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annotate lib.r @ 15:c04568596f40 draft

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planemo upload for repository https://github.com/workflow4metabolomics/xcms commit 08e7f269a5c59687a7768be8db5fcb4e4d736093
author lecorguille
date Mon, 30 Jan 2017 08:51:40 -0500
parents 55923d170538
children 20a75ba4345b
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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(dataData, numDigitsRT=0, numDigitsMZ=0) {
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31 return(make.unique(paste0("M",round(dataData[,"mz"],numDigitsMZ),"T",round(dataData[,"rt"],numDigitsRT))))
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32 }
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34 #@author G. Le Corguille
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35 # value: intensity values to be used into, maxo or intb
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36 getPeaklistW4M <- function(xset, intval="into",convertRTMinute=F,numDigitsMZ=4,numDigitsRT=0,variableMetadataOutput,dataMatrixOutput) {
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37 groups <- xset@groups
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38 values <- groupval(xset, "medret", value=intval)
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40 # renamming of the column rtmed to rt to fit with camera peaklist function output
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41 colnames(groups)[colnames(groups)=="rtmed"] <- "rt"
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42 colnames(groups)[colnames(groups)=="mzmed"] <- "mz"
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44 ids <- formatIonIdentifiers(groups, numDigitsRT=numDigitsRT, numDigitsMZ=numDigitsMZ)
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45 groups = RTSecondToMinute(groups, convertRTMinute)
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47 rownames(groups) = ids
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48 rownames(values) = ids
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50 #@TODO: add "name" as the first column name
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51 #colnames(groups)[1] = "name"
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52 #colnames(values)[1] = "name"
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54 write.table(groups, file=variableMetadataOutput,sep="\t",quote=F,row.names = T,col.names = NA)
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55 write.table(values, file=dataMatrixOutput,sep="\t",quote=F,row.names = T,col.names = NA)
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56 }
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58 #@author Y. Guitton
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59 getBPC <- function(file,rtcor=NULL, ...) {
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60 object <- xcmsRaw(file)
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61 sel <- profRange(object, ...)
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62 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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63 #plotChrom(xcmsRaw(file), base=T)
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64 }
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65
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66 #@author Y. Guitton
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67 getBPCs <- function (xcmsSet=NULL, pdfname="BPCs.pdf",rt=c("raw","corrected"), scanrange=NULL) {
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68 cat("Creating BIC pdf...\n")
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69
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70 if (is.null(xcmsSet)) {
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71 cat("Enter an xcmsSet \n")
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72 stop()
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73 } else {
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74 files <- filepaths(xcmsSet)
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75 }
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77 class<-as.vector(levels(xcmsSet@phenoData[,1])) #sometime phenoData have more than 1 column use first as class
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78
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79 classnames<-vector("list",length(class))
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80 for (i in 1:length(class)){
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81 classnames[[i]]<-which( xcmsSet@phenoData[,1]==class[i])
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82 }
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83
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84 N <- dim(phenoData(xcmsSet))[1]
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85
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86 TIC <- vector("list",N)
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89 for (j in 1:N) {
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90
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91 TIC[[j]] <- getBPC(files[j])
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92 #good for raw
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93 # seems strange for corrected
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94 #errors if scanrange used in xcmsSetgeneration
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95 if (!is.null(xcmsSet) && rt == "corrected")
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96 rtcor <- xcmsSet@rt$corrected[[j]] else
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97 rtcor <- NULL
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98
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99 TIC[[j]] <- getBPC(files[j],rtcor=rtcor)
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100 # TIC[[j]][,1]<-rtcor
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101 }
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102
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105 pdf(pdfname,w=16,h=10)
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106 cols <- rainbow(N)
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107 lty = 1:N
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108 pch = 1:N
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109 #search for max x and max y in BPCs
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110 xlim = range(sapply(TIC, function(x) range(x[,1])))
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111 ylim = range(sapply(TIC, function(x) range(x[,2])))
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112 ylim = c(-ylim[2], ylim[2])
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113
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114
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115 ##plot start
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116
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117 if (length(class)>2){
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118 for (k in 1:(length(class)-1)){
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119 for (l in (k+1):length(class)){
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120 #print(paste(class[k],"vs",class[l],sep=" "))
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121 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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122 colvect<-NULL
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123 for (j in 1:length(classnames[[k]])) {
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124 tic <- TIC[[classnames[[k]][j]]]
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125 # points(tic[,1]/60, tic[,2], col = cols[i], pch = pch[i], type="l")
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126 points(tic[,1]/60, tic[,2], col = cols[classnames[[k]][j]], pch = pch[classnames[[k]][j]], type="l")
