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annotate lib.r @ 19:2faecb1270fe draft

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planemo upload for repository https://github.com/workflow4metabolomics/xcms commit 481448087f0e09c131b24f7d552db69f3552d371-dirty
author lecorguille
date Wed, 08 Feb 2017 06:35:43 -0500
parents 8e740205c907
children 411d2b9ea412
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1 #Authors ABiMS TEAM
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2 #Lib.r for Galaxy Workflow4Metabolomics xcms tools
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3 #
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4 #version 2.4: lecorguille
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5 # add getPeaklistW4M
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6 #version 2.3: yguitton
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7 # correction for empty PDF when only 1 class
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8 #version 2.2
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9 # correct bug in Base Peak Chromatogram (BPC) option, not only TIC when scanrange used in xcmsSet
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10 # Note if scanrange is used a warning is prompted in R console but do not stop PDF generation
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11 #version 2.1: yguitton
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12 # Modifications made by Guitton Yann
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15 #@author G. Le Corguille
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16 #This function convert if it is required the Retention Time in minutes
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17 RTSecondToMinute <- function(variableMetadata, convertRTMinute) {
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18 if (convertRTMinute){
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19 #converting the retention times (seconds) into minutes
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20 print("converting the retention times into minutes in the variableMetadata")
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21 variableMetadata[,"rt"]=variableMetadata[,"rt"]/60
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22 variableMetadata[,"rtmin"]=variableMetadata[,"rtmin"]/60
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23 variableMetadata[,"rtmax"]=variableMetadata[,"rtmax"]/60
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24 }
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25 return (variableMetadata)
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26 }
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28 #@author G. Le Corguille
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29 #This function format ions identifiers
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30 formatIonIdentifiers <- function(variableMetadata, numDigitsRT=0, numDigitsMZ=0) {
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31 splitDeco = strsplit(as.character(variableMetadata$name),"_")
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32 idsDeco = sapply(splitDeco, function(x) { deco=unlist(x)[2]; if (is.na(deco)) return ("") else return(paste0("_",deco)) })
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33 namecustom = make.unique(paste0("M",round(variableMetadata[,"mz"],numDigitsMZ),"T",round(variableMetadata[,"rt"],numDigitsRT),idsDeco))
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34 variableMetadata=cbind(name=variableMetadata$name, namecustom=namecustom, variableMetadata[,!(colnames(variableMetadata) %in% c("name"))])
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35 return(variableMetadata)
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36 }
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38 #@author G. Le Corguille
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39 # value: intensity values to be used into, maxo or intb
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40 getPeaklistW4M <- function(xset, intval="into",convertRTMinute=F,numDigitsMZ=4,numDigitsRT=0,variableMetadataOutput,dataMatrixOutput) {
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41 variableMetadata_dataMatrix = peakTable(xset, method="medret", value=intval)
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42 variableMetadata_dataMatrix = cbind(name=groupnames(xset),variableMetadata_dataMatrix)
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44 dataMatrix = variableMetadata_dataMatrix[,(make.names(colnames(variableMetadata_dataMatrix)) %in% c("name", make.names(sampnames(xset))))]
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46 variableMetadata = variableMetadata_dataMatrix[,!(make.names(colnames(variableMetadata_dataMatrix)) %in% c(make.names(sampnames(xset))))]
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47 variableMetadata = RTSecondToMinute(variableMetadata, convertRTMinute)
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48 variableMetadata = formatIonIdentifiers(variableMetadata, numDigitsRT=numDigitsRT, numDigitsMZ=numDigitsMZ)
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50 write.table(variableMetadata, file=variableMetadataOutput,sep="\t",quote=F,row.names=F)
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51 write.table(dataMatrix, file=dataMatrixOutput,sep="\t",quote=F,row.names=F)
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52 }
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54 #@author Y. Guitton
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55 getBPC <- function(file,rtcor=NULL, ...) {
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56 object <- xcmsRaw(file)
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57 sel <- profRange(object, ...)
