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planemo upload for repository https://github.com/workflow4metabolomics/xcms commit 92dd69e5b063aad05a9b2b75e21c78bfa46c4b94
author lecorguille
date Thu, 22 Dec 2016 05:59:20 -0500
parents b9a87af62223
children f28041d2180a
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1a9bbd4670e8 planemo upload for repository https://github.com/workflow4metabolomics/xcms commit 92dd69e5b063aad05a9b2b75e21c78bfa46c4b94
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1 # lib.r version="2.3"
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2 #Authors ABiMS TEAM
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3 #Lib.r for Galaxy Workflow4Metabo
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4 #version 2.3
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5 #Based on lib.r 2.1
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6 #Modifications made by Guitton Yann
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7 #2.3 Note
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8 #correction for empty PDF when only 1 class
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9 #2.2 Note
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10 #correct bug in Base Peak Chromatogram (BPC) option, not only TIC when scanrange used in xcmsSet
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11 #Note if scanrange is used a warning is prompted in R console but do not stop PDF generation
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16 #@author Y. Guitton
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17 getBPC <- function(file,rtcor=NULL, ...) {
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18 object <- xcmsRaw(file)
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19 sel <- profRange(object, ...)
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20 cbind(if (is.null(rtcor)) object@scantime[sel$scanidx] else rtcor ,xcms:::colMax(object@env$profile[sel$massidx,sel$scanidx,drop=FALSE]))
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21 #plotChrom(xcmsRaw(file), base=T)
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22 }
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23
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24 #@author Y. Guitton
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25 getBPCs <- function (xcmsSet=NULL, pdfname="BPCs.pdf",rt=c("raw","corrected"), scanrange=NULL) {
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26 cat("Creating BIC pdf...\n")
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27
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28 if (is.null(xcmsSet)) {
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29 cat("Enter an xcmsSet \n")
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30 stop()
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31 } else {
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32 files <- filepaths(xcmsSet)
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33 }
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34
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35 class<-as.vector(levels(xcmsSet@phenoData[,1])) #sometime phenoData have more than 1 column use first as class
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36
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37 classnames<-vector("list",length(class))
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38 for (i in 1:length(class)){
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39 classnames[[i]]<-which( xcmsSet@phenoData[,1]==class[i])
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40 }
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41
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42 N <- dim(phenoData(xcmsSet))[1]
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43
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44 TIC <- vector("list",N)
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46
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47 for (j in 1:N) {
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48
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49 TIC[[j]] <- getBPC(files[j])
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50 #good for raw
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51 # seems strange for corrected
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52 #errors if scanrange used in xcmsSetgeneration
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53 if (!is.null(xcmsSet) && rt == "corrected")
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54 rtcor <- xcmsSet@rt$corrected[[j]] else
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55 rtcor <- NULL
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56
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57 TIC[[j]] <- getBPC(files[j],rtcor=rtcor)
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58 # TIC[[j]][,1]<-rtcor
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59 }
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62
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63 pdf(pdfname,w=16,h=10)
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64 cols <- rainbow(N)
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65 lty = 1:N
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66 pch = 1:N
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67 #search for max x and max y in BPCs
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68 xlim = range(sapply(TIC, function(x) range(x[,1])))
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69 ylim = range(sapply(TIC, function(x) range(x[,2])))
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70 ylim = c(-ylim[2], ylim[2])
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71
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72
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73 ##plot start
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74
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75 if (length(class)>2){
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76 for (k in 1:(length(class)-1)){
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77 for (l in (k+1):length(class)){
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78 #print(paste(class[k],"vs",class[l],sep=" "))
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79 plot(0, 0, type="n", xlim = xlim/60, ylim = ylim, main = paste("Base Peak Chromatograms \n","BPCs_",class[k]," vs ",class[l], sep=""), xlab = "Retention Time (min)", ylab = "BPC")
