# HG changeset patch # User lecorguille # Date 1537301549 14400 # Node ID 8828cba9aedd1a5d3d7012f1798dafe6a828d2bf # Parent e4e0254a3c0a492602b75cc9e89a692fa0a94ac8 planemo upload for repository https://github.com/workflow4metabolomics/xcms commit 9f72e947d9c241d11221cad561f3525d27231857 diff -r e4e0254a3c0a -r 8828cba9aedd README.rst --- a/README.rst Wed Nov 29 09:46:41 2017 -0500 +++ b/README.rst Tue Sep 18 16:12:29 2018 -0400 @@ -2,26 +2,42 @@ Changelog/News -------------- +**Version 3.0.0.0 - 08/03/2018** + +- UPGRADE: upgrade the xcms version from 1.46.0 to 3.0.0. So refactoring of a lot of underlying codes and methods. Some parameters may have been renamed. + +- NEW: a bunch of new options: Obiwarp.(centerSample, response, distFun, gapInit, gapExtend, factorDiag, factorGap, localAlignment, initPenalty) + +- IMPROVEMENT: the advanced options are now in sections. It will allow you to access to all the parameters and to know their default values. + +- CHANGE: removing of the TIC and BPC plots. You can new use the dedicated tool "xcms plot chromatogram" + + **Version 2.1.1 - 29/11/2017** - BUGFIX: To avoid issues with accented letter in the parentFile tag of the mzXML files, we changed a hidden mechanim to LC_ALL=C + **Version 2.1.0 - 03/02/2017** - IMPROVEMENT: xcms.retcor can deal with merged individual data + **Version 2.0.8 - 22/12/2016** - BUGFIX: when having only one group (i.e. one folder of raw data) the BPC and TIC pdf files do not contain any graph + **Version 2.0.7 - 06/07/2016** - UPGRADE: upgrate the xcms version from 1.44.0 to 1.46.0 + **Version 2.0.6 - 04/04/2016** - TEST: refactoring to pass planemo test using conda dependencies + **Version 2.0.5 - 10/02/2016** - BUGFIX: better management of errors. Datasets remained green although the process failed diff -r e4e0254a3c0a -r 8828cba9aedd abims_xcms_retcor.xml --- a/abims_xcms_retcor.xml Wed Nov 29 09:46:41 2017 -0500 +++ b/abims_xcms_retcor.xml Tue Sep 18 16:12:29 2018 -0400 @@ -1,36 +1,41 @@ - + - Retention Time Correction using retcor function from xcms R package + Retention Time Correction macros.xml + macros_xcms.xml - + - - - + + + - - + + + + + + + + + +
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- - - (methods['method'] == 'peakgroups') - (options['option'] == 'show') - (family == 'symmetric') - (plottype != 'none') - - - - - - - - - - - - - - + + + + + + + +
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**xset.group.RData** - -Parameters ----------- - - | Method: -> **peakgroups** - | smooth: -> **loess** - | extra: -> **1** - | missing -> **1** - | Advanced options: -> **show** - | span -> **0.2** - | family -> **gaussian** - | plottype -> **deviation** - - -Output files ------------- - - | **1) xset.group.retcor.RData: RData file** - - | **2) Example of an xset.group.retcor.TICs_corrected pdf file** - -.. image:: xcms_retcor.png + | Rdata file that will be necessary in the **xcms.groupChromPeaks** step of the workflow. --------------------------------------------------- @@ -319,22 +306,37 @@ Changelog/News -------------- +**Version 3.0.0.0 - 08/03/2018** + +- UPGRADE: upgrade the xcms version from 1.46.0 to 3.0.0. So refactoring of a lot of underlying codes and methods. Some parameters may have been renamed. + +- NEW: a bunch of new options: Obiwarp.(centerSample, response, distFun, gapInit, gapExtend, factorDiag, factorGap, localAlignment, initPenalty) + +- IMPROVEMENT: the advanced options are now in sections. It will allow you to access to all the parameters and to know their default values. + +- CHANGE: removing of the TIC and BPC plots. You can now use the dedicated tool "xcms plot chromatogram" + + **Version 2.1.1 - 29/11/2017** - BUGFIX: To avoid issues with accented letter in the parentFile tag of the mzXML files, we changed a hidden mechanim to LC_ALL=C + **Version 2.1.0 - 03/02/2017** - IMPROVEMENT: xcms.retcor can deal with merged individual data + **Version 2.0.8 - 22/12/2016** - BUGFIX: when having only one group (i.e. one folder of raw data) the BPC and TIC pdf files do not contain any graph + **Version 2.0.7 - 06/07/2016** - UPGRADE: upgrate the xcms version from 1.44.0 to 1.46.0 + **Version 2.0.6 - 04/04/2016** - TEST: refactoring to pass planemo test using conda dependencies diff -r e4e0254a3c0a -r 8828cba9aedd lib-xcms3.x.x.r --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/lib-xcms3.x.x.r Tue Sep 18 16:12:29 2018 -0400 @@ -0,0 +1,152 @@ + + +#@TODO: remove this function as soon as we can use xcms 3.x.x from Bioconductor 3.7 +# https://github.com/sneumann/xcms/issues/250 +groupnamesW4M <- function(xdata, mzdec = 0, rtdec = 0) { + mzfmt <- paste("%.", mzdec, "f", sep = "") + rtfmt <- paste("%.", rtdec, "f", sep = "") + + gnames <- paste("M", sprintf(mzfmt, featureDefinitions(xdata)[,"mzmed"]), "T", + sprintf(rtfmt, featureDefinitions(xdata)[,"rtmed"]), sep = "") + + if (any(dup <- duplicated(gnames))) + for (dupname in unique(gnames[dup])) { + dupidx <- which(gnames == dupname) + gnames[dupidx] <- paste(gnames[dupidx], seq(along = dupidx), sep = "_") + } + + return (gnames) +} + +#@TODO: remove this function as soon as we can use xcms 3.x.x from Bioconductor 3.7 +# https://github.com/sneumann/xcms/issues/247 +.concatenate_XCMSnExp <- function(...) { + x <- list(...) + if (length(x) == 0) + return(NULL) + if (length(x) == 1) + return(x[[1]]) + ## Check that all are XCMSnExp objects. + if (!all(unlist(lapply(x, function(z) is(z, "XCMSnExp"))))) + stop("All passed objects should be 'XCMSnExp' objects") + new_x <- as(.concatenate_OnDiskMSnExp(...), "XCMSnExp") + ## If any of the XCMSnExp has alignment results or detected features drop + ## them! + x <- lapply(x, function(z) { + if (hasAdjustedRtime(z)) { + z <- dropAdjustedRtime(z) + warning("Adjusted retention times found, had to drop them.") + } + if (hasFeatures(z)) { + z <- dropFeatureDefinitions(z) + warning("Feature definitions found, had to drop them.") + } + z + }) + ## Combine peaks + fls <- lapply(x, fileNames) + startidx <- cumsum(lengths(fls)) + pks <- lapply(x, chromPeaks) + procH <- lapply(x, processHistory) + for (i in 2:length(fls)) { + pks[[i]][, "sample"] <- pks[[i]][, "sample"] + startidx[i - 1] + procH[[i]] <- lapply(procH[[i]], function(z) { + z@fileIndex <- as.integer(z@fileIndex + startidx[i - 1]) + z + }) + } + pks <- do.call(rbind, pks) + new_x@.processHistory <- unlist(procH) + chromPeaks(new_x) <- pks + if (validObject(new_x)) + new_x +} + +#@TODO: remove this function as soon as we can use xcms 3.x.x from Bioconductor 3.7 +# https://github.com/sneumann/xcms/issues/247 +.concatenate_OnDiskMSnExp <- function(...) { + x <- list(...) + if (length(x) == 0) + return(NULL) + if (length(x) == 1) + return(x[[1]]) + ## Check that all are XCMSnExp objects. + if (!all(unlist(lapply(x, function(z) is(z, "OnDiskMSnExp"))))) + stop("All passed objects should be 'OnDiskMSnExp' objects") + ## Check processingQueue + procQ <- lapply(x, function(z) z@spectraProcessingQueue) + new_procQ <- procQ[[1]] + is_ok <- unlist(lapply(procQ, function(z) + !is.character(all.equal(new_procQ, z)) + )) + if (any(!is_ok)) { + warning("Processing queues from the submitted objects differ! ", + "Dropping the processing queue.") + new_procQ <- list() + } + ## processingData + fls <- lapply(x, function(z) z@processingData@files) + startidx <- cumsum(lengths(fls)) + ## featureData + featd <- lapply(x, fData) + ## Have to update the file index and the spectrum names. + for (i in 2:length(featd)) { + featd[[i]]$fileIdx <- featd[[i]]$fileIdx + startidx[i - 1] + rownames(featd[[i]]) <- MSnbase:::formatFileSpectrumNames( + fileIds = featd[[i]]$fileIdx, + spectrumIds = featd[[i]]$spIdx, + nSpectra = nrow(featd[[i]]), + nFiles = length(unlist(fls)) + ) + } + featd <- do.call(rbind, featd) + featd$spectrum <- 1:nrow(featd) + ## experimentData + expdata <- lapply(x, function(z) { + ed <- z@experimentData + data.frame(instrumentManufacturer = ed@instrumentManufacturer, + instrumentModel = ed@instrumentModel, + ionSource = ed@ionSource, + analyser = ed@analyser, + detectorType = ed@detectorType, + stringsAsFactors = FALSE) + }) + expdata <- do.call(rbind, expdata) + expdata <- new("MIAPE", + instrumentManufacturer = expdata$instrumentManufacturer, + instrumentModel = expdata$instrumentModel, + ionSource = expdata$ionSource, + analyser = expdata$analyser, + detectorType = expdata$detectorType) + + ## protocolData + protodata <- lapply(x, function(z) z@protocolData) + if (any(unlist(lapply(protodata, nrow)) > 0)) + warning("Found non-empty protocol data, but merging protocol data is", + " currently not supported. Skipped.") + ## phenoData + pdata <- do.call(rbind, lapply(x, pData)) + res <- new( + "OnDiskMSnExp", + phenoData = new("NAnnotatedDataFrame", data = pdata), + featureData = new("AnnotatedDataFrame", featd), + processingData = new("MSnProcess", + processing = paste0("Concatenated [", date(), "]"), + files = unlist(fls), smoothed = NA), + experimentData = expdata, + spectraProcessingQueue = new_procQ) + if (validObject(res)) + res +} + +#@TODO: remove this function as soon as we can use xcms 3.x.x from Bioconductor 3.7 +# https://github.com/sneumann/xcms/issues/247 +c.XCMSnExp <- function(...) { + .concatenate_XCMSnExp(...) +} + +#@TODO: remove this function as soon as we can use xcms 3.x.x from Bioconductor 3.7 +# https://github.com/sneumann/xcms/issues/247 +c.MSnbase <- function(...) { + .concatenate_OnDiskMSnExp(...) +} diff -r e4e0254a3c0a -r 8828cba9aedd lib.r --- a/lib.r Wed Nov 29 09:46:41 2017 -0500 +++ b/lib.r Tue Sep 18 16:12:29 2018 -0400 @@ -1,319 +1,269 @@ -#Authors ABiMS TEAM -#Lib.r for Galaxy Workflow4Metabolomics xcms tools -# -#version 2.4: lecorguille -# add getPeaklistW4M -#version 2.3: yguitton -# correction for empty PDF when only 1 class -#version 2.2 -# correct bug in Base Peak Chromatogram (BPC) option, not only TIC when scanrange used in xcmsSet -# Note if scanrange is used a warning is prompted in R console but do not stop PDF generation -#version 2.1: yguitton -# Modifications made by Guitton Yann +#@authors ABiMS TEAM, Y. Guitton +# lib.r for Galaxy Workflow4Metabolomics xcms tools + +#@author G. Le Corguille +# solve an issue with batch if arguments are logical TRUE/FALSE +parseCommandArgs <- function(...) { + args <- batch::parseCommandArgs(...) + for (key in names(args)) { + if (args[key] %in% c("TRUE","FALSE")) + args[key] = as.logical(args[key]) + } + return(args) +} +#@author G. Le Corguille +# This function will +# - load the packages +# - display the sessionInfo +loadAndDisplayPackages <- function(pkgs) { + for(pkg in pkgs) suppressPackageStartupMessages( stopifnot( library(pkg, quietly=TRUE, logical.return=TRUE, character.only=TRUE))) + + sessioninfo = sessionInfo() + cat(sessioninfo$R.version$version.string,"\n") + cat("Main packages:\n") + for (pkg in names(sessioninfo$otherPkgs)) { cat(paste(pkg,packageVersion(pkg)),"\t") }; cat("\n") + cat("Other loaded packages:\n") + for (pkg in names(sessioninfo$loadedOnly)) { cat(paste(pkg,packageVersion(pkg)),"\t") }; cat("\n") +} + +#@author G. Le Corguille +# This function merge several chromBPI or chromTIC into one. +mergeChrom <- function(chrom_merged, chrom) { + if (is.null(chrom_merged)) return(NULL) + chrom_merged@.Data <- cbind(chrom_merged@.Data, chrom@.Data) + return(chrom_merged) +} #@author G. Le Corguille -#This function convert if it is required the Retention Time in minutes +# This function merge several xdata into one. +mergeXData <- function(args) { + chromTIC <- NULL + chromBPI <- NULL + chromTIC_adjusted <- NULL + chromBPI_adjusted <- NULL + for(image in args$images) { + + load(image) + # Handle infiles + if (!exists("singlefile")) singlefile <- NULL + if (!exists("zipfile")) zipfile <- NULL + rawFilePath <- getRawfilePathFromArguments(singlefile, zipfile, args) + zipfile <- rawFilePath$zipfile + singlefile <- rawFilePath$singlefile + retrieveRawfileInTheWorkingDirectory(singlefile, zipfile) + + if (exists("raw_data")) xdata <- raw_data + if (!exists("xdata")) stop("\n\nERROR: The RData doesn't contain any object called 'xdata'. This RData should have been created by an old version of XMCS 2.*") + + cat(sampleNamesList$sampleNamesOrigin,"\n") + + if (!exists("xdata_merged")) { + xdata_merged <- xdata + singlefile_merged <- singlefile + md5sumList_merged <- md5sumList + sampleNamesList_merged <- sampleNamesList + chromTIC_merged <- chromTIC + chromBPI_merged <- chromBPI + chromTIC_adjusted_merged <- chromTIC_adjusted + chromBPI_adjusted_merged <- chromBPI_adjusted + } else { + if (is(xdata, "XCMSnExp")) xdata_merged <- c(xdata_merged,xdata) + else if (is(xdata, "OnDiskMSnExp")) xdata_merged <- .concatenate_OnDiskMSnExp(xdata_merged,xdata) + else stop("\n\nERROR: The RData either a OnDiskMSnExp object called raw_data or a XCMSnExp object called xdata") + + singlefile_merged <- c(singlefile_merged,singlefile) + md5sumList_merged$origin <- rbind(md5sumList_merged$origin,md5sumList$origin) + sampleNamesList_merged$sampleNamesOrigin <- c(sampleNamesList_merged$sampleNamesOrigin,sampleNamesList$sampleNamesOrigin) + sampleNamesList_merged$sampleNamesMakeNames <- c(sampleNamesList_merged$sampleNamesMakeNames,sampleNamesList$sampleNamesMakeNames) + chromTIC_merged <- mergeChrom(chromTIC_merged, chromTIC) + chromBPI_merged <- mergeChrom(chromBPI_merged, chromBPI) + chromTIC_adjusted_merged <- mergeChrom(chromTIC_adjusted_merged, chromTIC_adjusted) + chromBPI_adjusted_merged <- mergeChrom(chromBPI_adjusted_merged, chromBPI_adjusted) + } + } + rm(image) + xdata <- xdata_merged; rm(xdata_merged) + singlefile <- singlefile_merged; rm(singlefile_merged) + md5sumList <- md5sumList_merged; rm(md5sumList_merged) + sampleNamesList <- sampleNamesList_merged; rm(sampleNamesList_merged) + + if (!is.null(args$sampleMetadata)) { + cat("\tXSET PHENODATA SETTING...\n") + sampleMetadataFile <- args$sampleMetadata + sampleMetadata <- getDataFrameFromFile(sampleMetadataFile, header=F) + xdata@phenoData@data$sample_group=sampleMetadata$V2[match(xdata@phenoData@data$sample_name,sampleMetadata$V1)] + + if (any(is.na(pData(xdata)$sample_group))) { + sample_missing <- pData(xdata)$sample_name[is.na(pData(xdata)$sample_group)] + error_message <- paste("Those samples are missing in your sampleMetadata:", paste(sample_missing, collapse=" ")) + print(error_message) + stop(error_message) + } + } + + if (!is.null(chromTIC_merged)) { chromTIC <- chromTIC_merged; chromTIC@phenoData <- xdata@phenoData } + if (!is.null(chromBPI_merged)) { chromBPI <- chromBPI_merged; chromBPI@phenoData <- xdata@phenoData } + if (!is.null(chromTIC_adjusted_merged)) { chromTIC_adjusted <- chromTIC_adjusted_merged; chromTIC_adjusted@phenoData <- xdata@phenoData } + if (!is.null(chromBPI_adjusted_merged)) { chromBPI_adjusted <- chromBPI_adjusted_merged; chromBPI_adjusted@phenoData <- xdata@phenoData } + + return(list("xdata"=xdata, "singlefile"=singlefile, "md5sumList"=md5sumList,"sampleNamesList"=sampleNamesList, "chromTIC"=chromTIC, "chromBPI"=chromBPI, "chromTIC_adjusted"=chromTIC_adjusted, "chromBPI_adjusted"=chromBPI_adjusted)) +} + +#@author