comparison batch_correction_wrapper.R @ 3:2e3a23dd6c24 draft default tip

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author melpetera
date Thu, 28 Feb 2019 05:12:34 -0500
parents 57edfd3943ab
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2:57edfd3943ab 3:2e3a23dd6c24
1 #!/usr/bin/Rscript --vanilla --slave --no-site-file
2
3 ################################################################################################
4 # batch_correction_wrapper #
5 # #
6 # Author: Marion LANDI / Jean-Francois MARTIN / Melanie Petera #
7 # User: Galaxy #
8 # Original data: -- #
9 # Starting date: 22-07-2014 #
10 # Version 1: 22-07-2014 #
11 # Version 2: 08-12-2014 #
12 # Version 2.1: 09-01-2015 modification in Error message of sample matching #
13 # Version 2.2: 16-03-2015 inclusion of miniTools' functions for special characters #
14 # Version 2.90: 18-08-2015 new parameter valnull #
15 # Version 2.91: 25-08-2016 error message improvment #
16 # #
17 # #
18 # Input files: dataMatrix.txt ; sampleMetadata.txt ; variableMetadata.txt (for DBC) #
19 # Output files: graph_output.pdf ; corrected table ; diagnostic table #
20 # #
21 ################################################################################################
22
23
24 library(batch) #necessary for parseCommandArgs function
25 args = parseCommandArgs(evaluate=FALSE) #interpretation of arguments given in command line as an R list of objects
26
27 source_local <- function(...){
28 argv <- commandArgs(trailingOnly = FALSE)
29 base_dir <- dirname(substring(argv[grep("--file=", argv)], 8))
30 for(i in 1:length(list(...))){source(paste(base_dir, list(...)[[i]], sep="/"))}
31 }
32 #Import the different functions
33 source_local("Normalisation_QCpool.r","easyrlibrary-lib/RcheckLibrary.R","easyrlibrary-lib/miniTools.R")
34
35
36 ## Reading of input files
37 idsample=read.table(args$sampleMetadata,header=T,sep='\t',check.names=FALSE)
38 iddata=read.table(args$dataMatrix,header=T,sep='\t',check.names=FALSE)
39
40 ### Table match check
41 table.check <- match2(iddata,idsample,"sample")
42 if(length(table.check)>1){check.err(table.check)}
43
44 ### StockID
45 samp.id <- stockID(iddata,idsample,"sample")
46 iddata<-samp.id$dataMatrix ; idsample<-samp.id$Metadata ; samp.id<-samp.id$id.match
47
48 ### Checking mandatory variables
49 mand.check <- ""
50 for(mandcol in c("sampleType","injectionOrder","batch")){
51 if(!(mandcol%in%colnames(idsample))){
52 mand.check <- c(mand.check,"\nError: no '",mandcol,"' column in sample metadata.\n",
53 "Note: table must include this exact column name (it is case-sensitive).\n")
54 }
55 }
56 if(length(mand.check)>1){
57 mand.check <- c(mand.check,"\nFor more information, see the help section or:",
58 "\n http://workflow4metabolomics.org/sites/",
59 "workflow4metabolomics.org/files/files/w4e-2016-data_processing.pdf\n")
60 check.err(mand.check)
61 }
62
63 ### Formating
64 idsample[[1]]=make.names(idsample[[1]])
65 dimnames(iddata)[[1]]=iddata[[1]]
66
67 ### Transposition of ions data
68 idTdata=t(iddata[,2:dim(iddata)[2]])
69 idTdata=data.frame(dimnames(idTdata)[[1]],idTdata)
70
71 ### Merge of 2 files (ok even if the two dataframe are not sorted on the same key)
72 id=merge(idsample, idTdata, by.x=1, by.y=1)
73
74 id$batch=as.factor(id$batch)
75 ids=id[id$sampleType == 'pool' | id$sampleType == 'sample',]
76 nbid=dim(idsample)[2]
77
78 ### Checking the number of sample and pool
79
80 # least 2 samples
81 if(length(which(ids$sampleType == "sample"))<2){
82 table.check <- c(table.check,"\nError: less than 2 samples specified in sample metadata.",
83 "\nMake sure this is not due to errors in sampleType coding.\n")
84 }
85
86 # least 2 pools per batch for all batchs
87 B <- rep(0,length(levels(ids$batch)))
88 for(nbB in length(levels(ids$batch))){
89 B[nbB]<-length(which(ids[which(ids$batch==(levels(ids$batch)[nbB])),]$sampleType == "pool"))
90 }
91 if(length(which(B>1))==0){
92 table.check <- c(table.check,"\nError: less than 2 pools specified in each batch in sample metadata.",
93 "\nMake sure this is not due to errors in sampleType coding.\n")
94 }
95
96 ### Factor of interest
97 factbio=args$ref_factor
98
99
100 if(args$analyse == "batch_correction") {
101 ## Reading of Metadata Ions file
102 metaion=read.table(args$variableMetadata,header=T,sep='\t',check.names=FALSE)
103 ## Table match check
104 table.check <- c(table.check,match2(iddata,metaion,"variable"))
105 check.err(table.check)
106
107 ## variables
108 detail=args$detail
109 method=args$method
110
111 ## outputs
112 outlog=args$graph_output
113
114 ## Launch
115 res = norm_QCpool(ids,nbid,outlog,factbio,metaion,detail,F,F,method,args$span,args$valnull)
116 save(res, file=args$rdata_output)
117 write.table(reproduceID(res[[1]],res[[3]],"sample",samp.id)$dataMatrix, file=args$dataMatrix_out, sep = '\t', row.names=F, quote=F)
118 write.table(res[[2]], file=args$variableMetadata_out, sep = '\t', row.names=F, quote=F)
119 }else{
120 ## error check
121 check.err(table.check)
122
123 ## outputs
124 out_graph_pdf=args$out_graph_pdf
125 out_preNormSummary=args$out_preNormSummary
126
127 ## Launch
128 plotsituation(ids,nbid,out_graph_pdf,out_preNormSummary,factbio,args$span)
129 }
130
131 rm(args)