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58 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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59 #plotChrom(xcmsRaw(file), base=T)
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60 }
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62 #@author Y. Guitton
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63 getBPCs <- function (xcmsSet=NULL, pdfname="BPCs.pdf",rt=c("raw","corrected"), scanrange=NULL) {
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64 cat("Creating BIC pdf...\n")
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65
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66 if (is.null(xcmsSet)) {
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67 cat("Enter an xcmsSet \n")
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68 stop()
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69 } else {
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70 files <- filepaths(xcmsSet)
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71 }
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73 phenoDataClass<-as.vector(levels(xcmsSet@phenoData[,1])) #sometime phenoData have more than 1 column use first as class
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75 classnames<-vector("list",length(phenoDataClass))
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76 for (i in 1:length(phenoDataClass)){
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77 classnames[[i]]<-which( xcmsSet@phenoData[,1]==phenoDataClass[i])
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78 }
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80 N <- dim(phenoData(xcmsSet))[1]
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82 TIC <- vector("list",N)
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85 for (j in 1:N) {
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87 TIC[[j]] <- getBPC(files[j])
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88 #good for raw
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89 # seems strange for corrected
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90 #errors if scanrange used in xcmsSetgeneration
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91 if (!is.null(xcmsSet) && rt == "corrected")
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92 rtcor <- xcmsSet@rt$corrected[[j]]
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93 else
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94 rtcor <- NULL
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95
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96 TIC[[j]] <- getBPC(files[j],rtcor=rtcor)
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97 # TIC[[j]][,1]<-rtcor
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98 }
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99
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100
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101
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102 pdf(pdfname,w=16,h=10)
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103 cols <- rainbow(N)
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104 lty = 1:N
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105 pch = 1:N
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106 #search for max x and max y in BPCs
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107 xlim = range(sapply(TIC, function(x) range(x[,1])))
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108 ylim = range(sapply(TIC, function(x) range(x[,2])))
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109 ylim = c(-ylim[2], ylim[2])
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110
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111
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112 ##plot start
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113
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114 if (length(phenoDataClass)>2){
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115 for (k in 1:(length(phenoDataClass)-1)){
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116 for (l in (k+1):length(phenoDataClass)){
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117 #print(paste(phenoDataClass[k],"vs",phenoDataClass[l],sep=" "))
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118 plot(0, 0, type="n", xlim = xlim/60, ylim = ylim, main = paste("Base Peak Chromatograms \n","BPCs_",phenoDataClass[k]," vs ",phenoDataClass[l], sep=""), xlab = "Retention Time (min)", ylab = "BPC")
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119 colvect<-NULL
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120 for (j in 1:length(classnames[[k]])) {
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121 tic <- TIC[[classnames[[k]][j]]]
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122 # points(tic[,1]/60, tic[,2], col = cols[i], pch = pch[i], type="l")
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123 points(tic[,1]/60, tic[,2], col = cols[classnames[[k]][j]], pch = pch[classnames[[k]][j]], type="l")
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124 colvect<-append(colvect,cols[classnames[[k]][j]])
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125 }
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126 for (j in 1:length(classnames[[l]])) {
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127 # i=class2names[j]
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128 tic <- TIC[[classnames[[l]][j]]]
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129 points(tic[,1]/60, -tic[,2], col = cols[classnames[[l]][j]], pch = pch[classnames[[l]][j]], type="l")
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130 colvect<-append(colvect,cols[classnames[[l]][j]])
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131 }
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132 legend("topright",paste(basename(files[c(classnames[[k]],classnames[[l]])])), col = colvect, lty = lty, pch = pch)
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133 }
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134 }
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135 }#end if length >2
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136
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137 if (length(phenoDataClass)==2){
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138 k=1
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139 l=2
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140 colvect<-NULL
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141 plot(0, 0, type="n", xlim = xlim/60, ylim = ylim, main = paste("Base Peak Chromatograms \n","BPCs_",phenoDataClass[k],"vs",phenoDataClass[l], sep=""), xlab = "Retention Time (min)", ylab = "BPC")
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142
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143 for (j in 1:length(classnames[[k]])) {
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144
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145 tic <- TIC[[classnames[[k]][j]]]
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146 # points(tic[,1]/60, tic[,2], col = cols[i], pch = pch[i], type="l")
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147 points(tic[,1]/60, tic[,2], col = cols[classnames[[k]][j]], pch = pch[classnames[[k]][j]], type="l")
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148 colvect<-append(colvect,cols[classnames[[k]][j]])