G. Le Corguille +# This function convert if it is required the Retention Time in minutes RTSecondToMinute <- function(variableMetadata, convertRTMinute) { if (convertRTMinute){ #converting the retention times (seconds) into minutes print("converting the retention times into minutes in the variableMetadata") - variableMetadata[,"rt"]=variableMetadata[,"rt"]/60 - variableMetadata[,"rtmin"]=variableMetadata[,"rtmin"]/60 - variableMetadata[,"rtmax"]=variableMetadata[,"rtmax"]/60 + variableMetadata[,"rt"] <- variableMetadata[,"rt"]/60 + variableMetadata[,"rtmin"] <- variableMetadata[,"rtmin"]/60 + variableMetadata[,"rtmax"] <- variableMetadata[,"rtmax"]/60 } return (variableMetadata) } #@author G. Le Corguille -#This function format ions identifiers +# This function format ions identifiers formatIonIdentifiers <- function(variableMetadata, numDigitsRT=0, numDigitsMZ=0) { - splitDeco = strsplit(as.character(variableMetadata$name),"_") - idsDeco = sapply(splitDeco, function(x) { deco=unlist(x)[2]; if (is.na(deco)) return ("") else return(paste0("_",deco)) }) - namecustom = make.unique(paste0("M",round(variableMetadata[,"mz"],numDigitsMZ),"T",round(variableMetadata[,"rt"],numDigitsRT),idsDeco)) - variableMetadata=cbind(name=variableMetadata$name, namecustom=namecustom, variableMetadata[,!(colnames(variableMetadata) %in% c("name"))]) + splitDeco <- strsplit(as.character(variableMetadata$name),"_") + idsDeco <- sapply(splitDeco, function(x) { deco=unlist(x)[2]; if (is.na(deco)) return ("") else return(paste0("_",deco)) }) + namecustom <- make.unique(paste0("M",round(variableMetadata[,"mz"],numDigitsMZ),"T",round(variableMetadata[,"rt"],numDigitsRT),idsDeco)) + variableMetadata <- cbind(name=variableMetadata$name, namecustom=namecustom, variableMetadata[,!(colnames(variableMetadata) %in% c("name"))]) return(variableMetadata) } #@author G. Le Corguille +# This function convert the remain NA to 0 in the dataMatrix +naTOzeroDataMatrix <- function(dataMatrix, naTOzero) { + if (naTOzero){ + dataMatrix[is.na(dataMatrix)] <- 0 + } + return (dataMatrix) +} + +#@author G. Le Corguille +# Draw the plotChromPeakDensity 3 per page in a pdf file +getPlotChromPeakDensity <- function(xdata, mzdigit=4) { + pdf(file="plotChromPeakDensity.pdf", width=16, height=12) + + par(mfrow = c(3, 1), mar = c(4, 4, 1, 0.5)) + + group_colors <- brewer.pal(3, "Set1")[1:length(unique(xdata$sample_group))] + names(group_colors) <- unique(xdata$sample_group) + + xlim <- c(min(featureDefinitions(xdata)$rtmin), max(featureDefinitions(xdata)$rtmax)) + for (i in 1:nrow(featureDefinitions(xdata))) { + mzmin = featureDefinitions(xdata)[i,]$mzmin + mzmax = featureDefinitions(xdata)[i,]$mzmax + plotChromPeakDensity(xdata, mz=c(mzmin,mzmax), col=group_colors, pch=16, xlim=xlim, main=paste(round(mzmin,mzdigit),round(mzmax,mzdigit))) + legend("topright", legend=names(group_colors), col=group_colors, cex=0.8, lty=1) + } + + dev.off() +} + +#@author G. Le Corguille +# Draw the plotChromPeakDensity 3 per page in a pdf file +getPlotAdjustedRtime <- function(xdata) { + + pdf(file="raw_vs_adjusted_rt.pdf", width=16, height=12) + + # Color by group + group_colors <- brewer.pal(3, "Set1")[1:length(unique(xdata$sample_group))] + if (length(group_colors) > 1) { + names(group_colors) <- unique(xdata$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) + + dev.off() +} + +#@author G. Le Corguille # value: intensity values to be used into, maxo or intb -getPeaklistW4M <- function(xset, intval="into",convertRTMinute=F,numDigitsMZ=4,numDigitsRT=0,variableMetadataOutput,dataMatrixOutput) { - variableMetadata_dataMatrix = peakTable(xset, method="medret", value=intval) - variableMetadata_dataMatrix = cbind(name=groupnames(xset),variableMetadata_dataMatrix) +getPeaklistW4M <- function(xdata, intval="into", convertRTMinute=F, numDigitsMZ=4, numDigitsRT=0, naTOzero=T, variableMetadataOutput, dataMatrixOutput) { + dataMatrix <- featureValues(xdata, method="medret", value=intval) + colnames(dataMatrix) <- tools::file_path_sans_ext(colnames(dataMatrix)) + dataMatrix = cbind(name=groupnamesW4M(xdata), dataMatrix) + variableMetadata <- featureDefinitions(xdata) + colnames(variableMetadata)[1] = "mz"; colnames(variableMetadata)[4] = "rt" + variableMetadata = data.frame(name=groupnamesW4M(xdata), variableMetadata) - dataMatrix = variableMetadata_dataMatrix[,(make.names(colnames(variableMetadata_dataMatrix)) %in% c("name", make.names(sampnames(xset))))] - - variableMetadata = variableMetadata_dataMatrix[,!(make.names(colnames(variableMetadata_dataMatrix)) %in% c(make.names(sampnames(xset))))] - variableMetadata = RTSecondToMinute(variableMetadata, convertRTMinute) - variableMetadata = formatIonIdentifiers(variableMetadata, numDigitsRT=numDigitsRT, numDigitsMZ=numDigitsMZ) + variableMetadata <- RTSecondToMinute(variableMetadata, convertRTMinute) + variableMetadata <- formatIonIdentifiers(variableMetadata, numDigitsRT=numDigitsRT, numDigitsMZ=numDigitsMZ) + dataMatrix <- naTOzeroDataMatrix(dataMatrix, naTOzero) write.table(variableMetadata, file=variableMetadataOutput,sep="\t",quote=F,row.names=F) write.table(dataMatrix, file=dataMatrixOutput,sep="\t",quote=F,row.names=F) + } -#@author Y. Guitton -getBPC <- function(file,rtcor=NULL, ...) { - object <- xcmsRaw(file) - sel <- profRange(object, ...) - cbind(if (is.null(rtcor)) object@scantime[sel$scanidx] else rtcor ,xcms:::colMax(object@env$profile[sel$massidx,sel$scanidx,drop=FALSE])) - #plotChrom(xcmsRaw(file), base=T) +#@author G. Le Corguille +# It allow different of field separators +getDataFrameFromFile <- function(filename, header=T) { + myDataFrame <- read.table(filename, header=header, sep=";", stringsAsFactors=F) + if (ncol(myDataFrame) < 2) myDataFrame <- read.table(filename, header=header, sep="\t", stringsAsFactors=F) + if (ncol(myDataFrame) < 2) myDataFrame <- read.table(filename, header=header, sep=",", stringsAsFactors=F) + 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 Y. Guitton -getBPCs <- function (xcmsSet=NULL, pdfname="BPCs.pdf",rt=c("raw","corrected"), scanrange=NULL) { - cat("Creating BIC pdf...\n") +#@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 (is.null(xcmsSet)) { - cat("Enter an xcmsSet \n") - stop() - } else { - files <- filepaths(xcmsSet) - } - - phenoDataClass<-as.vector(levels(xcmsSet@phenoData[,1])) #sometime phenoData have more than 1 column use first as class - - classnames<-vector("list",length(phenoDataClass)) - for (i in 1:length(phenoDataClass)){ - classnames[[i]]<-which( xcmsSet@phenoData[,1]==phenoDataClass[i]) - } + if (aggregationFun == "sum") + type="Total Ion Chromatograms" + else + type="Base Peak Intensity Chromatograms" - N <- dim(phenoData(xcmsSet))[1] + adjusted="Raw" + if (hasAdjustedRtime(xdata)) + adjusted="Adjusted" - TIC <- vector("list",N) - - - for (j in 1:N) { + main <- paste(type,":",adjusted,"data") - TIC[[j]] <- getBPC(files[j]) - #good for raw - # seems strange for corrected - #errors if scanrange used in xcmsSetgeneration - if (!is.null(xcmsSet) && rt == "corrected") - rtcor <- xcmsSet@rt$corrected[[j]] - else - rtcor <- NULL + pdf(pdfname, width=16, height=10) - TIC[[j]] <- getBPC(files[j],rtcor=rtcor) - # TIC[[j]][,1]<-rtcor + # Color by group + group_colors <- brewer.pal(3, "Set1")[1:length(unique(xdata$sample_group))] + if (length(group_colors) > 1) { + names(group_colors) <- unique(xdata$sample_group) + plot(chrom, col = group_colors[chrom$sample_group], main=main) + legend("topright", legend=names(group_colors), col=group_colors, cex=0.8, lty=1) } - - - pdf(pdfname,w=16,h=10) - cols <- rainbow(N) - lty = 1:N - pch = 1:N - #search for max x and max y in BPCs - xlim = range(sapply(TIC, function(x) range(x[,1]))) - ylim = range(sapply(TIC, function(x) range(x[,2]))) - ylim = c(-ylim[2], ylim[2]) - - - ##plot start - - if (length(phenoDataClass)>2){ - for (k in 1:(length(phenoDataClass)-1)){ - for (l in (k+1):length(phenoDataClass)){ - #print(paste(phenoDataClass[k],"vs",phenoDataClass[l],sep=" ")) - plot(0, 0, type="n", xlim = xlim/60, ylim = ylim, main = paste("Base Peak Chromatograms \n","BPCs_",phenoDataClass[k]," vs ",phenoDataClass[l], sep=""), xlab = "Retention Time (min)", ylab = "BPC") - colvect<-NULL - for (j in 1:length(classnames[[k]])) { - tic <- TIC[[classnames[[k]][j]]] - # points(tic[,1]/60, tic[,2], col = cols[i], pch = pch[i], type="l") - points(tic[,1]/60, tic[,2], col = cols[classnames[[k]][j]], pch = pch[classnames[[k]][j]], type="l") - colvect<-append(colvect,cols[classnames[[k]][j]]) - } - for (j in 1:length(classnames[[l]])) { - # i=class2names[j] - tic <- TIC[[classnames[[l]][j]]] - points(tic[,1]/60, -tic[,2], col = cols[classnames[[l]][j]], pch = pch[classnames[[l]][j]], type="l") - colvect<-append(colvect,cols[classnames[[l]][j]]) - } - legend("topright",paste(basename(files[c(classnames[[k]],classnames[[l]])])), col = colvect, lty = lty, pch = pch) - } - } - }#end if length >2 + # Color by sample + plot(chrom, col = rainbow(length(xdata@phenoData@data$sample_name)), main=main) + legend("topright", legend=xdata@phenoData@data$sample_name, col=rainbow(length(xdata@phenoData@data$sample_name)), cex=0.8, lty=1) - if (length(phenoDataClass)==2){ - k=1 - l=2 - colvect<-NULL - plot(0, 0, type="n", xlim = xlim/60, ylim = ylim, main = paste("Base Peak Chromatograms \n","BPCs_",phenoDataClass[k],"vs",phenoDataClass[l], sep=""), xlab = "Retention Time (min)", ylab = "BPC") - - for (j in 1:length(classnames[[k]])) { - - tic <- TIC[[classnames[[k]][j]]] - # points(tic[,1]/60, tic[,2], col = cols[i], pch = pch[i], type="l") - points(tic[,1]/60, tic[,2], col = cols[classnames[[k]][j]], pch = pch[classnames[[k]][j]], type="l") - colvect<-append(colvect,cols[classnames[[k]][j]]) - } - for (j in 1:length(classnames[[l]])) { - # i=class2names[j] - tic <- TIC[[classnames[[l]][j]]] - points(tic[,1]/60, -tic[,2], col = cols[classnames[[l]][j]], pch = pch[classnames[[l]][j]], type="l") - colvect<-append(colvect,cols[classnames[[l]][j]]) - } - legend("topright",paste(basename(files[c(classnames[[k]],classnames[[l]])])), col = colvect, lty = lty, pch = pch) - - }#end length ==2 - - #case where only one class - if (length(phenoDataClass)==1){ - k=1 - ylim = range(sapply(TIC, function(x) range(x[,2]))) - colvect<-NULL - plot(0, 0, type="n", xlim = xlim/60, ylim = ylim, main = paste("Base Peak Chromatograms \n","BPCs_",phenoDataClass[k], sep=""), xlab = "Retention Time (min)", ylab = "BPC") - - for (j in 1:length(classnames[[k]])) { - tic <- TIC[[classnames[[k]][j]]] - # points(tic[,1]/60, tic[,2], col = cols[i], pch = pch[i], type="l") - points(tic[,1]/60, tic[,2], col = cols[classnames[[k]][j]], pch = pch[classnames[[k]][j]], type="l") - colvect<-append(colvect,cols[classnames[[k]][j]]) - } - - legend("topright",paste(basename(files[c(classnames[[k]])])), col = colvect, lty = lty, pch = pch) - - }#end length ==1 - - dev.off() #pdf(pdfname,w=16,h=10) - - invisible(TIC) + dev.off() } - -#@author Y. Guitton -getTIC <- function(file,rtcor=NULL) { - object <- xcmsRaw(file) - cbind(if (is.null(rtcor)) object@scantime else rtcor, rawEIC(object,mzrange=range(object@env$mz))$intensity) -} - -## -## overlay TIC from all files in current folder or from xcmsSet, create pdf -## -#@author Y. Guitton -getTICs <- function(xcmsSet=NULL,files=NULL, pdfname="TICs.pdf",rt=c("raw","corrected")) { - cat("Creating TIC pdf...\n") - - if (is.null(xcmsSet)) { - filepattern <- c("[Cc][Dd][Ff]", "[Nn][Cc]", "([Mm][Zz])?[Xx][Mm][Ll]", "[Mm][Zz][Dd][Aa][Tt][Aa]", "[Mm][Zz][Mm][Ll]") - filepattern <- paste(paste("\\.", filepattern, "$", sep = ""), collapse = "|") - if (is.null(files)) - files <- getwd() - info <- file.info(files) - listed <- list.files(files[info$isdir], pattern = filepattern, recursive = TRUE, full.names = TRUE) - files <- c(files[!info$isdir], listed) - } else { - files <- filepaths(xcmsSet) - } - - phenoDataClass<-as.vector(levels(xcmsSet@phenoData[,1])) #sometime phenoData have more than 1 column use first as class - classnames<-vector("list",length(phenoDataClass)) - for (i in 1:length(phenoDataClass)){ - classnames[[i]]<-which( xcmsSet@phenoData[,1]==phenoDataClass[i]) - } - - N <- length(files) - TIC <- vector("list",N) - - for (i in 1:N) { - if (!is.null(xcmsSet) && rt == "corrected") - rtcor <- xcmsSet@rt$corrected[[i]] else - rtcor <- NULL - TIC[[i]] <- getTIC(files[i],rtcor=rtcor) - } - - pdf(pdfname,w=16,h=10) - cols <- rainbow(N) - lty = 1:N - pch = 1:N - #search for max x and max y in TICs - xlim = range(sapply(TIC, function(x) range(x[,1]))) - ylim = range(sapply(TIC, function(x) range(x[,2]))) - ylim = c(-ylim[2], ylim[2]) - - - ##plot start - if (length(phenoDataClass)>2){ - for (k in 1:(length(phenoDataClass)-1)){ - for (l in (k+1):length(phenoDataClass)){ - #print(paste(phenoDataClass[k],"vs",phenoDataClass[l],sep=" ")) - plot(0, 0, type="n", xlim = xlim/60, ylim = ylim, main = paste("Total Ion Chromatograms \n","TICs_",phenoDataClass[k]," vs ",phenoDataClass[l], sep=""), xlab = "Retention Time (min)", ylab = "TIC") - colvect<-NULL - for (j in 1:length(classnames[[k]])) { - tic <- TIC[[classnames[[k]][j]]] - # points(tic[,1]/60, tic[,2], col = cols[i], pch = pch[i], type="l") - points(tic[,1]/60, tic[,2], col = cols[classnames[[k]][j]], pch = pch[classnames[[k]][j]], type="l") - colvect<-append(colvect,cols[classnames[[k]][j]]) - } - for (j in 1:length(classnames[[l]])) { - # i=class2names[j] - tic <- TIC[[classnames[[l]][j]]] - points(tic[,1]/60, -tic[,2], col = cols[classnames[[l]][j]], pch = pch[classnames[[l]][j]], type="l") - colvect<-append(colvect,cols[classnames[[l]][j]]) - } - legend("topright",paste(basename(files[c(classnames[[k]],classnames[[l]])])), col = colvect, lty = lty, pch = pch) - } - } - }#end if length >2 - if (length(phenoDataClass)==2){ - k=1 - l=2 - - plot(0, 0, type="n", xlim = xlim/60, ylim = ylim, main = paste("Total Ion Chromatograms \n","TICs_",phenoDataClass[k],"vs",phenoDataClass[l], sep=""), xlab = "Retention Time (min)", ylab = "TIC") - colvect<-NULL - for (j in 1:length(classnames[[k]])) { - tic <- TIC[[classnames[[k]][j]]] - # points(tic[,1]/60, tic[,2], col = cols[i], pch = pch[i], type="l") - points(tic[,1]/60, tic[,2], col = cols[classnames[[k]][j]], pch = pch[classnames[[k]][j]], type="l") - colvect<-append(colvect,cols[classnames[[k]][j]]) - } - for (j in 1:length(classnames[[l]])) { - # i=class2names[j] - tic <- TIC[[classnames[[l]][j]]] - points(tic[,1]/60, -tic[,2], col = cols[classnames[[l]][j]], pch = pch[classnames[[l]][j]], type="l") - colvect<-append(colvect,cols[classnames[[l]][j]]) - } - legend("topright",paste(basename(files[c(classnames[[k]],classnames[[l]])])), col = colvect, lty = lty, pch = pch) - - }#end length ==2 - - #case where only one class - if (length(phenoDataClass)==1){ - k=1 - ylim = range(sapply(TIC, function(x) range(x[,2]))) - - plot(0, 0, type="n", xlim = xlim/60, ylim = ylim, main = paste("Total Ion Chromatograms \n","TICs_",phenoDataClass[k], sep=""), xlab = "Retention Time (min)", ylab = "TIC") - colvect<-NULL - for (j in 1:length(classnames[[k]])) { - tic <- TIC[[classnames[[k]][j]]] - # points(tic[,1]/60, tic[,2], col = cols[i], pch = pch[i], type="l") - points(tic[,1]/60, tic[,2], col = cols[classnames[[k]][j]], pch = pch[classnames[[k]][j]], type="l") - colvect<-append(colvect,cols[classnames[[k]][j]]) - } - - legend("topright",paste(basename(files[c(classnames[[k]])])), col = colvect, lty = lty, pch = pch) - - }#end length ==1 - - dev.off() #pdf(pdfname,w=16,h=10) - - invisible(TIC) -} - - - -## -## Get the polarities from all the samples of a condition +# 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 -getSampleMetadata <- function(xcmsSet=NULL, sampleMetadataOutput="sampleMetadata.tsv") { +getSampleMetadata <- function(xdata=NULL, sampleMetadataOutput="sampleMetadata.tsv") { cat("Creating the sampleMetadata file...