Mercurial > repos > lecorguille > camera_annotate

annotate lib.r @ 10:8dd6f0ffa763 draft

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planemo upload commit 62670148178273a855c42e85438ce731548ada48-dirty
author lecorguille
date Mon, 04 Jul 2016 08:52:04 -0400
parents 7da9252dd983
children 1c30ff90f3ae
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1 # lib.r version="2.2.1"
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3 #The function create a pdf from the different png generated by diffreport
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4 diffreport_png2pdf <- function(filebase, new_file_path) {
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6 pdfEicOutput = paste(new_file_path,filebase,"-eic_visible_pdf",sep="")
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7 pdfBoxOutput = paste(new_file_path,filebase,"-box_visible_pdf",sep="")
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9 system(paste("gm convert ",filebase,"_eic/*.png ",filebase,"_eic.pdf",sep=""))
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10 system(paste("gm convert ",filebase,"_box/*.png ",filebase,"_box.pdf",sep=""))
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12 file.copy(paste(filebase,"_eic.pdf",sep=""), pdfEicOutput)
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13 file.copy(paste(filebase,"_box.pdf",sep=""), pdfBoxOutput)
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14 }
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16 #The function annotateDiffreport without the corr function which bugs
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17 annotatediff <- function(xset=xset, listArguments=listArguments, variableMetadataOutput="variableMetadata.tsv", dataMatrixOutput="dataMatrix.tsv",new_file_path=NULL) {
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18 # Resolve the bug with x11, with the function png
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19 options(bitmapType='cairo')
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21 #Check if the fillpeaks step has been done previously, if it hasn't, there is an error message and the execution is stopped.
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22 res=try(is.null(xset@filled))
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23
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24 # ------ annot -------
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25 listArguments[["calcCiS"]]=as.logical(listArguments[["calcCiS"]])
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26 listArguments[["calcIso"]]=as.logical(listArguments[["calcIso"]])
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27 listArguments[["calcCaS"]]=as.logical(listArguments[["calcCaS"]])
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29 #graphMethod parameter bugs where this parameter is not defined in quick=true
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30 if(listArguments[["quick"]]==TRUE) {
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31 xa= annotate(object=xset,nSlaves=1,sigma=listArguments[["sigma"]],perfwhm=listArguments[["perfwhm"]],maxcharge=listArguments[["maxcharge"]],maxiso=listArguments[["maxiso"]],minfrac=listArguments[["minfrac"]],ppm=listArguments[["ppm"]],mzabs=listArguments[["mzabs"]],quick=listArguments[["quick"]],polarity=listArguments[["polarity"]],max_peaks=listArguments[["max_peaks"]],intval=listArguments[["intval"]])
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32 }
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33 else {
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34 xa= annotate(object=xset,nSlaves=1,sigma=listArguments[["sigma"]],perfwhm=listArguments[["perfwhm"]],graphMethod=listArguments[["graphMethod"]],cor_eic_th=listArguments[["cor_eic_th"]],pval=listArguments[["pval"]],calcCiS=listArguments[["calcCiS"]],calcIso=listArguments[["calcIso"]],calcCaS=listArguments[["calcCaS"]],multiplier=listArguments[["multiplier"]],maxcharge=listArguments[["maxcharge"]],maxiso=listArguments[["maxiso"]],minfrac=listArguments[["minfrac"]],ppm=listArguments[["ppm"]],mzabs=listArguments[["mzabs"]],quick=listArguments[["quick"]],polarity=listArguments[["polarity"]],max_peaks=listArguments[["max_peaks"]],intval=listArguments[["intval"]])
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36 }
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37 peakList=getPeaklist(xa,intval=listArguments[["intval"]])
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38 peakList=cbind(groupnames(xa@xcmsSet),peakList); colnames(peakList)[1] = c("name");
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41 # --- Multi condition : diffreport ---
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42 diffrep=NULL
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43 if (!is.null(listArguments[["runDiffreport"]]) & nlevels(sampclass(xset))>=2) {
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44 #Check if the fillpeaks step has been done previously, if it hasn't, there is an error message and the execution is stopped.