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127 colvect<-append(colvect,cols[classnames[[k]][j]])
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128 }
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129 for (j in 1:length(classnames[[l]])) {
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130 # i=class2names[j]
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131 tic <- TIC[[classnames[[l]][j]]]
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132 points(tic[,1]/60, -tic[,2], col = cols[classnames[[l]][j]], pch = pch[classnames[[l]][j]], type="l")
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133 colvect<-append(colvect,cols[classnames[[l]][j]])
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134 }
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135 legend("topright",paste(basename(files[c(classnames[[k]],classnames[[l]])])), col = colvect, lty = lty, pch = pch)
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136 }
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137 }
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138 }#end if length >2
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139
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140 if (length(class)==2){
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141 k=1
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142 l=2
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143 colvect<-NULL
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144 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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145
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146 for (j in 1:length(classnames[[k]])) {
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147
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148 tic <- TIC[[classnames[[k]][j]]]
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149 # points(tic[,1]/60, tic[,2], col = cols[i], pch = pch[i], type="l")
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150 points(tic[,1]/60, tic[,2], col = cols[classnames[[k]][j]], pch = pch[classnames[[k]][j]], type="l")
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151 colvect<-append(colvect,cols[classnames[[k]][j]])
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152 }
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153 for (j in 1:length(classnames[[l]])) {
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154 # i=class2names[j]
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155 tic <- TIC[[classnames[[l]][j]]]
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156 points(tic[,1]/60, -tic[,2], col = cols[classnames[[l]][j]], pch = pch[classnames[[l]][j]], type="l")
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157 colvect<-append(colvect,cols[classnames[[l]][j]])
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158 }
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159 legend("topright",paste(basename(files[c(classnames[[k]],classnames[[l]])])), col = colvect, lty = lty, pch = pch)
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160
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161 }#end length ==2
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162
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163 #case where only one class
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164 if (length(class)==1){
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165 k=1
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166 ylim = range(sapply(TIC, function(x) range(x[,2])))
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167 colvect<-NULL
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168 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")
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169
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170 for (j in 1:length(classnames[[k]])) {
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171 tic <- TIC[[classnames[[k]][j]]]
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172 # points(tic[,1]/60, tic[,2], col = cols[i], pch = pch[i], type="l")
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173 points(tic[,1]/60, tic[,2], col = cols[classnames[[k]][j]], pch = pch[classnames[[k]][j]], type="l")
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174 colvect<-append(colvect,cols[classnames[[k]][j]])
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175 }
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176
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177 legend("topright",paste(basename(files[c(classnames[[k]])])), col = colvect, lty = lty, pch = pch)
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178
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179 }#end length ==1
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180
6
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181 dev.off() #pdf(pdfname,w=16,h=10)
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182
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183 invisible(TIC)
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184 }
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185
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186
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187
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188 #@author Y. Guitton
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189 getTIC <- function(file,rtcor=NULL) {
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190 object <- xcmsRaw(file)
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191 cbind(if (is.null(rtcor)) object@scantime else rtcor, rawEIC(object,mzrange=range(object@env$mz))$intensity)
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192 }
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193
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194 ##
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195 ## overlay TIC from all files in current folder or from xcmsSet, create pdf
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196 ##
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197 #@author Y. Guitton
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198 getTICs <- function(xcmsSet=NULL,files=NULL, pdfname="TICs.pdf",rt=c("raw","corrected")) {
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199 cat("Creating TIC pdf...\n")
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200
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201 if (is.null(xcmsSet)) {
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202 filepattern <- c("[Cc][Dd][Ff]", "[Nn][Cc]", "([Mm][Zz])?[Xx][Mm][Ll]", "[Mm][Zz][Dd][Aa][Tt][Aa]", "[Mm][Zz][Mm][Ll]")
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203 filepattern <- paste(paste("\\.", filepattern, "$", sep = ""), collapse = "|")
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204 if (is.null(files))
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205 files <- getwd()
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206 info <- file.info(files)
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207 listed <- list.files(files[info$isdir], pattern = filepattern, recursive = TRUE, full.names = TRUE)
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208 files <- c(files[!info$isdir], listed)
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209 } else {
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210 files <- filepaths(xcmsSet)
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211 }
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212
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213 class<-as.vector(levels(xcmsSet@phenoData[,1])) #sometime phenoData have more than 1 column use first as class
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214