\n") #Create the sampleMetada dataframe - sampleMetadata=xset@phenoData - sampleNamesOrigin=rownames(sampleMetadata) - sampleNamesMakeNames=make.names(sampleNamesOrigin) + sampleMetadata <- xdata@phenoData@data + rownames(sampleMetadata) <- NULL + colnames(sampleMetadata) <- c("sampleMetadata", "class") + + sampleNamesOrigin <- sampleMetadata$sampleMetadata + 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()) @@ -330,63 +280,49 @@ } } - sampleMetadata$sampleMetadata=sampleNamesMakeNames - sampleMetadata=cbind(sampleMetadata["sampleMetadata"],sampleMetadata["class"]) #Reorder columns - rownames(sampleMetadata)=NULL + sampleMetadata$sampleMetadata <- sampleNamesMakeNames + - #Create a list of files name in the current directory - list_files=xset@filepaths #For each sample file, the following actions are done - for (file in list_files){ + for (fileIdx in 1:length(fileNames(xdata))) { #Check if the file is in the CDF format - if (!mzR:::netCDFIsFile(file)){ + 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 + if (is.null(sampleMetadata$polarity)) sampleMetadata$polarity <- NA - #Create a simple xcmsRaw object for each sample - xcmsRaw=xcmsRaw(file) #Extract the polarity (a list of polarities) - polarity=xcmsRaw@polarity + polarity <- fData(xdata)[fData(xdata)$fileIdx == fileIdx,"polarity"] #Verify if all the scans have the same polarity - uniq_list=unique(polarity) + uniq_list <- unique(polarity) if (length(uniq_list)>1){ - polarity="mixed" + polarity <- "mixed" } else { - polarity=as.character(uniq_list) + polarity <- as.character(uniq_list) } - #Transforms the character to obtain only the sample name - filename=basename(file) - library(tools) - samplename=file_path_sans_ext(filename) #Set the polarity attribute - sampleMetadata$polarity[sampleMetadata$sampleMetadata==samplename]=polarity - - #Delete xcmsRaw object because it creates a bug for the fillpeaks step - rm(xcmsRaw) + sampleMetadata$polarity[fileIdx] <- polarity } } 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 check if xcms will found all the files -## +# This function check if xcms will found all the files #@author Gildas Le Corguille lecorguille@sb-roscoff.fr ABiMS TEAM checkFilesCompatibilityWithXcms <- function(directory) { cat("Checking files filenames compatibilities with xmcs...\n") # WHAT XCMS WILL FIND 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, "$", sep = ""),collapse = "|") + filepattern <- paste(paste("\\.", filepattern, "$", sep=""),collapse="|") info <- file.info(directory) - listed <- list.files(directory[info$isdir], pattern = filepattern,recursive = TRUE, full.names = TRUE) + listed <- list.files(directory[info$isdir], pattern=filepattern, recursive=TRUE, full.names=TRUE) files <- c(directory[!info$isdir], listed) files_abs <- file.path(getwd(), files) exists <- file.exists(files_abs) @@ -394,8 +330,8 @@ files[exists] <- sub("//","/",files[exists]) # WHAT IS ON THE FILESYSTEM - filesystem_filepaths=system(paste("find $PWD/",directory," -not -name '\\.*' -not -path '*conda-env*' -type f -name \"*\"", sep=""), intern=T) - filesystem_filepaths=filesystem_filepaths[grep(filepattern, filesystem_filepaths, perl=T)] + filesystem_filepaths <- system(paste0("find \"$PWD/",directory,"\" -not -name '\\.*' -not -path '*conda-env*' -type f -name \"*\""), intern=T) + filesystem_filepaths <- filesystem_filepaths[grep(filepattern, filesystem_filepaths, perl=T)] # COMPARISON if (!is.na(table(filesystem_filepaths %in% files)["FALSE"])) { @@ -406,16 +342,26 @@ } +#This function list the compatible files within the directory as xcms did +#@author Gildas Le Corguille lecorguille@sb-roscoff.fr ABiMS TEAM +getMSFiles <- function (directory) { + 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$isdir], listed) + exists <- file.exists(files) + files <- files[exists] + return(files) +} -## -## This function check if XML contains special caracters. It also checks integrity and completness. -## +# This function check if XML contains special caracters. It also checks integrity and completness. #@author Misharl Monsoor misharl.monsoor@sb-roscoff.fr ABiMS TEAM checkXmlStructure <- function (directory) { cat("Checking XML structure...\n") - cmd=paste("IFS=$'\n'; for xml in $(find",directory,"-not -name '\\.*' -not -path '*conda-env*' -type f -iname '*.*ml*'); do if [ $(xmllint --nonet --noout \"$xml\" 2> /dev/null; echo $?) -gt 0 ]; then echo $xml;fi; done;") - capture=system(cmd,intern=TRUE) + cmd <- paste0("IFS=$'\n'; for xml in $(find '",directory,"' -not -name '\\.*' -not -path '*conda-env*' -type f -iname '*.*ml*'); do if [ $(xmllint --nonet --noout \"$xml\" 2> /dev/null; echo $?) -gt 0 ]; then echo $xml;fi; done;") + capture <- system(cmd, intern=TRUE) if (length(capture)>0){ #message=paste("The following mzXML or mzML file is incorrect, please check these files first:",capture) @@ -427,24 +373,22 @@ } -## -## This function check if XML contain special characters -## +# This function check if XML contain special characters #@author Misharl Monsoor misharl.monsoor@sb-roscoff.fr ABiMS TEAM deleteXmlBadCharacters<- function (directory) { cat("Checking Non ASCII characters in the XML...\n") - processed=F - l=system( paste("find",directory, "-not -name '\\.*' -not -path '*conda-env*' -type f -iname '*.*ml*'"),intern=TRUE) + processed <- F + l <- system( paste0("find '",directory, "' -not -name '\\.*' -not -path '*conda-env*' -type f -iname '*.*ml*'"), intern=TRUE) for (i in l){ - cmd=paste("LC_ALL=C grep '[^ -~]' \"",i,"\"",sep="") - capture=suppressWarnings(system(cmd,intern=TRUE)) + cmd <- paste("LC_ALL=C grep '[^ -~]' \"", i, "\"", sep="") + capture <- suppressWarnings(system(cmd, intern=TRUE)) if (length(capture)>0){ - cmd=paste("perl -i -pe 's/[^[:ascii:]]//g;'",i) + cmd <- paste("perl -i -pe 's/[^[:ascii:]]//g;'",i) print( paste("WARNING: Non ASCII characters have been removed from the ",i,"file") ) - c=system(cmd,intern=TRUE) - capture="" - processed=T + c <- system(cmd, intern=TRUE) + capture <- "" + processed <- T } } if (processed) cat("\n\n") @@ -452,17 +396,15 @@ } -## -## This function will compute MD5 checksum to check the data integrity -## +# This function will compute MD5 checksum to check the data integrity #@author Gildas Le Corguille lecorguille@sb-roscoff.fr getMd5sum <- function (directory) { cat("Compute md5 checksum...\n") # WHAT XCMS WILL FIND filepattern <- c("[Cc][Dd][Ff]", "[Nn][Cc]", "([Mm][Zz])?