annotate batch_correction_all_loess_wrapper.R @ 0:71d83d8920bf draft

planemo upload for repository https://github.com/workflow4metabolomics/batchcorrection.git commit de79117e6ab856420b87efca3675c7963688f975

#!/usr/bin/env Rscript

library(batch) ## necessary for parseCommandArgs function
args = parseCommandArgs(evaluate=FALSE) #interpretation of arguments given in command line as an R list of objects

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("batch_correction_all_loess_script.R")

argVc <- unlist(args)

##  argVc["method"] is either 'all_loess_pool' or 'all_loess_sample'
##  alternative version developped by CEA
##  all variables are treated with loess
##  the reference observations for loess are either 'pool'
## ('all_loess_pool') or 'sample' ('all_loess_sample')


##------------------------------
## Initializing
##------------------------------

## options
##--------

strAsFacL <- options()$stringsAsFactors
options(stringsAsFactors = FALSE)

## libraries
##----------

suppressMessages(library(ropls))

if(packageVersion("ropls") < "1.4.0")
    stop("Please use 'ropls' versions of 1.4.0 and above")

## constants
##----------

modNamC <- "Batch correction" ## module name

## log file
##---------

## sink(argVc["information"]) ## not implemented

cat("\nStart of the '", modNamC, "' Galaxy module call: ",
    format(Sys.time(), "%a %d %b %Y %X"), "\n", sep="")

## loading
##--------

rawMN <- t(as.matrix(read.table(argVc["dataMatrix"],
                                header = TRUE,
                                row.names = 1,
                                sep = "\t")))

samDF <- read.table(argVc["sampleMetadata"],
                    header = TRUE,
                    row.names = 1,
                    sep = "\t")

varDF <- read.table(argVc["variableMetadata"],
                    check.names = FALSE,
                    header = TRUE,
                    row.names = 1,
                    sep = "\t") ## not used; for compatibility only

refC <- tolower(gsub("all_loess_", "", argVc["method"]))

spnN <- as.numeric(argVc["span"])


## checking
##---------

stopifnot(refC %in% c("pool", "sample"))

if(refC == "pool" &&
   !any("pool" %in% samDF[, "sampleType"]))
    stop("No 'pool' found in the 'sampleType' column; use the samples as normalization reference instead")

refMN <- rawMN[samDF[, "sampleType"] == refC, ]
refNasZerVl <- apply(refMN, 2,
                     function(refVn)
                     all(sapply(refVn,
                                function(refN) {is.na(refN) || refN == 0})))

if(sum(refNasZerVl)) {

    refNasZerVi <- which(refNasZerVl)
    cat("The following variables have 'NA' or 0 values in all reference samples; they will be removed from the data:\n", sep = "")
    print(refNasZerVi)
    rawMN <- rawMN[, !refNasZerVl, drop = FALSE]
    varDF <- varDF[!refNasZerVl, , drop = FALSE]

}

##------------------------------
## Computation
##------------------------------

## ordering (batch and injection order)
##-------------------------------------

samDF[, "ordIniVi"] <- 1:nrow(rawMN)
ordBatInjVi <- order(samDF[, "batch"], samDF[, "injectionOrder"])
rawMN <- rawMN[ordBatInjVi, ]
samDF <- samDF[ordBatInjVi, ]

## signal drift and batch-effect correction
##-----------------------------------------

nrmMN <- shiftBatchCorrectF(rawMN,
                            samDF,
                            refC,
                            spnN)

## figure
##-------

cat("\nPlotting\n")

pdf(argVc["graph_output"], onefile = TRUE, width = 11, height = 7)
plotBatchF(rawMN, samDF, spnN)
plotBatchF(nrmMN, samDF, spnN)
dev.off()

## returning to initial order
##---------------------------

ordIniVi <- order(samDF[, "ordIniVi"])
nrmMN <- nrmMN[ordIniVi, ]
samDF <- samDF[ordIniVi, ]
samDF <- samDF[, colnames(samDF) != "ordIniVi", drop=FALSE]


##------------------------------
## Ending
##------------------------------


## saving
##-------

datMN <- nrmMN

datDF <- cbind.data.frame(dataMatrix = colnames(datMN),
                          as.data.frame(t(datMN)))
write.table(datDF,
            file = argVc["dataMatrix_out"],
            quote = FALSE,
            row.names = FALSE,
            sep = "\t")

varDF <- cbind.data.frame(variableMetadata = rownames(varDF),
                          varDF) ## not modified; for compatibility only
write.table(varDF,
            file = argVc["variableMetadata_out"],
            quote = FALSE,
            row.names = FALSE,
            sep = "\t")

simDF <- cbind.data.frame(samDF, as.data.frame(datMN)) ## for compatibility
simDF <- cbind.data.frame(names = rownames(simDF),
                          simDF)
write.table(simDF,
            file = argVc["variable_for_simca"],
            quote = FALSE,
            row.names = FALSE,
            sep = "\t")

res <- list(dataMatrix_raw = rawMN,
            dataMatrix_normalized = nrmMN,
            sampleMetadata = samDF)
save(res,
     file = argVc["rdata_output"]) ## for compatibility

## closing
##--------

cat("\nEnd of '", modNamC, "' Galaxy module call: ",
    as.character(Sys.time()), "\n", sep = "")

## sink()

options(stringsAsFactors = strAsFacL)


rm(argVc)