Mercurial > repos > marie-tremblay-metatoul > normalization
view NmrNormalization_wrapper.R @ 5:3d00a98974b7 draft
planemo upload for repository https://github.com/workflow4metabolomics/normalization commit 1aedb0fe77d56139bc8f5ded1fee1e455e8e9495
author | lecorguille |
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date | Tue, 02 Oct 2018 12:14:47 -0400 |
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children | 221cbd549c40 |
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#!/usr/bin/env Rscript ## 070115_NmrBucketing2galaxy_v1.R ## Marie Tremblay-Franco ## MetaboHUB: The French Infrastructure for Metabolomics and Fluxomics ## www.metabohub.fr/en ## marie.tremblay-franco@toulouse.inra.fr runExampleL <- FALSE ##------------------------------ ## Options ##------------------------------ strAsFacL <- options()$stringsAsFactors options(stringsAsFactors = FALSE) ##------------------------------ ## Libraries laoding ##------------------------------ # For parseCommandArgs function library(batch) # Constants argv <- commandArgs(trailingOnly = FALSE) script.path <- sub("--file=","",argv[grep("--file=",argv)]) prog.name <- basename(script.path) # Print help if (length(grep('-h', argv)) >0) { cat("Usage:", prog.name, "dataMatrix myDataMatrix.tsv", "scalingMethod PQN|QuantitativeVariable", "graphType None|Overlay|One_per_individual", "logOut myLog.txt", "dataMatrixOut myDataMatrixOutput.tsv", "graphOut myGraph.pdf", "\n") quit(status = 0) } # R script call source_local <- function(fname) { argv <- commandArgs(trailingOnly = FALSE) base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) source(paste(base_dir, fname, sep="/")) } #Import the different functions source_local("NmrNormalization_script.R") source_local("DrawSpec.R") ##------------------------------ ## Errors ????????????????????? ##------------------------------ ##------------------------------ ## Constants ##------------------------------ topEnvC <- environment() flagC <- "\n" ##------------------------------ ## Script ##------------------------------ if(!runExampleL) argLs <- parseCommandArgs(evaluate=FALSE) ## Parameters Loading ##------------------- # Inputs data <- read.table(argLs[["dataMatrix"]], check.names=FALSE, header=TRUE, sep="\t", row.names=1) names <- rownames(data) ## Add a test to check if all values are numercical if (!all(vapply(data, is.numeric, FUN.VALUE = FALSE))) stop("Data are not numeric") ## Integer conversion to avoid stack overflow when computin the sum data <- as.data.frame(lapply(data, as.numeric)) rownames(data) <- names scaling <- argLs[["scalingMethod"]] graphique <- argLs[["graphType"]] if (scaling=='PQN') { metadataSample <- read.table(argLs[["sampleMetadata"]],check.names=FALSE,header=TRUE,sep="\t") factor<- argLs[["factor"]] ControlGroup <- argLs[["controlGroup"]] } if (scaling=='QuantitativeVariable') { metadataSample <- read.table(argLs[["sampleMetadata"]],check.names=FALSE,header=TRUE,sep="\t") factor <- argLs[["factor"]] } # Outputs nomGraphe <- argLs[["graphOut"]] dataMatrixOut <- argLs[["dataMatrixOut"]] log <- argLs[["logOut"]] ## Checking R packages ##-------------------- sink(log) cat("\tPACKAGE INFO\n") pkgs=c("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="") } cat("\n") ## Checking arguments ##------------------- error.stock <- "\n" if(length(error.stock) > 1) stop(error.stock) ## Computation ##------------ NormalizationResults <- NmrNormalization(dataMatrix=data,scalingMethod=scaling,sampleMetadata=metadataSample, bioFactor=factor,ControlGroup=ControlGroup, graph=graphique,nomFichier=nomGraphe,savLog.txtC=log) data_normalized <- NormalizationResults[[1]] ## Graphical outputs ##------------------ if (graphique != "None") { # Graphic Device opening pdf(nomGraphe,onefile=TRUE) if (graphique == "Overlay") { # Global spectral window spectra <- data.frame(t(data_normalized)) drawSpec(spectra,xlab="", ylab="Intensity", main="") } else { for (i in 1:ncol(data_normalized)) { spectra <- t(data_normalized[,i]) drawSpec(spectra,xlab="", ylab="Intensity", main=colnames(data_normalized)[i]) } } dev.off() } ## Saving ##------- # Data data_normalized <- cbind(rownames(data_normalized),data_normalized) colnames(data_normalized) <- c("Variable",colnames(data_normalized)[-1]) write.table(data_normalized,file=argLs$dataMatrixOut,quote=FALSE,row.names=FALSE,sep="\t") ## Ending ##--------------------- cat("\nEnd of 'Normalization' Galaxy module call: ", as.character(Sys.time()), sep = "") sink() options(stringsAsFactors = strAsFacL) rm(list = ls())