[Xx][Mm][Ll]","[Mm][Zz][Dd][Aa][Tt][Aa]", "[Mm][Zz][Mm][Ll]") - filepattern <- paste(paste("\\.", filepattern, "$", sep = ""),collapse = "|") + filepattern <- paste(paste("\\.", filepattern, "$", sep=""),collapse="|") info <- file.info(directory) - listed <- list.files(directory[info$isdir], pattern = filepattern,recursive = TRUE, full.names = TRUE) + 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] @@ -476,80 +418,93 @@ # This function get the raw file path from the arguments -getRawfilePathFromArguments <- function(singlefile, zipfile, listArguments) { - if (!is.null(listArguments[["zipfile"]])) zipfile = listArguments[["zipfile"]] - if (!is.null(listArguments[["zipfilePositive"]])) zipfile = listArguments[["zipfilePositive"]] - if (!is.null(listArguments[["zipfileNegative"]])) zipfile = listArguments[["zipfileNegative"]] +#@author Gildas Le Corguille lecorguille@sb-roscoff.fr +getRawfilePathFromArguments <- function(singlefile, zipfile, args, prefix="") { + if (!(prefix %in% c("","Positive","Negative","MS1","MS2"))) stop("prefix must be either '', 'Positive', 'Negative', 'MS1' or 'MS2'") + + if (!is.null(args[[paste0("zipfile",prefix)]])) zipfile <- args[[paste0("zipfile",prefix)]] - if (!is.null(listArguments[["singlefile_galaxyPath"]])) { - singlefile_galaxyPaths = listArguments[["singlefile_galaxyPath"]]; - singlefile_sampleNames = listArguments[["singlefile_sampleName"]] - } - if (!is.null(listArguments[["singlefile_galaxyPathPositive"]])) { - singlefile_galaxyPaths = listArguments[["singlefile_galaxyPathPositive"]]; - singlefile_sampleNames = listArguments[["singlefile_sampleNamePositive"]] - } - if (!is.null(listArguments[["singlefile_galaxyPathNegative"]])) { - singlefile_galaxyPaths = listArguments[["singlefile_galaxyPathNegative"]]; - singlefile_sampleNames = listArguments[["singlefile_sampleNameNegative"]] + if (!is.null(args[[paste0("singlefile_galaxyPath",prefix)]])) { + singlefile_galaxyPaths <- args[[paste0("singlefile_galaxyPath",prefix)]] + singlefile_sampleNames <- args[[paste0("singlefile_sampleName",prefix)]] + } + if (exists("singlefile_galaxyPaths")){ + singlefile_galaxyPaths <- unlist(strsplit(singlefile_galaxyPaths,"\\|")) + singlefile_sampleNames <- unlist(strsplit(singlefile_sampleNames,"\\|")) + + singlefile <- NULL + for (singlefile_galaxyPath_i in seq(1: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 } - if (exists("singlefile_galaxyPaths")){ - singlefile_galaxyPaths = unlist(strsplit(singlefile_galaxyPaths,",")) - singlefile_sampleNames = unlist(strsplit(singlefile_sampleNames,",")) - - singlefile=NULL - for (singlefile_galaxyPath_i in seq(1:length(singlefile_galaxyPaths))) { - singlefile_galaxyPath=singlefile_galaxyPaths[singlefile_galaxyPath_i] - singlefile_sampleName=singlefile_sampleNames[singlefile_galaxyPath_i] - singlefile[[singlefile_sampleName]] = singlefile_galaxyPath - } - } - for (argument in c("zipfile","zipfilePositive","zipfileNegative","singlefile_galaxyPath","singlefile_sampleName","singlefile_galaxyPathPositive","singlefile_sampleNamePositive","singlefile_galaxyPathNegative","singlefile_sampleNameNegative")) { - listArguments[[argument]]=NULL - } - return(list(zipfile=zipfile, singlefile=singlefile, listArguments=listArguments)) + } + return(list(zipfile=zipfile, singlefile=singlefile)) } - # 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 retrieveRawfileInTheWorkingDirectory <- function(singlefile, zipfile) { if(!is.null(singlefile) && (length("singlefile")>0)) { for (singlefile_sampleName in names(singlefile)) { - singlefile_galaxyPath = singlefile[[singlefile_sampleName]] + 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!") + 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) } - file.symlink(singlefile_galaxyPath,singlefile_sampleName) + if (!suppressWarnings( try (file.link(singlefile_galaxyPath, singlefile_sampleName), silent=T))) + file.copy(singlefile_galaxyPath, singlefile_sampleName) + } - directory = "." + directory <- "." } - if(!is.null(zipfile) && (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!") + error_message <- paste("Cannot access the Zip file:",zipfile,". Please, contact your administrator ... if you have one!") print(error_message) stop(error_message) } #list all file in the zip file - #zip_files=unzip(zipfile,list=T)[,"Name"] + #zip_files <- unzip(zipfile,list=T)[,"Name"] #unzip suppressWarnings(unzip(zipfile, unzip="unzip")) #get the directory name - filesInZip=unzip(zipfile, list=T); - 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 + suppressWarnings(filesInZip <- unzip(zipfile, list=T)) + 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") } return (directory) } + + +# This function retrieve a xset like object +#@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) + } +} diff -r e4e0254a3c0a -r 8828cba9aedd macros.xml --- a/macros.xml Wed Nov 29 09:46:41 2017 -0500 +++ b/macros.xml Tue Sep 18 16:12:29 2018 -0400 @@ -1,141 +1,52 @@ - - - r-snow - bioconductor-xcms - r-batch - - - - - bioconductor-xcms - - - - LC_ALL=C Rscript $__tool_directory__/xcms.r - + + LC_ALL=C Rscript $__tool_directory__/ ; return=\$?; - mv log.txt '$log'; - cat '$log'; + cat 'log.txt'; sh -c "exit \$return" - - - - #if $file_load_section.file_load_conditional.file_load_select == "yes": - #if $file_load_section.file_load_conditional.input[0].is_of_type("mzxml") or $file_load_section.file_load_conditional.input[0].is_of_type("mzml") or $file_load_section.file_load_conditional.input[0].is_of_type("mzdata") or $file_load_section.file_load_conditional.input[0].is_of_type("netcdf"): - #set singlefile_galaxyPath = ','.join( [ str( $single_file ) for $single_file in $file_load_section.file_load_conditional.input ] ) - #set singlefile_sampleName = ','.join( [ str( $single_file.name ) for $single_file in $file_load_section.file_load_conditional.input ] ) - - singlefile_galaxyPath '$singlefile_galaxyPath' singlefile_sampleName '$singlefile_sampleName' - #else - zipfile '$file_load_section.file_load_conditional.input' - #end if - #end if - - - -
- - - - - - - - - - - -
+ + + [0-9]+ *, *[0-9]+ - -
- - - - -
+ + [0-9]+\.?[0-9]* *, *[0-9]+\.?[0-9]* - -
- - - - -
+ + [0-9, ]+ - - #if $peaklist.peaklistBool - variableMetadataOutput '$variableMetadata' - dataMatrixOutput '$dataMatrix' - convertRTMinute $peaklist.convertRTMinute - numDigitsMZ $peaklist.numDigitsMZ - numDigitsRT $peaklist.numDigitsRT - intval $peaklist.intval - #end if - + + RData file + It contains a xcms3::XCMSnExp object (named xdata) - - - - - - - - - - - - - - - - - - - (peaklist['peaklistBool']) - - - (peaklist['peaklistBool']) - - - - -.. class:: infomark - -**Authors** Colin A. Smith csmith@scripps.edu, Ralf Tautenhahn rtautenh@gmail.com, Steffen Neumann sneumann@ipb-halle.de, Paul Benton hpaul.benton08@imperial.ac.uk and Christopher Conley cjconley@ucdavis.edu + + .. class:: infomark -**Galaxy integration** ABiMS TEAM - UPMC/CNRS - Station biologique de Roscoff and Yann Guitton yann.guitton@oniris-nantes.fr - part of Workflow4Metabolomics.org [W4M] +**Galaxy integration** ABiMS TEAM - SU/CNRS - Station biologique de Roscoff and Yann Guitton - LABERCA +Part of Workflow4Metabolomics.org [W4M] | Contact support@workflow4metabolomics.org for any questions or concerns about the Galaxy implementation of this tool. ---------------------------------------------------- - - - - - 10.1021/ac051437y + 10.1093/bioinformatics/btu813 -