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149 }
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150 for (j in 1:length(classnames[[l]])) {
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151 # i=class2names[j]
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152 tic <- TIC[[classnames[[l]][j]]]
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153 points(tic[,1]/60, -tic[,2], col = cols[classnames[[l]][j]], pch = pch[classnames[[l]][j]], type="l")
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154 colvect<-append(colvect,cols[classnames[[l]][j]])
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155 }
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156 legend("topright",paste(basename(files[c(classnames[[k]],classnames[[l]])])), col = colvect, lty = lty, pch = pch)
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157
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158 }#end length ==2
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159
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160 #case where only one class
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161 if (length(phenoDataClass)==1){
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162 k=1
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163 ylim = range(sapply(TIC, function(x) range(x[,2])))
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164 colvect<-NULL
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165 plot(0, 0, type="n", xlim = xlim/60, ylim = ylim, main = paste("Base Peak Chromatograms \n","BPCs_",phenoDataClass[k], sep=""), xlab = "Retention Time (min)", ylab = "BPC")
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166
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167 for (j in 1:length(classnames[[k]])) {
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168 tic <- TIC[[classnames[[k]][j]]]
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169 # points(tic[,1]/60, tic[,2], col = cols[i], pch = pch[i], type="l")
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170 points(tic[,1]/60, tic[,2], col = cols[classnames[[k]][j]], pch = pch[classnames[[k]][j]], type="l")
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171 colvect<-append(colvect,cols[classnames[[k]][j]])
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172 }
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173
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174 legend("topright",paste(basename(files[c(classnames[[k]])])), col = colvect, lty = lty, pch = pch)
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175
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176 }#end length ==1
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177
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178 dev.off() #pdf(pdfname,w=16,h=10)
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179
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180 invisible(TIC)
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181 }
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182
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183
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184
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185 #@author Y. Guitton
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186 getTIC <- function(file,rtcor=NULL) {
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187 object <- xcmsRaw(file)
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188 cbind(if (is.null(rtcor)) object@scantime else rtcor, rawEIC(object,mzrange=range(object@env$mz))$intensity)
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189 }
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190
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191 ##
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192 ## overlay TIC from all files in current folder or from xcmsSet, create pdf
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193 ##
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194 #@author Y. Guitton
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195 getTICs <- function(xcmsSet=NULL,files=NULL, pdfname="TICs.pdf",rt=c("raw","corrected")) {
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196 cat("Creating TIC pdf...\n")
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197
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198 if (is.null(xcmsSet)) {
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199 filepattern <- c("[Cc][Dd][Ff]", "[Nn][Cc]", "([Mm][Zz])?[Xx][Mm][Ll]", "[Mm][Zz][Dd][Aa][Tt][Aa]", "[Mm][Zz][Mm][Ll]")
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200 filepattern <- paste(paste("\\.", filepattern, "$", sep = ""), collapse = "|")
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201 if (is.null(files))
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202 files <- getwd()
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203 info <- file.info(files)
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204 listed <- list.files(files[info$isdir], pattern = filepattern, recursive = TRUE, full.names = TRUE)
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205 files <- c(files[!info$isdir], listed)
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206 } else {
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207 files <- filepaths(xcmsSet)
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208 }
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209
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210 phenoDataClass<-as.vector(levels(xcmsSet@phenoData[,1])) #sometime phenoData have more than 1 column use first as class
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211 classnames<-vector("list",length(phenoDataClass))
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212 for (i in 1:length(phenoDataClass)){
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213 classnames[[i]]<-which( xcmsSet@phenoData[,1]==phenoDataClass[i])
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214 }
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215
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216 N <- length(files)
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217 TIC <- vector("list",N)
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218
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219 for (i in 1:N) {
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220 if (!is.null(xcmsSet) && rt == "corrected")
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221 rtcor <- xcmsSet@rt$corrected[[i]] else
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222 rtcor <- NULL
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223 TIC[[i]] <- getTIC(files[i],rtcor=rtcor)
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224 }
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225
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226 pdf(pdfname,w=16,h=10)
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227 cols <- rainbow(N)
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228 lty = 1:N
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229 pch = 1:N
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230 #search for max x and max y in TICs
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231 xlim = range(sapply(TIC, function(x) range(x[,1])))