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80 colvect<-NULL
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81 for (j in 1:length(classnames[[k]])) {
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82 tic <- TIC[[classnames[[k]][j]]]
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83 # points(tic[,1]/60, tic[,2], col = cols[i], pch = pch[i], type="l")
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84 points(tic[,1]/60, tic[,2], col = cols[classnames[[k]][j]], pch = pch[classnames[[k]][j]], type="l")
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85 colvect<-append(colvect,cols[classnames[[k]][j]])
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86 }
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87 for (j in 1:length(classnames[[l]])) {
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88 # i=class2names[j]
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89 tic <- TIC[[classnames[[l]][j]]]
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90 points(tic[,1]/60, -tic[,2], col = cols[classnames[[l]][j]], pch = pch[classnames[[l]][j]], type="l")
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91 colvect<-append(colvect,cols[classnames[[l]][j]])
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92 }
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93 legend("topright",paste(basename(files[c(classnames[[k]],classnames[[l]])])), col = colvect, lty = lty, pch = pch)
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94 }
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95 }
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96 }#end if length >2
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97
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98 if (length(class)==2){
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99 k=1
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100 l=2
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101 colvect<-NULL
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102 plot(0, 0, type="n", xlim = xlim/60, ylim = ylim, main = paste("Base Peak Chromatograms \n","BPCs_",class[k],"vs",class[l], sep=""), xlab = "Retention Time (min)", ylab = "BPC")
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103
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104 for (j in 1:length(classnames[[k]])) {
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105
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106 tic <- TIC[[classnames[[k]][j]]]
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107 # points(tic[,1]/60, tic[,2], col = cols[i], pch = pch[i], type="l")
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108 points(tic[,1]/60, tic[,2], col = cols[classnames[[k]][j]], pch = pch[classnames[[k]][j]], type="l")
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109 colvect<-append(colvect,cols[classnames[[k]][j]])
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110 }
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111 for (j in 1:length(classnames[[l]])) {
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112 # i=class2names[j]
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113 tic <- TIC[[classnames[[l]][j]]]
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114 points(tic[,1]/60, -tic[,2], col = cols[classnames[[l]][j]], pch = pch[classnames[[l]][j]], type="l")
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115 colvect<-append(colvect,cols[classnames[[l]][j]])
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116 }
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117 legend("topright",paste(basename(files[c(classnames[[k]],classnames[[l]])])), col = colvect, lty = lty, pch = pch)
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118
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119 }#end length ==2
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120
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121 #case where only one class
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122 if (length(class)==1){
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123 k=1
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124 ylim = range(sapply(TIC, function(x) range(x[,2])))
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125 colvect<-NULL
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126 plot(0, 0, type="n", xlim = xlim/60, ylim = ylim, main = paste("Base Peak Chromatograms \n","BPCs_",class[k], sep=""), xlab = "Retention Time (min)", ylab = "BPC")
5
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127
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128 for (j in 1:length(classnames[[k]])) {
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129 tic <- TIC[[classnames[[k]][j]]]
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130 # points(tic[,1]/60, tic[,2], col = cols[i], pch = pch[i], type="l")
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131 points(tic[,1]/60, tic[,2], col = cols[classnames[[k]][j]], pch = pch[classnames[[k]][j]], type="l")
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132 colvect<-append(colvect,cols[classnames[[k]][j]])
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133 }
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134
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135 legend("topright",paste(basename(files[c(classnames[[k]])])), col = colvect, lty = lty, pch = pch)
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136
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137 }#end length ==1
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138
5
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139 dev.off() #pdf(pdfname,w=16,h=10)
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140
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141 invisible(TIC)
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142 }
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143
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144
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145
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146 #@author Y. Guitton
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147 getTIC <- function(file,rtcor=NULL) {
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148 object <- xcmsRaw(file)