diff -r e4e0254a3c0a -r 8828cba9aedd macros_xcms.xml --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/macros_xcms.xml Tue Sep 18 16:12:29 2018 -0400 @@ -0,0 +1,244 @@ + + + + 3.0.0 + + + bioconductor-xcms + r-batch + r-rcolorbrewer + unzip + + + + + + + #if $file_load_section.file_load_conditional.file_load_select == "yes": + #if $file_load_section.file_load_conditional.input[0].is_of_type("mzxml") or $file_load_section.file_load_conditional.input[0].is_of_type("mzml") or $file_load_section.file_load_conditional.input[0].is_of_type("mzdata") or $file_load_section.file_load_conditional.input[0].is_of_type("netcdf"): + #set singlefile_galaxyPath = '|'.join( [ str( $single_file ) for $single_file in $file_load_section.file_load_conditional.input ] ) + #set singlefile_sampleName = '|'.join( [ str( $single_file.name ) for $single_file in $file_load_section.file_load_conditional.input ] ) + + singlefile_galaxyPath '$singlefile_galaxyPath' singlefile_sampleName '$singlefile_sampleName' + #else + zipfile '$file_load_section.file_load_conditional.input' + #end if + #end if + + + +
+ + + + + + + + + + + +
+
+ + +
+ + + + +
+
+ + +
+ + + + +
+
+ + +
+ + + + +
+
+ + +
+ + + + +
+
+ + + + #if $peaklist.peaklistBool + convertRTMinute $peaklist.convertRTMinute + numDigitsMZ $peaklist.numDigitsMZ + numDigitsRT $peaklist.numDigitsRT + intval $peaklist.intval + naTOzero $peaklist.naTOzero + #end if + + + + + + + + + + + + + + + + + + + + + + + (peaklist['peaklistBool']) + + + (peaklist['peaklistBool']) + + + + + +Get a Peak List +--------------- + +If 'true', the module generates two additional files corresponding to the peak list: +- the variable metadata file (corresponding to information about extracted ions such as mass or retention time) +- the data matrix (corresponding to related intensities) + +**decimal places for [mass or retention time] values in identifiers** + + | Ions' identifiers are constructed as MxxxTyyy where 'xxx' is the ion median mass and 'yyy' the ion median retention time. + | Two parameters are used to adjust the number of decimal places wanted in identifiers for mass and retention time respectively. + | Theses parameters do not affect decimal places in columns other than the identifier one. + +**Reported intensity values** + + | This parameter determines which values should be reported as intensities in the dataMatrix table; it correspond to xcms 'intval' parameter: + | - into: integrated area of original (raw) peak + | - maxo: maximum intensity of original (raw) peak + | - intb: baseline corrected integrated peak area (only available if peak detection was done by ‘findPeaks.centWave’) + + + + +xset.variableMetadata.tsv : tabular format + + | Table containing information about ions; can be used as one input of **Quality_Metrics** or **Generic_filter** modules. + +xset.dataMatrix.tsv : tabular format + + | Table containing ions' intensities; can be used as one input of **Quality_Metrics** or **Generic_filter** modules. + + + + + ppm $methods.ppm + peakwidth "c($methods.peakwidth)" + + ## Advanced + snthresh $methods.CentWaveAdv.snthresh + prefilter "c($methods.CentWaveAdv.prefilter)" + mzCenterFun $methods.CentWaveAdv.mzCenterFun + integrate $methods.CentWaveAdv.integrate + mzdiff $methods.CentWaveAdv.mzdiff + fitgauss $methods.CentWaveAdv.fitgauss + noise $methods.CentWaveAdv.noise + verboseColumns $methods.CentWaveAdv.verboseColumns + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + #if $sectionROI.roiList: + roiList '$sectionROI.roiList' + firstBaselineCheck $sectionROI.firstBaselineCheck + #if $sectionROI.roiScales != "": + roiScales "c($sectionROI.roiScales)" + #end if + #end if + + + + + + + + + + + + +.. class:: infomark + +**Authors** Colin A. Smith csmith@scripps.edu, Ralf Tautenhahn rtautenh@gmail.com, Steffen Neumann sneumann@ipb-halle.de, Paul Benton hpaul.benton08@imperial.ac.uk and Christopher Conley cjconley@ucdavis.edu + +@HELP_AUTHORS_WRAPPERS@ + +--------------------------------------------------- + + + + + +For details and explanations concerning all the parameters and workflow of xcms_ package, see its manual_ and this example_ + +.. _xcms: https://bioconductor.org/packages/release/bioc/html/xcms.html +.. _manual: http://www.bioconductor.org/packages/release/bioc/manuals/xcms/man/xcms.pdf +.. _example: https://bioconductor.org/packages/release/bioc/vignettes/xcms/inst/doc/xcms.html + + + + + + 10.1021/ac051437y + + + +
diff -r e4e0254a3c0a -r 8828cba9aedd static/images/xcms_retcor_workflow.png Binary file static/images/xcms_retcor_workflow.png has changed diff -r e4e0254a3c0a -r 8828cba9aedd test-data/faahKO-single-class.xset.group.RData Binary file test-data/faahKO-single-class.xset.group.RData has changed diff -r e4e0254a3c0a -r 8828cba9aedd test-data/faahKO.xset.group.RData Binary file test-data/faahKO.xset.group.RData has changed diff -r e4e0254a3c0a -r 8828cba9aedd xcms.r --- a/xcms.r Wed Nov 29 09:46:41 2017 -0500 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,229 +0,0 @@ -#!/usr/bin/env Rscript -# xcms.r version="2.2.0" -#Authors ABIMS TEAM -#BPC Addition from Y.guitton - - -# ----- LOG FILE ----- -log_file=file("log.txt", open = "wt") -sink(log_file) -sink(log_file, type = "output") - - -# ----- PACKAGE ----- -cat("\tPACKAGE INFO\n") -#pkgs=c("xcms","batch") -pkgs=c("parallel","BiocGenerics", "Biobase", "Rcpp", "mzR", "xcms","snow","batch") -for(pkg in pkgs) { - suppressPackageStartupMessages( stopifnot( library(pkg, quietly=TRUE, logical.return=TRUE, character.only=TRUE))) - cat(pkg,"\t",as.character(packageVersion(pkg)),"\n",sep="") -} -source_local <- function(fname){ argv <- commandArgs(trailingOnly = FALSE); base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)); source(paste(base_dir, fname, sep="/")) } -cat("\n\n"); - - - - - -# ----- ARGUMENTS ----- -cat("\tARGUMENTS INFO\n") -listArguments = parseCommandArgs(evaluate=FALSE) #interpretation of arguments given in command line as an R list of objects -write.table(as.matrix(listArguments), col.names=F, quote=F, sep='\t') - -cat("\n\n"); - - -# ----- ARGUMENTS PROCESSING ----- -cat("\tINFILE PROCESSING INFO\n") - -#image is an .RData file necessary to use xset variable given by previous tools -if (!is.null(listArguments[["image"]])){ - load(listArguments[["image"]]); listArguments[["image"]]=NULL -} - -#Import the different functions -source_local("lib.r") - -cat("\n\n") - -#Import the different functions - -# ----- PROCESSING INFILE ----- -cat("\tARGUMENTS PROCESSING INFO\n") - -# Save arguments to generate a report -if (!exists("listOFlistArguments")) listOFlistArguments=list() -listOFlistArguments[[paste(format(Sys.time(), "%y%m%d-%H:%M:%S_"),listArguments[["xfunction"]],sep="")]] = listArguments - - -#saving the commun parameters -thefunction = listArguments[["xfunction"]]; listArguments[["xfunction"]]=NULL #delete from the list of arguments - -xsetRdataOutput = paste(thefunction,"RData",sep=".") -if (!is.null(listArguments[["xsetRdataOutput"]])){ - xsetRdataOutput = listArguments[["xsetRdataOutput"]]; listArguments[["xsetRdataOutput"]]=NULL -} - -#saving the specific parameters -rplotspdf = "Rplots.pdf" -if (!is.null(listArguments[["rplotspdf"]])){ - rplotspdf = listArguments[["rplotspdf"]]; listArguments[["rplotspdf"]]=NULL -} -sampleMetadataOutput = "sampleMetadata.tsv" -if (!is.null(listArguments[["sampleMetadataOutput"]])){ - sampleMetadataOutput = listArguments[["sampleMetadataOutput"]]; listArguments[["sampleMetadataOutput"]]=NULL -} -variableMetadataOutput = "variableMetadata.tsv" -if (!is.null(listArguments[["variableMetadataOutput"]])){ - variableMetadataOutput = listArguments[["variableMetadataOutput"]]; listArguments[["variableMetadataOutput"]]=NULL -} -dataMatrixOutput = "dataMatrix.tsv" -if (!is.null(listArguments[["dataMatrixOutput"]])){ - dataMatrixOutput = listArguments[["dataMatrixOutput"]]; listArguments[["dataMatrixOutput"]]=NULL -} -if (!is.null(listArguments[["convertRTMinute"]])){ - convertRTMinute = listArguments[["convertRTMinute"]]; listArguments[["convertRTMinute"]]=NULL -} -if (!is.null(listArguments[["numDigitsMZ"]])){ - numDigitsMZ = listArguments[["numDigitsMZ"]]; listArguments[["numDigitsMZ"]]=NULL -} -if (!is.null(listArguments[["numDigitsRT"]])){ - numDigitsRT = listArguments[["numDigitsRT"]]; listArguments[["numDigitsRT"]]=NULL -} -if (!is.null(listArguments[["intval"]])){ - intval = listArguments[["intval"]]; listArguments[["intval"]]=NULL -} - -if (thefunction %in% c("xcmsSet","retcor")) { - ticspdf = listArguments[["ticspdf"]]; listArguments[["ticspdf"]]=NULL - bicspdf = listArguments[["bicspdf"]]; listArguments[["bicspdf"]]=NULL -} - - -if (thefunction %in% c("xcmsSet","retcor","fillPeaks")) { - if (!exists("singlefile")) singlefile=NULL - if (!exists("zipfile")) zipfile=NULL - rawFilePath = getRawfilePathFromArguments(singlefile, zipfile, listArguments) - zipfile = rawFilePath$zipfile - singlefile = rawFilePath$singlefile - listArguments = rawFilePath$listArguments - directory = retrieveRawfileInTheWorkingDirectory(singlefile, zipfile) - md5sumList=list("origin"=getMd5sum(directory)) -} - -#addition of the directory to the list of arguments in the first position -if (thefunction == "xcmsSet") { - checkXmlStructure(directory) - checkFilesCompatibilityWithXcms(directory) - listArguments=append(directory, listArguments) -} - - -#addition of xset object to the list of arguments in the first position -if (exists("xset")){ - listArguments=append(list(xset), listArguments) -} - -cat("\n\n") - - - - -# ----- MAIN PROCESSING INFO ----- -cat("\tMAIN PROCESSING INFO\n") - - -#Verification of a group step before doing the fillpeaks job. - -if (thefunction == "fillPeaks") { - res=try(is.null(groupnames(xset))) - if (class(res) == "try-error"){ - error<-geterrmessage() - write(error, stderr()) - stop("You must always do a group step after a retcor. Otherwise it won't work for the fillpeaks step") - } - -} - -#change the default display settings -#dev.new(file="Rplots.pdf", width=16, height=12) -pdf(file=rplotspdf, width=16, height=12) -if (thefunction == "group") { - par(mfrow=c(2,2)) -} -#else if (thefunction == "retcor") { -#try to change the legend display -# par(xpd=NA) -# par(xpd=T, mar=par()$mar+c(0,0,0,4)) -#} - - -#execution of the function "thefunction" with the parameters given in "listArguments" - -cat("\t\tCOMPUTE\n") -xset = do.call(thefunction, listArguments) - -# check if there are no peaks -if (nrow(peaks(xset)) == 0) { - stop("No peaks were detected. You should review your settings") -} - - -cat("\n\n") - -dev.off() #dev.new(file="Rplots.pdf", width=16, height=12) - -if (thefunction == "xcmsSet") { - - #transform the files absolute pathways into relative pathways - xset@filepaths<-sub(paste(getwd(),"/",sep="") ,"", xset@filepaths) - if(exists("zipfile") && !is.null(zipfile) && (zipfile!="")) { - - #Modify the samples names (erase the path) - for(i in 1:length(sampnames(xset))){ - - sample_name=unlist(strsplit(sampnames(xset)[i], "/")) - sample_name=sample_name[length(sample_name)] - sample_name= unlist(strsplit(sample_name,"[.]"))[1] - sampnames(xset)[i]=sample_name - - } - - } - -} - -# -- TIC -- -if (thefunction == "xcmsSet") { - cat("\t\tGET TIC GRAPH\n") - sampleNamesList = getSampleMetadata(xcmsSet=xset, sampleMetadataOutput=sampleMetadataOutput) - getTICs(xcmsSet=xset, pdfname=ticspdf,rt="raw") - getBPCs(xcmsSet=xset,rt="raw",pdfname=bicspdf) -} else if (thefunction == "retcor") { - cat("\t\tGET TIC GRAPH\n") - getTICs(xcmsSet=xset, pdfname=ticspdf,rt="corrected") - getBPCs(xcmsSet=xset,rt="corrected",pdfname=bicspdf) -} - -if ((thefunction == "group" || thefunction == "fillPeaks") && exists("intval")) { - getPeaklistW4M(xset,intval,convertRTMinute,numDigitsMZ,numDigitsRT,variableMetadataOutput,dataMatrixOutput) -} - - -cat("\n\n") - -# ----- EXPORT ----- - -cat("\tXSET OBJECT INFO\n") -print(xset) -#delete the parameters to avoid the passage to the next tool in .RData image - - -#saving R data in .Rdata file to save the variables used in the present tool -objects2save = c("xset","zipfile","singlefile","listOFlistArguments","md5sumList","sampleNamesList") -save(list=objects2save[objects2save %in% ls()], file=xsetRdataOutput) - -cat("\n\n") - - -cat("\tDONE\n") diff -r e4e0254a3c0a -r 8828cba9aedd xcms_retcor.r --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/xcms_retcor.r Tue Sep 18 16:12:29 2018 -0400 @@ -0,0 +1,102 @@ +#!/usr/bin/env Rscript + +# ----- LOG FILE ----- +log_file=file("log.txt", open = "wt") +sink(log_file) +sink(log_file, type = "output") + + +# ----- PACKAGE ----- +cat("\tSESSION INFO\n") + +#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="/")) } +source_local("lib.r") +source_local("lib-xcms3.x.x.r") + +pkgs <- c("xcms","batch","RColorBrewer") +loadAndDisplayPackages(pkgs) +cat("\n\n"); + + +# ----- ARGUMENTS ----- +cat("\tARGUMENTS INFO\n") +args = parseCommandArgs(evaluate=FALSE) #interpretation of arguments given in command line as an R list of objects +write.table(as.matrix(args), col.names=F, quote=F, sep='\t') + +cat("\n\n") + +# ----- PROCESSING INFILE ----- +cat("\tARGUMENTS PROCESSING INFO\n") + +#saving the specific parameters +method <- args$method + +cat("\n\n") + + +# ----- ARGUMENTS PROCESSING ----- +cat("\tINFILE PROCESSING INFO\n") + +#image is an .RData file necessary to use xset variable given by previous tools +load(args$image); args$image=NULL +if (!exists("xdata")) stop("\n\nERROR: The RData doesn't contain any object called 'xdata'. This RData should have been created by an old version of XMCS 2.*") + +# Handle infiles +if (!exists("singlefile")) singlefile <- NULL +if (!exists("zipfile")) zipfile <- NULL +rawFilePath <- getRawfilePathFromArguments(singlefile, zipfile, args) +zipfile <- rawFilePath$zipfile +singlefile <- rawFilePath$singlefile +directory <- retrieveRawfileInTheWorkingDirectory(singlefile, zipfile) + +cat("\n\n") + + +# ----- MAIN PROCESSING INFO ----- +cat("\tMAIN PROCESSING INFO\n") + + +cat("\t\tCOMPUTE\n") + +cat("\t\t\tAlignment/Retention Time correction\n") +# clear the arguement list to remove unexpected key/value as singlefile_galaxyPath or method ... +args <- args[names(args) %in% slotNames(do.call(paste0(method,"Param"), list()))] + +adjustRtimeParam <- do.call(paste0(method,"Param"), args) +print(adjustRtimeParam) +xdata <- adjustRtime(xdata, param=adjustRtimeParam) + +cat("\t\t\tCompute and Store TIC and BPI\n") +chromTIC_adjusted = chromatogram(xdata, aggregationFun = "sum") +chromBPI_adjusted = chromatogram(xdata, aggregationFun = "max") + +cat("\n\n") + + +# -- TIC -- +cat("\t\tDRAW GRAPHICS\n") +getPlotAdjustedRtime(xdata) + +cat("\n\n") + +# ----- EXPORT ----- + +cat("\tXCMSnExp OBJECT INFO\n") +print(xdata) +cat("\n\n") + +cat("\txcmsSet OBJECT INFO\n") +# Get the legacy xcmsSet object +xset <- getxcmsSetObject(xdata) +print(xset) +cat("\n\n") + +#saving R data in .Rdata file to save the variables used in the present tool +objects2save = c("xdata","zipfile","singlefile","md5sumList","sampleNamesList", "chromTIC", "chromBPI", "chromTIC_adjusted", "chromBPI_adjusted") +save(list=objects2save[objects2save %in% ls()], file="retcor.RData") + +cat("\n\n") + + +cat("\tDONE\n")