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232 ylim = range(sapply(TIC, function(x) range(x[,2])))
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233 ylim = c(-ylim[2], ylim[2])
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234
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235
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236 ##plot start
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237 if (length(phenoDataClass)>2){
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238 for (k in 1:(length(phenoDataClass)-1)){
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239 for (l in (k+1):length(phenoDataClass)){
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240 #print(paste(phenoDataClass[k],"vs",phenoDataClass[l],sep=" "))
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241 plot(0, 0, type="n", xlim = xlim/60, ylim = ylim, main = paste("Total Ion Chromatograms \n","TICs_",phenoDataClass[k]," vs ",phenoDataClass[l], sep=""), xlab = "Retention Time (min)", ylab = "TIC")
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242 colvect<-NULL
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243 for (j in 1:length(classnames[[k]])) {
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244 tic <- TIC[[classnames[[k]][j]]]
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245 # points(tic[,1]/60, tic[,2], col = cols[i], pch = pch[i], type="l")
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246 points(tic[,1]/60, tic[,2], col = cols[classnames[[k]][j]], pch = pch[classnames[[k]][j]], type="l")
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247 colvect<-append(colvect,cols[classnames[[k]][j]])
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248 }
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249 for (j in 1:length(classnames[[l]])) {
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250 # i=class2names[j]
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251 tic <- TIC[[classnames[[l]][j]]]
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252 points(tic[,1]/60, -tic[,2], col = cols[classnames[[l]][j]], pch = pch[classnames[[l]][j]], type="l")
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253 colvect<-append(colvect,cols[classnames[[l]][j]])
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254 }
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255 legend("topright",paste(basename(files[c(classnames[[k]],classnames[[l]])])), col = colvect, lty = lty, pch = pch)
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256 }
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257 }
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258 }#end if length >2
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259 if (length(phenoDataClass)==2){
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260 k=1
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261 l=2
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262
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263 plot(0, 0, type="n", xlim = xlim/60, ylim = ylim, main = paste("Total Ion Chromatograms \n","TICs_",phenoDataClass[k],"vs",phenoDataClass[l], sep=""), xlab = "Retention Time (min)", ylab = "TIC")
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264 colvect<-NULL
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265 for (j in 1:length(classnames[[k]])) {
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266 tic <- TIC[[classnames[[k]][j]]]
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267 # points(tic[,1]/60, tic[,2], col = cols[i], pch = pch[i], type="l")
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268 points(tic[,1]/60, tic[,2], col = cols[classnames[[k]][j]], pch = pch[classnames[[k]][j]], type="l")
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269 colvect<-append(colvect,cols[classnames[[k]][j]])
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270 }
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271 for (j in 1:length(classnames[[l]])) {
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272 # i=class2names[j]
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273 tic <- TIC[[classnames[[l]][j]]]
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274 points(tic[,1]/60, -tic[,2], col = cols[classnames[[l]][j]], pch = pch[classnames[[l]][j]], type="l")
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275 colvect<-append(colvect,cols[classnames[[l]][j]])
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276 }
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277 legend("topright",paste(basename(files[c(classnames[[k]],classnames[[l]])])), col = colvect, lty = lty, pch = pch)
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278
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279 }#end length ==2
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280
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281 #case where only one class
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282 if (length(phenoDataClass)==1){
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283 k=1
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284 ylim = range(sapply(TIC, function(x) range(x[,2])))
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285
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286 plot(0, 0, type="n", xlim = xlim/60, ylim = ylim, main = paste("Total Ion Chromatograms \n","TICs_",phenoDataClass[k], sep=""), xlab = "Retention Time (min)", ylab = "TIC")
20a75ba4345b planemo upload for repository https://github.com/workflow4metabolomics/xcms commit 22c4e92909198328fc7439ff47e4546a273eb907
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287 colvect<-NULL
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288 for (j in 1:length(classnames[[k]])) {
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289 tic <- TIC[[classnames[[k]][j]]]
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290 # points(tic[,1]/60, tic[,2], col = cols[i], pch = pch[i], type="l")
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291 points(tic[,1]/60, tic[,2], col = cols[classnames[[k]][j]], pch = pch[classnames[[k]][j]], type="l")
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292 colvect<-append(colvect,cols[classnames[[k]][j]])
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293 }
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294
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295 legend("topright",paste(basename(files[c(classnames[[k]])])), col = colvect, lty = lty, pch = pch)
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296
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297 }#end length ==1
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298
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299 dev.off() #pdf(pdfname,w=16,h=10)
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300
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301 invisible(TIC)
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302 }
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303
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304
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305
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306 ##
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307 ## Get the polarities from all the samples of a condition
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308 #@author Misharl Monsoor misharl.monsoor@sb-roscoff.fr ABiMS TEAM