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149 cbind(if (is.null(rtcor)) object@scantime else rtcor, rawEIC(object,mzrange=range(object@env$mz))$intensity)
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150 }
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151
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152 ##
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153 ## overlay TIC from all files in current folder or from xcmsSet, create pdf
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154 ##
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155 #@author Y. Guitton
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156 getTICs <- function(xcmsSet=NULL,files=NULL, pdfname="TICs.pdf",rt=c("raw","corrected")) {
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157 cat("Creating TIC pdf...\n")
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158
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159 if (is.null(xcmsSet)) {
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160 filepattern <- c("[Cc][Dd][Ff]", "[Nn][Cc]", "([Mm][Zz])?[Xx][Mm][Ll]", "[Mm][Zz][Dd][Aa][Tt][Aa]", "[Mm][Zz][Mm][Ll]")
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161 filepattern <- paste(paste("\\.", filepattern, "$", sep = ""), collapse = "|")
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162 if (is.null(files))
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163 files <- getwd()
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164 info <- file.info(files)
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165 listed <- list.files(files[info$isdir], pattern = filepattern, recursive = TRUE, full.names = TRUE)
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166 files <- c(files[!info$isdir], listed)
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167 } else {
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168 files <- filepaths(xcmsSet)
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169 }
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170
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171 class<-as.vector(levels(xcmsSet@phenoData[,1])) #sometime phenoData have more than 1 column use first as class
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172
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173 classnames<-vector("list",length(class))
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174 for (i in 1:length(class)){
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175 classnames[[i]]<-which( xcmsSet@phenoData[,1]==class[i])
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176 }
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177
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178 N <- length(files)
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179 TIC <- vector("list",N)
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180
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181 for (i in 1:N) {
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182 if (!is.null(xcmsSet) && rt == "corrected")
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183 rtcor <- xcmsSet@rt$corrected[[i]] else
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184 rtcor <- NULL
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185 TIC[[i]] <- getTIC(files[i],rtcor=rtcor)
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186 }
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187
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188 pdf(pdfname,w=16,h=10)
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189 cols <- rainbow(N)
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190 lty = 1:N
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191 pch = 1:N
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192 #search for max x and max y in TICs
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193 xlim = range(sapply(TIC, function(x) range(x[,1])))
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194 ylim = range(sapply(TIC, function(x) range(x[,2])))
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195 ylim = c(-ylim[2], ylim[2])
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196
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197
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198 ##plot start
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199 if (length(class)>2){
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200 for (k in 1:(length(class)-1)){
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201 for (l in (k+1):length(class)){
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202 #print(paste(class[k],"vs",class[l],sep=" "))
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203 plot(0, 0, type="n", xlim = xlim/60, ylim = ylim, main = paste("Total Ion Chromatograms \n","TICs_",class[k]," vs ",class[l], sep=""), xlab = "Retention Time (min)", ylab = "TIC")
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204 colvect<-NULL
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205 for (j in 1:length(classnames[[k]])) {
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206
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207 tic <- TIC[[classnames[[k]][j]]]
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208 # points(tic[,1]/60, tic[,2], col = cols[i], pch = pch[i], type="l")
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209 points(tic[,1]/60, tic[,2], col = cols[classnames[[k]][j]], pch = pch[classnames[[k]][j]], type="l")
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210 colvect<-append(colvect,cols[classnames[[k]][j]])
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211 }
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212 for (j in 1:length(classnames[[l]])) {
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213 # i=class2names[j]
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214 tic <- TIC[[classnames[[l]][j]]]
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215 points(tic[,1]/60, -tic[,2], col = cols[classnames[[l]][j]], pch = pch[classnames[[l]][j]], type="l")
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216 colvect<-append(colvect,cols[classnames[[l]][j]])
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217 }
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218 legend("topright",paste(basename(files[c(classnames[[k]],classnames[[l]])])), col = colvect, lty = lty, pch = pch)
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219 }
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220 }