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45 res=try(is.null(xset@filled))
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46 classes=levels(sampclass(xset))
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47 x=1:(length(classes)-1)
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48 for (i in seq(along=x) ) {
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49 y=1:(length(classes))
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50 for (n in seq(along=y)){
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51 if(i+n <= length(classes)){
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52 filebase=paste(classes[i],class2=classes[i+n],sep="-vs-")
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53
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54 diffrep=diffreport(object=xset,class1=classes[i],class2=classes[i+n],filebase=filebase,eicmax=listArguments[["eicmax"]],eicwidth=listArguments[["eicwidth"]],sortpval=TRUE,value=listArguments[["value"]],h=listArguments[["h"]],w=listArguments[["w"]],mzdec=listArguments[["mzdec"]])
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55 #combines results
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56 diffreportTSV=merge(peakList, diffrep[,c("name","fold","tstat","pvalue")], by.x="name", by.y="name", sort=F)
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57 diffreportTSV=cbind(diffreportTSV[,!(colnames(diffreportTSV) %in% c(sampnames(xa@xcmsSet)))],diffreportTSV[,(colnames(diffreportTSV) %in% c(sampnames(xa@xcmsSet)))])
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58
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59 if(listArguments[["sortpval"]]){
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60 diffreportTSV=diffreportTSV[order(diffreportTSV$pvalue), ]
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61 }
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62
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63 if (listArguments[["convert_param"]]){
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64 #converting the retention times (seconds) into minutes
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65 diffreportTSV$rt=diffreportTSV$rt/60;diffreportTSV$rtmin=diffreportTSV$rtmin/60; diffreportTSV$rtmax=diffreportTSV$rtmax/60;
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66 }
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67 write.table(diffreportTSV, sep="\t", quote=FALSE, row.names=FALSE, file=paste(new_file_path,filebase,"-tabular_visible_tabular",sep=""))
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68
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69 if (listArguments[["eicmax"]] != 0) {
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70 diffreport_png2pdf(filebase, new_file_path)
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71 }
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72 }
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73 }
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74 }
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75 }
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80 # --- variableMetadata ---
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81 variableMetadata=peakList[,!(make.names(colnames(peakList)) %in% c(make.names(sampnames(xa@xcmsSet))))]
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82 # if we have 2 conditions, we keep stat of diffrep
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83 if (!is.null(listArguments[["runDiffreport"]]) & nlevels(sampclass(xset))==2) {
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84 variableMetadata = merge(variableMetadata, diffrep[,c("name","fold","tstat","pvalue")],by.x="name", by.y="name", sort=F)
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85 if(exists("listArguments[[\"sortpval\"]]")){
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86 variableMetadata=variableMetadata[order(variableMetadata$pvalue), ]
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87 }
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88 }
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89
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90 variableMetadataOri=variableMetadata
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91 if (listArguments[["convert_param"]]){
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92 #converting the retention times (seconds) into minutes
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93 print("converting the retention times into minutes in the variableMetadata")
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94 variableMetadata$rt=variableMetadata$rt/60;variableMetadata$rtmin=variableMetadata$rtmin/60; variableMetadata$rtmax=variableMetadata$rtmax/60;
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95 }
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96 #Transform metabolites name
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97 variableMetadata$name= paste("M",round(variableMetadata$mz,digits=listArguments[["num_digits"]]),"T",round(variableMetadata$rt),sep="")
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98 write.table(variableMetadata, sep="\t", quote=FALSE, row.names=FALSE, file=variableMetadataOutput)
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99
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100 # --- dataMatrix ---
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101 dataMatrix = peakList[,(make.names(colnames(peakList)) %in% c(make.names(sampnames(xa@xcmsSet))))]
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102 dataMatrix=cbind(peakList$name,dataMatrix); colnames(dataMatrix)[1] = c("name");
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103
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104 if (listArguments[["convert_param"]]){
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105 #converting the retention times (seconds) into minutes
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106 print("converting the retention times into minutes in the dataMatrix ids")
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107 peakList$rt=peakList$rt/60
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108 }
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109 dataMatrix$name= paste("M",round(peakList$mz,digits=listArguments[["num_digits"]]),"T",round(peakList$rt),sep="")
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110 write.table(dataMatrix, sep="\t", quote=FALSE, row.names=FALSE, file=dataMatrixOutput)
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111
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112 return(list("xa"=xa,"diffrep"=diffrep,"variableMetadata"=variableMetadataOri));
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113
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114 }
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115
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116
