annotate anticipated_purity_dims.R @ 6:2dce593d6c68 draft

planemo upload for repository https://github.com/computational-metabolomics/mspurity-galaxy commit afee93a926072b534bb3541e1524f1ad6a7decb9
author tomnl
date Mon, 23 Apr 2018 05:58:03 -0400
parents 84d223e361c6
children 43008b9c2009
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1 library(msPurity)
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2 library(optparse)
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3 print(sessionInfo())
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5 option_list <- list(
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6 make_option(c("--mzML_file"), type="character"),
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7 make_option(c("--peaks_file"), type="character"),
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8 make_option(c("-o", "--out_dir"), type="character"),
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9 make_option("--minOffset", default=0.5),
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10 make_option("--maxOffset", default=0.5),
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11 make_option("--ilim", default=0.05),
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12 make_option("--ppm", default=4),
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13 make_option("--dimspy", action="store_true"),
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14 make_option("--sim", action="store_true"),
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15 make_option("--remove_nas", action="store_true"),
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16 make_option("--iwNorm", default="none", type="character"),
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17 make_option("--file_num_dimspy", default=1),
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18 make_option("--exclude_isotopes", action="store_true"),
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19 make_option("--isotope_matrix", type="character")
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20 )
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22 # store options
efb634ef71fd planemo upload for repository https://github.com/computational-metabolomics/mspurity-galaxy commit f9591483bef88aef71a9f0cc0ffc75cf6eab480c
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23 opt<- parse_args(OptionParser(option_list=option_list))
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25 print(sessionInfo())
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26 print(opt)
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27
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28 if (is.null(opt$dimspy)){
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30 df <- read.table(opt$peaks_file, header = TRUE, sep='\t')
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31 filename = NA
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32 }else{
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33 indf <- read.table(opt$peaks_file,
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34 header = TRUE, sep='\t', stringsAsFactors = FALSE)
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35 filename = colnames(indf)[8:ncol(indf)][opt$dimspy_file_num]
efb634ef71fd planemo upload for repository https://github.com/computational-metabolomics/mspurity-galaxy commit f9591483bef88aef71a9f0cc0ffc75cf6eab480c
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36 # check if the data file is mzML or RAW (can only use mzML currently) so
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37 # we expect an mzML file of the same name in the same folder
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38 indf$i <- indf[,colnames(indf)==filename]
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39 indf[,colnames(indf)==filename] <- as.numeric(indf[,colnames(indf)==filename])
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41 filename = sub("raw", "mzML", filename, ignore.case = TRUE)
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43 df <- indf[4:nrow(indf),]
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44 if ('blank_flag' %in% colnames(df)){
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45 df <- df[df$blank_flag==1,]
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46 }
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48 colnames(df)[colnames(df)=='m.z'] <- 'mz'
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50 if ('nan' %in% df$mz){
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51 df[df$mz=='nan',]$mz <- NA
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52 }
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53 df$mz <- as.numeric(df$mz)
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55
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57
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58 }
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60 if (!is.null(opt$remove_nas)){
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61 df <- df[!is.na(df$mz),]
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62 }
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63
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64 if (is.null(opt$isotope_matrix)){
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65 im <- NULL
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66 }else{
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67 im <- read.table(opt$isotope_matrix,
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68 header = TRUE, sep='\t', stringsAsFactors = FALSE)
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69 }
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71 if (is.null(opt$exclude_isotopes)){
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72 isotopes <- FALSE
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73 }else{
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74 isotopes <- TRUE
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75 }
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77 print('FIRST ROWS OF PEAK FILE')
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78 print(head(df))
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79
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80 if (dir.exists(opt$mzML_file)){
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81 # if directory then we need to add a file name
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82 print(filename)
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83 if (is.na(filename)){
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84 print('ERROR: If a directory is provided then a filename needs to be entered
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85 directory or automatically obtained by using a dimspy output')
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86 quit()
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87 }else{
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88 mzml_file <- file.path(opt$mzML_file, filename)
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89 }
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90 }else{
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91 mzml_file <- opt$mzML_file
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92 }
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93
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94 if (is.null(opt$sim)){
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95 sim=FALSE
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96 }else{
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97 sim=TRUE
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98 }
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99
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100 minOffset = as.numeric(opt$minOffset)
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101 maxOffset = as.numeric(opt$maxOffset)
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102
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103
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104
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105 if (opt$iwNorm=='none'){
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106 iwNorm = FALSE
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107 iwNormFun = NULL
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108 }else if (opt$iwNorm=='gauss'){
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109 iwNorm = TRUE
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110 iwNormFun = msPurity::iwNormGauss(minOff=-minOffset, maxOff=maxOffset)
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111 }else if (opt$iwNorm=='rcosine'){
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112 iwNorm = TRUE
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113 iwNormFun = msPurity::iwNormRcosine(minOff=-minOffset, maxOff=maxOffset)
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114 }else if (opt$iwNorm=='QE5'){
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115 iwNorm = TRUE
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116 iwNormFun = msPurity::iwNormQE.5()
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117 }
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118
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119
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120 predicted <- msPurity::dimsPredictPuritySingle(df$mz,
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121 filepth=mzml_file,
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122 minOffset=minOffset,
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123 maxOffset=maxOffset,
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124 ppm=opt$ppm,
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125 mzML=TRUE,
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126 sim = sim,
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127 ilim = opt$ilim,
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128 isotopes = isotopes,
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129 im = im,
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130 iwNorm = iwNorm,
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131 iwNormFun = iwNormFun
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132 )
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133 predicted <- cbind(df, predicted)
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134
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135
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136 write.table(predicted, file.path(opt$out_dir, 'anticipated_dims_purity.tsv'), row.names=FALSE, sep='\t')