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221 }#end if length >2
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222 if (length(class)==2){
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223 k=1
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224 l=2
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225
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226 plot(0, 0, type="n", xlim = xlim/60, ylim = ylim, main = paste("Total Ion Chromatograms \n","TICs_",class[k],"vs",class[l], sep=""), xlab = "Retention Time (min)", ylab = "TIC")
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227 colvect<-NULL
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228 for (j in 1:length(classnames[[k]])) {
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229 tic <- TIC[[classnames[[k]][j]]]
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230 # points(tic[,1]/60, tic[,2], col = cols[i], pch = pch[i], type="l")
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231 points(tic[,1]/60, tic[,2], col = cols[classnames[[k]][j]], pch = pch[classnames[[k]][j]], type="l")
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232 colvect<-append(colvect,cols[classnames[[k]][j]])
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233 }
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234 for (j in 1:length(classnames[[l]])) {
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235 # i=class2names[j]
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236 tic <- TIC[[classnames[[l]][j]]]
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237 points(tic[,1]/60, -tic[,2], col = cols[classnames[[l]][j]], pch = pch[classnames[[l]][j]], type="l")
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238 colvect<-append(colvect,cols[classnames[[l]][j]])
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239 }
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240 legend("topright",paste(basename(files[c(classnames[[k]],classnames[[l]])])), col = colvect, lty = lty, pch = pch)
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241
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242 }#end length ==2
15
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243
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244 #case where only one class
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245 if (length(class)==1){
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246 k=1
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247 ylim = range(sapply(TIC, function(x) range(x[,2])))
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248
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249 plot(0, 0, type="n", xlim = xlim/60, ylim = ylim, main = paste("Total Ion Chromatograms \n","TICs_",class[k], sep=""), xlab = "Retention Time (min)", ylab = "TIC")
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250 colvect<-NULL
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251 for (j in 1:length(classnames[[k]])) {
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252 tic <- TIC[[classnames[[k]][j]]]
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253 # points(tic[,1]/60, tic[,2], col = cols[i], pch = pch[i], type="l")
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254 points(tic[,1]/60, tic[,2], col = cols[classnames[[k]][j]], pch = pch[classnames[[k]][j]], type="l")
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255 colvect<-append(colvect,cols[classnames[[k]][j]])
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256 }
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257
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258 legend("topright",paste(basename(files[c(classnames[[k]])])), col = colvect, lty = lty, pch = pch)
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259
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260 }#end length ==1
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261
5
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262 dev.off() #pdf(pdfname,w=16,h=10)
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263
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264 invisible(TIC)
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265 }
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266
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267
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268
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269 ##
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270 ## Get the polarities from all the samples of a condition
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271 #@author Misharl Monsoor misharl.monsoor@sb-roscoff.fr ABiMS TEAM
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272 #@author Gildas Le Corguille lecorguille@sb-roscoff.fr ABiMS TEAM
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273 getSampleMetadata <- function(xcmsSet=NULL, sampleMetadataOutput="sampleMetadata.tsv") {
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274 cat("Creating the sampleMetadata file...\n")
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275
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276 #Create the sampleMetada dataframe
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277 sampleMetadata=xset@phenoData
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278 sampleNamesOrigin=rownames(sampleMetadata)
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279 sampleNamesMakeNames=make.names(sampleNamesOrigin)
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280
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281 if (any(duplicated(sampleNamesMakeNames))) {
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282 write("\n\nERROR: Usually, R has trouble to deal with special characters in its column names, so it rename them using make.names().\nIn your case, at least two columns after the renaming obtain the same name, thus XCMS will collapse those columns per name.", stderr())
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283 for (sampleName in sampleNamesOrigin) {
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284 write(paste(sampleName,"\t->\t",make.names(sampleName)),stderr())
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285 }
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286 stop("\n\nERROR: One or more of your files will not be import by xcmsSet. It may due to bad characters in their filenames.")