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117 combinexsAnnos_function <- function(xaP, xaN, listOFlistArgumentsP,listOFlistArgumentsN, diffrepP=NULL,diffrepN=NULL,convert_param=FALSE,pos=TRUE,tol=2,ruleset=NULL,keep_meta=TRUE, variableMetadataOutput="variableMetadata.tsv"){
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118
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119 #Load the two Rdata to extract the xset objects from positive and negative mode
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120 cat("\tObject xset from positive mode\n")
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121 print(xaP)
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122 cat("\n")
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123
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124 cat("\tObject xset from negative mode\n")
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125 print(xaN)
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126 cat("\n")
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127
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128 cat("\n")
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129 cat("\tCombining...\n")
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130 #Convert the string to numeric for creating matrix
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131 row=as.numeric(strsplit(ruleset,",")[[1]][1])
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132 column=as.numeric(strsplit(ruleset,",")[[1]][2])
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133 ruleset=cbind(row,column)
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134 #Test if the file comes from an older version tool
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135 if ((!is.null(xaP)) & (!is.null(xaN))) {
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136 #Launch the combinexsannos function from CAMERA
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137 cAnnot=combinexsAnnos(xaP, xaN,pos=pos,tol=tol,ruleset=ruleset)
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138 } else {
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139 stop("You must relauch the CAMERA.annotate step with the lastest version.")
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140 }
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141
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142
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143
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144 if(pos){
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145 xa=xaP
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146 listOFlistArgumentsP=listOFlistArguments
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147 mode="neg. Mode"
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148 } else {
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149 xa=xaN
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150 listOFlistArgumentsN=listOFlistArguments
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151 mode="pos. Mode"
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152 }
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153 intval = "into"; for (steps in names(listOFlistArguments)) { if (!is.null(listOFlistArguments[[steps]]$intval)) intval = listOFlistArguments[[steps]]$intval }
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154 peakList=getPeaklist(xa,intval=intval)
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155 peakList=cbind(groupnames(xa@xcmsSet),peakList); colnames(peakList)[1] = c("name");
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156 variableMetadata=cbind(peakList, cAnnot[, c("isotopes", "adduct", "pcgroup",mode)]);
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157 variableMetadata=variableMetadata[,!(colnames(variableMetadata) %in% c(sampnames(xa@xcmsSet)))]
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158
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159 #Test if there are more than two classes (conditions)
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160 if ( nlevels(sampclass(xaP@xcmsSet))==2 & (!is.null(diffrepN)) & (!is.null(diffrepP))) {
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161 diffrepP = diffrepP[,c("name","fold","tstat","pvalue")]; colnames(diffrepP) = paste("P.",colnames(diffrepP),sep="")
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162 diffrepN = diffrepN[,c("name","fold","tstat","pvalue")]; colnames(diffrepN) = paste("N.",colnames(diffrepN),sep="")
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163
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164 variableMetadata = merge(variableMetadata, diffrepP, by.x="name", by.y="P.name")
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165 variableMetadata = merge(variableMetadata, diffrepN, by.x="name", by.y="N.name")
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166 }
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167
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168 rownames(variableMetadata) = NULL
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169 #TODO: checker
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170 #colnames(variableMetadata)[1:2] = c("name","mz/rt");
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171
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172 #If the user want to convert the retention times (seconds) into minutes.
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173 if (listArguments[["convert_param"]]){
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174 #converting the retention times (seconds) into minutes
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175 cat("\tConverting the retention times into minutes\n")
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176 variableMetadata$rtmed=cAnnot$rt/60; variableMetadata$rtmin=cAnnot$rtmin/60; variableMetadata$rtmax=cAnnot$rtmax/60;
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177 }
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178
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179 #If the user want to keep only the metabolites which match a difference
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180 if(keep_meta){
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181 variableMetadata=variableMetadata[variableMetadata[,c(mode)]!="",]
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182 }
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183
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184 #Write the output into a tsv file
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185 write.table(variableMetadata, sep="\t", quote=FALSE, row.names=FALSE, file=variableMetadataOutput)
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186 return(variableMetadata);
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187
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188 }