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309 #@author Gildas Le Corguille lecorguille@sb-roscoff.fr ABiMS TEAM
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310 getSampleMetadata <- function(xcmsSet=NULL, sampleMetadataOutput="sampleMetadata.tsv") {
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311 cat("Creating the sampleMetadata file...\n")
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312
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313 #Create the sampleMetada dataframe
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314 sampleMetadata=xset@phenoData
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315 sampleNamesOrigin=rownames(sampleMetadata)
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316 sampleNamesMakeNames=make.names(sampleNamesOrigin)
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317
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318 if (any(duplicated(sampleNamesMakeNames))) {
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319 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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320 for (sampleName in sampleNamesOrigin) {
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321 write(paste(sampleName,"\t->\t",make.names(sampleName)),stderr())
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322 }
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323 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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324 }
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325
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326 if (!all(sampleNamesOrigin == sampleNamesMakeNames)) {
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327 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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328 for (sampleName in sampleNamesOrigin) {
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329 cat(paste(sampleName,"\t->\t",make.names(sampleName),"\n"))
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330 }
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331 }
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332
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333 sampleMetadata$sampleMetadata=sampleNamesMakeNames
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334 sampleMetadata=cbind(sampleMetadata["sampleMetadata"],sampleMetadata["class"]) #Reorder columns
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335 rownames(sampleMetadata)=NULL
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336
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337 #Create a list of files name in the current directory
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338 list_files=xset@filepaths
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339 #For each sample file, the following actions are done
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340 for (file in list_files){
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341 #Check if the file is in the CDF format
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342 if (!mzR:::netCDFIsFile(file)){
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343
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344 # If the column isn't exist, with add one filled with NA
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345 if (is.null(sampleMetadata$polarity)) sampleMetadata$polarity=NA
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346
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347 #Create a simple xcmsRaw object for each sample
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348 xcmsRaw=xcmsRaw(file)
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349 #Extract the polarity (a list of polarities)
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350 polarity=xcmsRaw@polarity
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351 #Verify if all the scans have the same polarity
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352 uniq_list=unique(polarity)
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353 if (length(uniq_list)>1){
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354 polarity="mixed"
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355 } else {
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356 polarity=as.character(uniq_list)
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357 }
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358 #Transforms the character to obtain only the sample name
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359 filename=basename(file)
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360 library(tools)
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361 samplename=file_path_sans_ext(filename)
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362
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363 #Set the polarity attribute
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364 sampleMetadata$polarity[sampleMetadata$sampleMetadata==samplename]=polarity
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365
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366 #Delete xcmsRaw object because it creates a bug for the fillpeaks step
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367 rm(xcmsRaw)
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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 write.table(sampleMetadata, sep="\t", quote=FALSE, row.names=FALSE, file=sampleMetadataOutput)
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373
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374 return(list("sampleNamesOrigin"=sampleNamesOrigin,"sampleNamesMakeNames"=sampleNamesMakeNames))
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375
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376 }
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377
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378
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379 ##
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380 ## This function check if xcms will found all the files
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381 ##
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382 #@author Gildas Le Corguille lecorguille@sb-roscoff.fr ABiMS TEAM
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383 checkFilesCompatibilityWithXcms <- function(directory) {
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384 cat("Checking files filenames compatibilities with xmcs...\n")
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385 # WHAT XCMS WILL FIND
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386 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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387 filepattern <- paste(paste("\\.", filepattern, "$", sep = ""),collapse = "|")
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388 info <- file.info(directory)
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389 listed <- list.files(directory[info$isdir], pattern = filepattern,recursive = TRUE, full.names = TRUE)
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390 files <- c(directory[!info$isdir], listed)
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391 files_abs <- file.path(getwd(), files)
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392 exists <- file.exists(files_abs)
