Mercurial > repos > ethevenot > batchcorrection
view BC/batch_correction_wrapper.R @ 3:2e3a23dd6c24 draft default tip
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| author | melpetera |
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| date | Thu, 28 Feb 2019 05:12:34 -0500 |
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#!/usr/bin/env Rscript ################################################################################################ # batch_correction_wrapper # # # # Author: Marion LANDI / Jean-Francois MARTIN / Melanie Petera # # User: Galaxy # # Original data: -- # # Starting date: 22-07-2014 # # Version 1: 22-07-2014 # # Version 2: 08-12-2014 # # Version 2.1: 09-01-2015 modification in Error message of sample matching # # Version 2.2: 16-03-2015 inclusion of miniTools' functions for special characters # # Version 2.90: 18-08-2015 new parameter valnull # # Version 2.91: 25-08-2016 error message improvment # # # # # # Input files: dataMatrix.txt ; sampleMetadata.txt ; variableMetadata.txt (for DBC) # # Output files: graph_output.pdf ; corrected table ; diagnostic table # # # ################################################################################################ library(batch) #necessary for parseCommandArgs function ##------------------------------ ## test help option ##------------------------------ # Prog. constants argv.help <- commandArgs(trailingOnly = FALSE) script.path <- sub("--file=", "", argv.help[grep("--file=", argv.help)]) prog.name <- basename(script.path) # Test Help if (length(grep('-h', argv.help)) > 0) { cat("Usage: Rscript ", prog.name, "{args} \n", "parameters: \n", "\tanalyse {val}: must be set to \"batch_correction\"", "\tdataMatrix {file}: set the input data matrix file (mandatory) \n", "\tsampleMetadata {file}: set the input sample metadata file (mandatory) \n", "\tvariableMetadata {file}: set the input variable metadata file (mandatory) \n", "\tmethod {opt}: set the method; can set to \"linear\", \"lowess\" or \"loess\" (mandatory) \n", "\tspan {condition}: set the span condition; set to \"none\" if method is set to \"linear\" (mandatory) \n", "\tref_factor {value}: set the ref_factor value; (if span value is set to NULL, optional) \n", "\tdetail {value}: set the detail value; (if span value is set to NULL, optional) \n", "\tdataMatrix_out {file}: set the output data matrix file (mandatory) \n", "\tvariableMetadata_out {file}: set the output variable metadata file (mandatory) \n", "\tgraph_output {file}: set the output graph file (mandatory) \n", "\trdata_output {file}: set the output Rdata file (mandatory) \n", "\tbatch_col_name {val}: the column name for batch. Default value is \"batch\".\n", "\tinjection_order_col_name {val}: the column name for the injection order. Default value is \"injectionOrder\".\n", "\tsample_type_col_name {val}: the column name for the sample types. Default value is \"sampleType\".\n", "\tsample_type_tags {val}: the tags used inside the sample type column, defined as key/value pairs separated by commas (example: blank=blank,pool=pool,sample=sample).\n", "\n") quit(status = 0) } ##------------------------------ ## init. params ##------------------------------ args = parseCommandArgs(evaluate=FALSE) #interpretation of arguments given in command line as an R list of objects # Set default col names if ( ! 'batch_col_name' %in% names(args)) args[['batch_col_name']] <- 'batch' if ( ! 'injection_order_col_name' %in% names(args)) args[['injection_order_col_name']] <- 'injectionOrder' if ( ! 'sample_type_col_name' %in% names(args)) args[['sample_type_col_name']] <- 'sampleType' if ( ! 