990a65b45a4 xcms_xcmsSet.r --- a/xcms_xcmsSet.r Mon Jul 15 16:02:04 2024 +0000 +++ b/xcms_xcmsSet.r Mon Feb 03 14:48:09 2025 +0000 @@ -9,11 +9,11 @@ # ----- PACKAGE ----- cat("\tSESSION INFO\n") -#Import the different functions +# Import the different functions source_local <- function(fname) { - argv <- commandArgs(trailingOnly = FALSE) - base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) - source(paste(base_dir, fname, sep = "/")) + argv <- commandArgs(trailingOnly = FALSE) + base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) + source(paste(base_dir, fname, sep = "/")) } source_local("lib.r") @@ -24,7 +24,7 @@ # ----- ARGUMENTS ----- cat("\tARGUMENTS INFO\n") -args <- parseCommandArgs(evaluate = FALSE) #interpretation of arguments given in command line as an R list of objects +args <- parseCommandArgs(evaluate = FALSE) # interpretation of arguments given in command line as an R list of objects write.table(as.matrix(args), col.names = FALSE, quote = FALSE, sep = "\t") cat("\n\n") @@ -33,14 +33,14 @@ # ----- PROCESSING INFILE ----- cat("\tARGUMENTS PROCESSING INFO\n") -#saving the commun parameters +# saving the commun parameters BPPARAM <- MulticoreParam(1) if (!is.null(args$BPPARAM)) { - BPPARAM <- MulticoreParam(args$BPPARAM) + BPPARAM <- MulticoreParam(args$BPPARAM) } register(BPPARAM) -#saving the specific parameters +# saving the specific parameters if (!is.null(args$filterAcquisitionNum)) filterAcquisitionNumParam <- args$filterAcquisitionNum if (!is.null(args$filterRt)) filterRtParam <- args$filterRt if (!is.null(args$filterMz)) filterMzParam <- args$filterMz @@ -49,9 +49,9 @@ method <- args$method if (!is.null(args$roiList)) { - cat("\t\troiList provided\n") - args$roiList <- list(getDataFrameFromFile(args$roiList)) - print(args$roiList) + cat("\t\troiList provided\n") + args$roiList <- list(getDataFrameFromFile(args$roiList)) + print(args$roiList) } cat("\n\n") @@ -59,7 +59,7 @@ # ----- INFILE PROCESSING ----- cat("\tINFILE PROCESSING INFO\n") -#image is an .RData file necessary to use xset variable given by previous tools +# image is an .RData file necessary to use xset variable given by previous tools load(args$image) 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") @@ -79,12 +79,12 @@ cat("\t\tCOMPUTE\n") cat("\t\t\tApply filter[s] (if asked)\n") -if (exists("filterAcquisitionNumParam")) raw_data <- filterAcquisitionNum(raw_data, filterAcquisitionNumParam[1]:filterAcquisitionNumParam[2]) +if (exists("filterAcquisitionNumParam")) raw_data <- filterAcquisitionNum(raw_data, filterAcquisitionNumParam[1]:filterAcquisitionNumParam[2]) if (exists("filterRtParam")) raw_data <- filterRt(raw_data, filterRtParam) if (exists("filterMzParam")) raw_data <- filterMz(raw_data, filterMzParam) -#Apply this filter only if file contain MS and MSn +# Apply this filter only if file contain MS and MSn if (length(unique(msLevel(raw_data))) != 1) { - raw_data <- filterMsLevel(raw_data, msLevel = 1) + raw_data <- filterMsLevel(raw_data, msLevel = 1) } cat("\t\t\tChromatographic peak detection\n") @@ -103,10 +103,10 @@ # Create a chromPeaks table if required if (exists("peaklistParam")) { - if (peaklistParam) { - cat("\nCreating the chromatographic peaks' table...\n") - write.table(chromPeaks(xdata), file = "chromPeak_table.tsv", sep = "\t", quote = FALSE, row.names = FALSE) - } + if (peaklistParam) { + cat("\nCreating the chromatographic peaks' table...\n") + write.table(chromPeaks(xdata), file = "chromPeak_table.tsv", sep = "\t", quote = FALSE, row.names = FALSE) + } } cat("\n\n") @@ -123,7 +123,7 @@ print(xset) cat("\n\n") -#saving R data in .Rdata file to save the variables used in the present tool +# saving R data in .Rdata file to save the variables used in the present tool objects2save <- c("xdata", "zipfile", "singlefile", "md5sumList", "sampleNamesList") save(list = objects2save[objects2save %in% ls()], file = "xcmsSet.RData")