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393 files[exists] <- files_abs[exists]
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394 files[exists] <- sub("//","/",files[exists])
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395
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396 # WHAT IS ON THE FILESYSTEM
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397 filesystem_filepaths=system(paste("find $PWD/",directory," -not -name '\\.*' -not -path '*conda-env*' -type f -name \"*\"", sep=""), intern=T)
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398 filesystem_filepaths=filesystem_filepaths[grep(filepattern, filesystem_filepaths, perl=T)]
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399
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400 # COMPARISON
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401 if (!is.na(table(filesystem_filepaths %in% files)["FALSE"])) {
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402 write("\n\nERROR: List of the files which will not be imported by xcmsSet",stderr())
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403 write(filesystem_filepaths[!(filesystem_filepaths %in% files)],stderr())
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404 stop("\n\nERROR: One or more of your files will not be import by xcmsSet. It may due to bad characters in their filenames.")
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405 }
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406 }
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407
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408
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409
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410 ##
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411 ## This function check if XML contains special caracters. It also checks integrity and completness.
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412 ##
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413 #@author Misharl Monsoor misharl.monsoor@sb-roscoff.fr ABiMS TEAM
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414 checkXmlStructure <- function (directory) {
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415 cat("Checking XML structure...\n")
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416
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417 cmd=paste("IFS=$'\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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418 capture=system(cmd,intern=TRUE)
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419
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420 if (length(capture)>0){
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421 #message=paste("The following mzXML or mzML file is incorrect, please check these files first:",capture)
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422 write("\n\nERROR: The following mzXML or mzML file(s) are incorrect, please check these files first:", stderr())
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423 write(capture, stderr())
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424 stop("ERROR: xcmsSet cannot continue with incorrect mzXML or mzML files")
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425 }
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426
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427 }
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428
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429
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430 ##
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431 ## This function check if XML contain special characters
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432 ##
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433 #@author Misharl Monsoor misharl.monsoor@sb-roscoff.fr ABiMS TEAM
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434 deleteXmlBadCharacters<- function (directory) {
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435 cat("Checking Non ASCII characters in the XML...\n")
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436
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437 processed=F
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438 l=system( paste("find",directory, "-not -name '\\.*' -not -path '*conda-env*' -type f -iname '*.*ml*'"),intern=TRUE)
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439 for (i in l){
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440 cmd=paste("LC_ALL=C grep '[^ -~]' \"",i,"\"",sep="")
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441 capture=suppressWarnings(system(cmd,intern=TRUE))
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442 if (length(capture)>0){
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443 cmd=paste("perl -i -pe 's/[^[:ascii:]]//g;'",i)
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444 print( paste("WARNING: Non ASCII characters have been removed from the ",i,"file") )
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445 c=system(cmd,intern=TRUE)
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446 capture=""
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447 processed=T
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448 }
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449 }
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450 if (processed) cat("\n\n")
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451 return(processed)
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452 }
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453
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454
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455 ##
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456 ## This function will compute MD5 checksum to check the data integrity
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457 ##
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458 #@author Gildas Le Corguille lecorguille@sb-roscoff.fr
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459 getMd5sum <- function (directory) {
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460 cat("Compute md5 checksum...\n")
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461 # WHAT XCMS WILL FIND
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462 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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463 filepattern <- paste(paste("\\.", filepattern, "$", sep = ""),collapse = "|")
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464 info <- file.info(directory)
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465 listed <- list.files(directory[info$isdir], pattern = filepattern,recursive = TRUE, full.names = TRUE)
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466 files <- c(directory[!info$isdir], listed)
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467 exists <- file.exists(files)
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468 files <- files[exists]
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469
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470 library(tools)
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471
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472 #cat("\n\n")
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473
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474 return(as.matrix(md5sum(files)))
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475 }