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215 classnames<-vector("list",length(class))
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216 for (i in 1:length(class)){
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217 classnames[[i]]<-which( xcmsSet@phenoData[,1]==class[i])
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218 }
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219
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220 N <- length(files)
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221 TIC <- vector("list",N)
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222
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223 for (i in 1:N) {
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224 if (!is.null(xcmsSet) && rt == "corrected")
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225 rtcor <- xcmsSet@rt$corrected[[i]] else
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226 rtcor <- NULL
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227 TIC[[i]] <- getTIC(files[i],rtcor=rtcor)
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228 }
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229
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230 pdf(pdfname,w=16,h=10)
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231 cols <- rainbow(N)
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232 lty = 1:N
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233 pch = 1:N
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234 #search for max x and max y in TICs
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235 xlim = range(sapply(TIC, function(x) range(x[,1])))
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236 ylim = range(sapply(TIC, function(x) range(x[,2])))
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237 ylim = c(-ylim[2], ylim[2])
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238
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239
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240 ##plot start
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241 if (length(class)>2){
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242 for (k in 1:(length(class)-1)){
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243 for (l in (k+1):length(class)){
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244 #print(paste(class[k],"vs",class[l],sep=" "))
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245 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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246 colvect<-NULL
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247 for (j in 1:length(classnames[[k]])) {
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248
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249 tic <- TIC[[classnames[[k]][j]]]
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250 # points(tic[,1]/60, tic[,2], col = cols[i], pch = pch[i], type="l")
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251 points(tic[,1]/60, tic[,2], col = cols[classnames[[k]][j]], pch = pch[classnames[[k]][j]], type="l")
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252 colvect<-append(colvect,cols[classnames[[k]][j]])
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253 }
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254 for (j in 1:length(classnames[[l]])) {
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255 # i=class2names[j]
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256 tic <- TIC[[classnames[[l]][j]]]
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257 points(tic[,1]/60, -tic[,2], col = cols[classnames[[l]][j]], pch = pch[classnames[[l]][j]], type="l")
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258 colvect<-append(colvect,cols[classnames[[l]][j]])
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259 }
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260 legend("topright",paste(basename(files[c(classnames[[k]],classnames[[l]])])), col = colvect, lty = lty, pch = pch)
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261 }
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262 }
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263 }#end if length >2
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264 if (length(class)==2){
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265 k=1
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266 l=2
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267
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268 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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269 colvect<-NULL
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270 for (j in 1:length(classnames[[k]])) {
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271 tic <- TIC[[classnames[[k]][j]]]
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272 # points(tic[,1]/60, tic[,2], col = cols[i], pch = pch[i], type="l")
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273 points(tic[,1]/60, tic[,2], col = cols[classnames[[k]][j]], pch = pch[classnames[[k]][j]], type="l")
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274 colvect<-append(colvect,cols[classnames[[k]][j]])
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275 }
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276 for (j in 1:length(classnames[[l]])) {
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277 # i=class2names[j]
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278 tic <- TIC[[classnames[[l]][j]]]
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279 points(tic[,1]/60, -tic[,2], col = cols[classnames[[l]][j]], pch = pch[classnames[[l]][j]], type="l")
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280 colvect<-append(colvect,cols[classnames[[l]][j]])
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281 }
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282 legend("topright",paste(basename(files[c(classnames[[k]],classnames[[l]])])), col = colvect, lty = lty, pch = pch)
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283
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284 }#end length ==2
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285
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286 #case where only one class
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287 if (length(class)==1){
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288 k=1
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289 ylim = range(sapply(TIC, function(x) range(x[,2])))
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290
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291 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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292 colvect<-NULL
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293 for (j in 1:length(classnames[[k]])) {
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294 tic <- TIC[[classnames[[k]][j]]]
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295 # points(tic[,1]/60, tic[,2], col = cols[i], pch = pch[i], type="l")
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296 points(tic[,1]/60, tic[,2], col = cols[classnames[[k]][j]], pch = pch[classnames[[k]][j]], type="l")
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297 colvect<-append(colvect,cols[classnames[[k]][j]])
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298 }
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299
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300 legend("topright",paste(basename(files[c(classnames[[k]])])), col = colvect, lty = lty, pch = pch)
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301
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302 }#end length ==1
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303
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304 dev.off() #pdf(pdfname,w=16,h=10)
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305
