annotate NmrNormalization_wrapper.R @ 0:e1b29d705286 draft

planemo upload for repository https://github.com/workflow4metabolomics/nmr_normalization commit 0a2ec9e30fbf7690a80695c751e6ea432b10a759-dirty
author marie-tremblay-metatoul
date Mon, 18 Apr 2016 11:29:30 -0400
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1 #!/usr/local/public/bin/Rscript --vanilla --slave --no-site-file
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3 ## 070115_NmrBucketing2galaxy_v1.R
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4 ## Marie Tremblay-Franco
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5 ## MetaboHUB: The French Infrastructure for Metabolomics and Fluxomics
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6 ## www.metabohub.fr/en
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7 ## marie.tremblay-franco@toulouse.inra.fr
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9 runExampleL <- FALSE
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12 ##------------------------------
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13 ## Options
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14 ##------------------------------
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15 strAsFacL <- options()$stringsAsFactors
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16 options(stringsAsFactors = FALSE)
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19 ##------------------------------
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20 ## Libraries laoding
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21 ##------------------------------
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22 # For parseCommandArgs function
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23 library(batch)
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25 # R script call
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26 source_local <- function(fname)
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27 {
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28 argv <- commandArgs(trailingOnly = FALSE)
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29 base_dir <- dirname(substring(argv[grep("--file=", argv)], 8))
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30 source(paste(base_dir, fname, sep="/"))
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31 }
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32 #Import the different functions
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33 source_local("NmrNormalization_script.R")
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35 ##------------------------------
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36 ## Errors ?????????????????????
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37 ##------------------------------
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38
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40 ##------------------------------
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41 ## Constants
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42 ##------------------------------
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43 topEnvC <- environment()
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44 flagC <- "\n"
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47 ##------------------------------
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48 ## Script
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49 ##------------------------------
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50 if(!runExampleL)
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51 argLs <- parseCommandArgs(evaluate=FALSE)
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52
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53
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54 ## Parameters Loading
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55 ##-------------------
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56 # Inputs
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57 data <- read.table(argLs[["dataMatrix"]],check.names=FALSE,header=TRUE,sep="\t")
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58 rownames(data) <- data[,1]
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59 data <- data[,-1]
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60
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61 scaling <- argLs[["scalingMethod"]]
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62 graphique <- argLs[["graphType"]]
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63
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64 if (scaling=='PQN')
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65 {
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66 metadataSample <- read.table(argLs[["sampleMetadata"]],check.names=FALSE,header=TRUE,sep="\t")
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67 factor<- argLs[["factor"]]
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68 ControlGroup <- argLs[["controlGroup"]]
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69 }
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70 if (scaling=='QuantitativeVariable')
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71 {
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72 metadataSample <- read.table(argLs[["sampleMetadata"]],check.names=FALSE,header=TRUE,sep="\t")
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73 factor <- argLs[["factor"]]
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74 }
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75
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76 # Outputs
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77 nomGraphe <- argLs[["graphOut"]]
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78 dataMatrixOut <- argLs[["dataMatrixOut"]]
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79 sampleMetadataOut <- argLs[["sampleMetadataOut"]]
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80 variableMetadataOut <- argLs[["variableMetadataOut"]]
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81 log <- argLs[["logOut"]]
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82
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83 ## Checking arguments
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84 ##-------------------
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85 error.stock <- "\n"
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86
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87 if(length(error.stock) > 1)
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88 stop(error.stock)
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89
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90
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91 ## Computation
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92 ##------------
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93 NormalizationResults <- NmrNormalization(dataMatrix=data,scalingMethod=scaling,sampleMetadata=metadataSample,
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94 bioFactor=factor,ControlGroup=ControlGroup,
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95 graph=graphique,nomFichier=nomGraphe,savLog.txtC=log)
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96
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97 data_normalized <- NormalizationResults[[1]]
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98 data_sample <- NormalizationResults[[2]]
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99 data_variable <- NormalizationResults[[3]]
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100
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101
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102
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103 ## Saving
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104 ##-------
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105 # Data
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106 data_normalized <- cbind(rownames(data_normalized),data_normalized)
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107 colnames(data_normalized) <- c("Bucket",colnames(data_normalized)[-1])
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108 write.table(data_normalized,file=argLs$dataMatrixOut,quote=FALSE,row.names=FALSE,sep="\t")
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109 # Sample
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110 data_sample <- cbind(rownames(data_sample),data_sample)
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111 colnames(data_sample) <- c("Sample",colnames(data_sample)[-1])
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112 write.table(data_sample,file=argLs$sampleMetadataOut,quote=FALSE,row.names=FALSE,sep="\t")
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113 # Variable
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114 data_variable <- cbind(rownames(data_variable),data_variable)
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115 colnames(data_variable) <- c("Bucket",colnames(data_variable)[-1])
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116 write.table(data_variable,file=argLs$variableMetadataOut,quote=FALSE,row.names=FALSE,sep="\t")
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117
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118
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119 ## Ending
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120 ##---------------------
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121
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122 cat("\nEnd of 'NMR Normalization' Galaxy module call: ", as.character(Sys.time()), sep = "")
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123
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124 ## sink(NULL)
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125
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126 options(stringsAsFactors = strAsFacL)
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127
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128 rm(list = ls())