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287 }
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288
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289 if (!all(sampleNamesOrigin == sampleNamesMakeNames)) {
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290 cat("\n\nWARNING: Usually, R has trouble to deal with special characters in its column names, so it rename them using make.names()\nIn your case, one or more sample names will be renamed in the sampleMetadata and dataMatrix files:\n")
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291 for (sampleName in sampleNamesOrigin) {
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292 cat(paste(sampleName,"\t->\t",make.names(sampleName),"\n"))
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293 }
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294 }
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295
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296 sampleMetadata$sampleMetadata=sampleNamesMakeNames
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297 sampleMetadata=cbind(sampleMetadata["sampleMetadata"],sampleMetadata["class"]) #Reorder columns
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298 rownames(sampleMetadata)=NULL
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299
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300 #Create a list of files name in the current directory
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301 list_files=xset@filepaths
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302 #For each sample file, the following actions are done
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303 for (file in list_files){
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304 #Check if the file is in the CDF format
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305 if (!mzR:::netCDFIsFile(file)){
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306
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307 # If the column isn't exist, with add one filled with NA
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308 if (is.null(sampleMetadata$polarity)) sampleMetadata$polarity=NA
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309
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310 #Create a simple xcmsRaw object for each sample
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311 xcmsRaw=xcmsRaw(file)
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312 #Extract the polarity (a list of polarities)
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313 polarity=xcmsRaw@polarity
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314 #Verify if all the scans have the same polarity
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315 uniq_list=unique(polarity)
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316 if (length(uniq_list)>1){
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317 polarity="mixed"
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318 } else {
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319 polarity=as.character(uniq_list)
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320 }
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321 #Transforms the character to obtain only the sample name
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322 filename=basename(file)
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323 library(tools)
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324 samplename=file_path_sans_ext(filename)
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325
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326 #Set the polarity attribute
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327 sampleMetadata$polarity[sampleMetadata$sampleMetadata==samplename]=polarity
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328
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329 #Delete xcmsRaw object because it creates a bug for the fillpeaks step
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330 rm(xcmsRaw)
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331 }
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332
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333 }
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334
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335 write.table(sampleMetadata, sep="\t", quote=FALSE, row.names=FALSE, file=sampleMetadataOutput)
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336
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337 return(list("sampleNamesOrigin"=sampleNamesOrigin,"sampleNamesMakeNames"=sampleNamesMakeNames))
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338
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339 }
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340
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341
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342 ##
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343 ## This function check if xcms will found all the files
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344 ##
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345 #@author Gildas Le Corguille lecorguille@sb-roscoff.fr ABiMS TEAM
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346 checkFilesCompatibilityWithXcms <- function(directory) {
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347 cat("Checking files filenames compatibilities with xmcs...\n")
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348 # WHAT XCMS WILL FIND
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349 filepattern <- c("[Cc][Dd][Ff]", "[Nn][Cc]", "([Mm][Zz])?[Xx][Mm][Ll]","[Mm][Zz][Dd][Aa][Tt][Aa]", "[Mm][Zz][Mm][Ll]")
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350 filepattern <- paste(paste("\\.", filepattern, "$", sep = ""),collapse = "|")
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351 info <- file.info(directory)
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352 listed <- list.files(directory[info$isdir], pattern = filepattern,recursive = TRUE, full.names = TRUE)
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353 files <- c(directory[!info$isdir], listed)
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354 files_abs <- file.path(getwd(), files)
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355 exists <- file.exists(files_abs)
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356 files[exists] <- files_abs[exists]
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357 files[exists] <- sub("//","/",files[exists])
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358
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359 # WHAT IS ON THE FILESYSTEM
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360 filesystem_filepaths=system(paste("find $PWD/",directory," -not -name '\\.*' -not -path '*conda-env*' -type f -name \"*\"", sep=""), intern=T)
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361 filesystem_filepaths=filesystem_filepaths[grep(filepattern, filesystem_filepaths, perl=T)]
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362
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363 # COMPARISON
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364 if (!is.na(table(filesystem_filepaths %in% files)["FALSE"])) {
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365 write("\n\nERROR: List of the files which will not be imported by xcmsSet",stderr())
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366 write(filesystem_filepaths[!(filesystem_filepaths %in% files)],stderr())
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367 stop("\n\nERROR: One or more of your files will not be import by xcmsSet. It may due to bad characters in their filenames.")