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306 invisible(TIC)
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307 }
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308
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309
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310
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311 ##
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312 ## Get the polarities from all the samples of a condition
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313 #@author Misharl Monsoor misharl.monsoor@sb-roscoff.fr ABiMS TEAM
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314 #@author Gildas Le Corguille lecorguille@sb-roscoff.fr ABiMS TEAM
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315 getSampleMetadata <- function(xcmsSet=NULL, sampleMetadataOutput="sampleMetadata.tsv") {
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316 cat("Creating the sampleMetadata file...\n")
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317
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318 #Create the sampleMetada dataframe
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319 sampleMetadata=xset@phenoData
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320 sampleNamesOrigin=rownames(sampleMetadata)
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321 sampleNamesMakeNames=make.names(sampleNamesOrigin)
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322
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323 if (any(duplicated(sampleNamesMakeNames))) {
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324 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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325 for (sampleName in sampleNamesOrigin) {
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326 write(paste(sampleName,"\t->\t",make.names(sampleName)),stderr())
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327 }
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328 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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329 }
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330
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331 if (!all(sampleNamesOrigin == sampleNamesMakeNames)) {
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332 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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333 for (sampleName in sampleNamesOrigin) {
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334 cat(paste(sampleName,"\t->\t",make.names(sampleName),"\n"))
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335 }
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336 }
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337
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338 sampleMetadata$sampleMetadata=sampleNamesMakeNames
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339 sampleMetadata=cbind(sampleMetadata["sampleMetadata"],sampleMetadata["class"]) #Reorder columns
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340 rownames(sampleMetadata)=NULL
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341
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342 #Create a list of files name in the current directory
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343 list_files=xset@filepaths
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344 #For each sample file, the following actions are done
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345 for (file in list_files){
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346 #Check if the file is in the CDF format
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347 if (!mzR:::netCDFIsFile(file)){
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348
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349 # If the column isn't exist, with add one filled with NA
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350 if (is.null(sampleMetadata$polarity)) sampleMetadata$polarity=NA
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351
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352 #Create a simple xcmsRaw object for each sample
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353 xcmsRaw=xcmsRaw(file)
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354 #Extract the polarity (a list of polarities)
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355 polarity=xcmsRaw@polarity
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356 #Verify if all the scans have the same polarity
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357 uniq_list=unique(polarity)
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358 if (length(uniq_list)>1){
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359 polarity="mixed"
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360 } else {
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361 polarity=as.character(uniq_list)
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362 }
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363 #Transforms the character to obtain only the sample name
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364 filename=basename(file)
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365 library(tools)
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366 samplename=file_path_sans_ext(filename)
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367
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368 #Set the polarity attribute
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369 sampleMetadata$polarity[sampleMetadata$sampleMetadata==samplename]=polarity
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370
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371 #Delete xcmsRaw object because it creates a bug for the fillpeaks step
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372 rm(xcmsRaw)
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373 }
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374
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375 }
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376
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377 write.table(sampleMetadata, sep="\t", quote=FALSE, row.names=FALSE, file=sampleMetadataOutput)
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378
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379 return(list("sampleNamesOrigin"=sampleNamesOrigin,"sampleNamesMakeNames"=sampleNamesMakeNames))
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380
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381 }
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382
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383
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384 ##
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385 ## This function check if xcms will found all the files
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386 ##
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387 #@author Gildas Le Corguille lecorguille@sb-roscoff.fr ABiMS TEAM
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388 checkFilesCompatibilityWithXcms <- function(directory) {
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389 cat("Checking files filenames compatibilities with xmcs...\n")
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390 # WHAT XCMS WILL FIND
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391 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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392 filepattern <- paste(paste("\\.", filepattern, "$", sep = ""),collapse = "|")
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393 info <- file.info(directory)
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394 listed <- list.files(directory[info$isdir], pattern = filepattern,recursive = TRUE, full.names = TRUE)
