annotate NmrNormalization_wrapper.R @ 3:966fcf7ae66e draft

planemo upload for repository https://github.com/workflow4metabolomics/normalization commit 9ca88a22e9b9394bfa00ea383fbb2b78ef05f990

#!/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
## [e-mail]

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())