'sample_type_tags' %in% names(args)) args[['sample_type_tags']] <- 'blank=blank,pool=pool,sample=sample' # Parse sample type tags sample.type.tags <- list() for (kv in strsplit(strsplit(args$sample_type_tags, ',')[[1]], '=')) sample.type.tags[[kv[[1]]]] <- kv[[2]] if ( ! all(c('pool', 'blank', 'sample') %in% names(sample.type.tags))) stop("All tags pool, blank and sample must be defined in option sampleTypeTags.") args$sample_type_tags <- sample.type.tags ##------------------------------ ## init. functions ##------------------------------ source_local <- function(...){ argv <- commandArgs(trailingOnly = FALSE) base_dir <- dirname(substring(argv[grep("--file=", argv)], 8)) for(i in 1:length(list(...))){source(paste(base_dir, list(...)[[i]], sep="/"))} } #Import the different functions source_local("Normalisation_QCpool.r","easyrlibrary-lib/RcheckLibrary.R","easyrlibrary-lib/miniTools.R") ## Reading of input files idsample=read.table(args$sampleMetadata,header=T,sep='\t',check.names=FALSE,comment.char = '') iddata=read.table(args$dataMatrix,header=T,sep='\t',check.names=FALSE,comment.char = '') ### Table match check table.check <- match2(iddata,idsample,"sample") if(length(table.check)>1){check.err(table.check)} ### StockID samp.id <- stockID(iddata,idsample,"sample") iddata<-samp.id$dataMatrix ; idsample<-samp.id$Metadata ; samp.id<-samp.id$id.match ### Checking mandatory variables mand.check <- "" for(mandcol in c(args$sample_type_col_name, args$injection_order_col_name, args$batch_col_name)){ if(!(mandcol%in%colnames(idsample))){ mand.check <- c(mand.check,"\nError: no '",mandcol,"' column in sample metadata.\n", "Note: table must include this exact column name (it is case-sensitive).\n") } } if(length(mand.check)>1){ mand.check <- c(mand.check,"\nFor more information, see the help section or:", "\n http://workflow4metabolomics.org/sites/", "workflow4metabolomics.org/files/files/w4e-2016-data_processing.pdf\n") check.err(mand.check) } ### Formating idsample[[1]]=make.names(idsample[[1]]) dimnames(iddata)[[1]]=iddata[[1]] ### Transposition of ions data idTdata=t(iddata[,2:dim(iddata)[2]]) idTdata=data.frame(dimnames(idTdata)[[1]],idTdata) ### Merge of 2 files (ok even if the two dataframe are not sorted on the same key) id=merge(idsample, idTdata, by.x=1, by.y=1) id[[args$batch_col_name]]=as.factor(id[[args$batch_col_name]]) ids=id[id[[args$sample_type_col_name]] == args$sample_type_tags$pool | id[[args$sample_type_col_name]] == args$sample_type_tags$sample,] nbid=dim(idsample)[2] ### Checking the number of sample and pool # least 2 samples if(length(which(ids[[args$sample_type_col_name]] == args$sample_type_tags$sample))<2){ table.check <- c(table.check,"\nError: less than 2 samples specified in sample metadata.", "\nMake sure this is not due to errors in sampleType coding.\n") } # least 2 pools per batch for all batchs B <- rep(0,length(levels(ids[[args$batch_col_name]]))) for(nbB in length(levels(ids[[args$batch_col_name]]))){ B[nbB]<-length(which(ids[which(ids[[args$batch_col_name]]==(levels(ids[[args$batch_col_name]])[nbB])),][[args$sample_type_col_name]] == args$sample_type_tags$pool)) } if(length(which(B>1))==0){ table.check <- c(table.check,"\nError: less than 2 pools specified in each batch in sample metadata.", "\nMake sure this is not due to errors in sampleType coding.\n") } ### Factor of interest factbio=args$ref_factor if(args$analyse == "batch_correction") { ## Reading of Metadata Ions file metaion=read.table(args$variableMetadata,header=T,sep='\t',check.names=FALSE,comment.char = '') ## Table match check table.check <- c(table.check,match2(iddata,metaion,"variable")) check.err(table.check) ## variables detail=args$detail method=args$method ## outputs outlog=args$graph_output ## Launch res = norm_QCpool(ids,nbid,outlog,factbio,metaion,detail,F,F,method,args$span,args$valnull) save(res, file=args$rdata_output) write.table(reproduceID(res[[1]],res[[3]],"sample",samp.id)$dataMatrix, file=args$dataMatrix_out, sep = '\t', row.names=F, quote=F) write.table(res[[2]], file=args$variableMetadata_out, sep = '\t', row.names=F, quote=F) }else{ ## error check check.err(table.check) ## outputs out_graph_pdf=args$out_graph_pdf out_preNormSummary=args$out_preNormSummary ## Launch plotsituation(ids,nbid,out_graph_pdf,out_preNormSummary,factbio,args$span) } rm(args)