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395 files <- c(directory[!info$isdir], listed)
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396 files_abs <- file.path(getwd(), files)
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397 exists <- file.exists(files_abs)
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398 files[exists] <- files_abs[exists]
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399 files[exists] <- sub("//","/",files[exists])
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400
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401 # WHAT IS ON THE FILESYSTEM
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402 filesystem_filepaths=system(paste("find $PWD/",directory," -not -name '\\.*' -not -path '*conda-env*' -type f -name \"*\"", sep=""), intern=T)
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403 filesystem_filepaths=filesystem_filepaths[grep(filepattern, filesystem_filepaths, perl=T)]
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404
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405 # COMPARISON
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406 if (!is.na(table(filesystem_filepaths %in% files)["FALSE"])) {
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407 write("\n\nERROR: List of the files which will not be imported by xcmsSet",stderr())
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408 write(filesystem_filepaths[!(filesystem_filepaths %in% files)],stderr())
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409 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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410
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411 }
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412 }
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413
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414
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415
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416 ##
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417 ## This function check if XML contains special caracters. It also checks integrity and completness.
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418 ##
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419 #@author Misharl Monsoor misharl.monsoor@sb-roscoff.fr ABiMS TEAM
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420 checkXmlStructure <- function (directory) {
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421 cat("Checking XML structure...\n")
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422
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423 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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424 capture=system(cmd,intern=TRUE)
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425
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426 if (length(capture)>0){
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427 #message=paste("The following mzXML or mzML file is incorrect, please check these files first:",capture)
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428 write("\n\nERROR: The following mzXML or mzML file(s) are incorrect, please check these files first:", stderr())
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429 write(capture, stderr())
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430 stop("ERROR: xcmsSet cannot continue with incorrect mzXML or mzML files")
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431 }
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432
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433 }
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434
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435
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436 ##
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437 ## This function check if XML contain special characters
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438 ##
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439 #@author Misharl Monsoor misharl.monsoor@sb-roscoff.fr ABiMS TEAM
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440 deleteXmlBadCharacters<- function (directory) {
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441 cat("Checking Non ASCII characters in the XML...\n")
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442
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443 processed=F
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444 l=system( paste("find",directory, "-not -name '\\.*' -not -path '*conda-env*' -type f -iname '*.*ml*'"),intern=TRUE)
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445 for (i in l){
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446 cmd=paste("LC_ALL=C grep '[^ -~]' \"",i,"\"",sep="")
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447 capture=suppressWarnings(system(cmd,intern=TRUE))
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448 if (length(capture)>0){
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449 cmd=paste("perl -i -pe 's/[^[:ascii:]]//g;'",i)
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450 print( paste("WARNING: Non ASCII characters have been removed from the ",i,"file") )
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451 c=system(cmd,intern=TRUE)
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452 capture=""
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453 processed=T
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454 }
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455 }
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456 if (processed) cat("\n\n")
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457 return(processed)
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458 }
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459
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460
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c04568596f40 planemo upload for repository https://github.com/workflow4metabolomics/xcms commit 08e7f269a5c59687a7768be8db5fcb4e4d736093
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461 ##
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462 ## This function will compute MD5 checksum to check the data integrity
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463 ##
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464 #@author Gildas Le Corguille lecorguille@sb-roscoff.fr
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465 getMd5sum <- function (directory) {
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466 cat("Compute md5 checksum...\n")
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467 # WHAT XCMS WILL FIND
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468 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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469 filepattern <- paste(paste("\\.", filepattern, "$", sep = ""),collapse = "|")
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470 info <- file.info(directory)
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471 listed <- list.files(directory[info$isdir], pattern = filepattern,recursive = TRUE, full.names = TRUE)
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472 files <- c(directory[!info$isdir], listed)
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473 exists <- file.exists(files)
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474 files <- files[exists]
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475
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476 library(tools)
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477
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478 #cat("\n\n")
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479
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480 return(as.matrix(md5sum(files)))
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481 }