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368
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369 }
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370 }
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371
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372
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373
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374 ##
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375 ## This function check if XML contains special caracters. It also checks integrity and completness.
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376 ##
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377 #@author Misharl Monsoor misharl.monsoor@sb-roscoff.fr ABiMS TEAM
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378 checkXmlStructure <- function (directory) {
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379 cat("Checking XML structure...\n")
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380
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381 cmd=paste("IFS=$'\n'; for xml in $(find",directory,"-not -name '\\.*' -not -path '*conda-env*' -type f -iname '*.*ml*'); do if [ $(xmllint --nonet --noout \"$xml\" 2> /dev/null; echo $?) -gt 0 ]; then echo $xml;fi; done;")
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382 capture=system(cmd,intern=TRUE)
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383
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384 if (length(capture)>0){
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385 #message=paste("The following mzXML or mzML file is incorrect, please check these files first:",capture)
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386 write("\n\nERROR: The following mzXML or mzML file(s) are incorrect, please check these files first:", stderr())
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387 write(capture, stderr())
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388 stop("ERROR: xcmsSet cannot continue with incorrect mzXML or mzML files")
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389 }
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390
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391 }
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392
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393
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394 ##
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395 ## This function check if XML contain special characters
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396 ##
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397 #@author Misharl Monsoor misharl.monsoor@sb-roscoff.fr ABiMS TEAM
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398 deleteXmlBadCharacters<- function (directory) {
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399 cat("Checking Non ASCII characters in the XML...\n")
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400
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401 processed=F
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402 l=system( paste("find",directory, "-not -name '\\.*' -not -path '*conda-env*' -type f -iname '*.*ml*'"),intern=TRUE)
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403 for (i in l){
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404 cmd=paste("LC_ALL=C grep '[^ -~]' \"",i,"\"",sep="")
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405 capture=suppressWarnings(system(cmd,intern=TRUE))
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406 if (length(capture)>0){
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407 cmd=paste("perl -i -pe 's/[^[:ascii:]]//g;'",i)
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408 print( paste("WARNING: Non ASCII characters have been removed from the ",i,"file") )
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409 c=system(cmd,intern=TRUE)
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410 capture=""
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411 processed=T
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412 }
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413 }
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414 if (processed) cat("\n\n")
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415 return(processed)
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416 }
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417
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418
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419 ##
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420 ## This function will compute MD5 checksum to check the data integrity
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421 ##
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422 #@author Gildas Le Corguille lecorguille@sb-roscoff.fr
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423 getMd5sum <- function (directory) {
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424 cat("Compute md5 checksum...\n")
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425 # WHAT XCMS WILL FIND
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426 filepattern <- c("[Cc][Dd][Ff]", "[Nn][Cc]", "([Mm][Zz])?[Xx][Mm][Ll]","[Mm][Zz][Dd][Aa][Tt][Aa]", "[Mm][Zz][Mm][Ll]")
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lecorguille
parents:
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427 filepattern <- paste(paste("\\.", filepattern, "$", sep = ""),collapse = "|")
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lecorguille
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428 info <- file.info(directory)
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lecorguille
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429 listed <- list.files(directory[info$isdir], pattern = filepattern,recursive = TRUE, full.names = TRUE)
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lecorguille
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430 files <- c(directory[!info$isdir], listed)
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lecorguille
parents:
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431 exists <- file.exists(files)
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lecorguille
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432 files <- files[exists]
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lecorguille
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433
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lecorguille
parents:
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434 library(tools)
b9a87af62223 planemo upload commit 5a5b747865d7fb76f711bce2d9ce2a0f82a2a374-dirty
lecorguille
parents:
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435
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lecorguille
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436 #cat("\n\n")
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lecorguille
parents:
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437
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lecorguille
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438 return(as.matrix(md5sum(files)))
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lecorguille
parents:
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439 }
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lecorguille
parents:
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440