Mercurial > repos > marie-tremblay-metatoul > normalization
view NmrNormalization_wrapper.R @ 3:966fcf7ae66e draft
planemo upload for repository https://github.com/workflow4metabolomics/normalization commit 9ca88a22e9b9394bfa00ea383fbb2b78ef05f990
author | lecorguille |
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date | Thu, 26 Oct 2017 06:01:14 -0400 |
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#!/usr/local/public/bin/Rscript --vanilla --slave --no-site-file ## 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) # 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") rownames(data) <- data[,1] data <- data[,-1] 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 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("Bucket",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 = "") options(stringsAsFactors = strAsFacL) rm(list = ls())