Mercurial > repos > mmonsoor > camera_combinexsannos

annotate lib.r @ 12:961089e21ae2 draft default tip

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planemo upload commit 1a5357c0e28103a0325b2df858504721f6266049
author lecorguille
date Tue, 09 Oct 2018 06:03:24 -0400
parents 837c6955e4e9
children
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1 # lib.r
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2
11
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3 # This function retrieve a xset like object
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4 #@author Gildas Le Corguille lecorguille@sb-roscoff.fr
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5 getxcmsSetObject <- function(xobject) {
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6 # XCMS 1.x
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7 if (class(xobject) == "xcmsSet")
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8 return (xobject)
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9 # XCMS 3.x
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10 if (class(xobject) == "XCMSnExp") {
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11 # Get the legacy xcmsSet object
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12 suppressWarnings(xset <- as(xobject, 'xcmsSet'))
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13 if (is.null(xset@phenoData$sample_group))
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14 sampclass(xset) = "."
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15 else
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16 sampclass(xset) <- xset@phenoData$sample_group
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17 if (!is.null(xset@phenoData$sample_name))
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18 rownames(xset@phenoData) = xset@phenoData$sample_name
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19 return (xset)
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20 }
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21 }
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22
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23 #@author G. Le Corguille
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24 #The function create a pdf from the different png generated by diffreport
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25 diffreport_png2pdf <- function(filebase) {
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26 dir.create("pdf")
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28 pdfEicOutput = paste0("pdf/",filebase,"-eic_pdf.pdf")
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29 pdfBoxOutput = paste0("pdf/",filebase,"-box_pdf.pdf")
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31 system(paste0("gm convert ",filebase,"_eic/*.png ",pdfEicOutput))
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32 system(paste0("gm convert ",filebase,"_box/*.png ",pdfBoxOutput))
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33
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34 }
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35
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36 #@author G. Le Corguille
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37 #This function convert if it is required the Retention Time in minutes
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38 RTSecondToMinute <- function(variableMetadata, convertRTMinute) {
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39 if (convertRTMinute){
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40 #converting the retention times (seconds) into minutes
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41 print("converting the retention times into minutes in the variableMetadata")
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42 variableMetadata[,"rt"]=variableMetadata[,"rt"]/60
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43 variableMetadata[,"rtmin"]=variableMetadata[,"rtmin"]/60
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44 variableMetadata[,"rtmax"]=variableMetadata[,"rtmax"]/60
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45 }
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46 return (variableMetadata)
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47 }
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49 #@author G. Le Corguille
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50 #This function format ions identifiers
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51 formatIonIdentifiers <- function(variableMetadata, numDigitsRT=0, numDigitsMZ=0) {
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52 splitDeco = strsplit(as.character(variableMetadata$name),"_")
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53 idsDeco = sapply(splitDeco, function(x) { deco=unlist(x)[2]; if (is.na(deco)) return ("") else return(paste0("_",deco)) })
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54 namecustom = make.unique(paste0("M",round(variableMetadata[,"mz"],numDigitsMZ),"T",round(variableMetadata[,"rt"],numDigitsRT),idsDeco))
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55 variableMetadata=cbind(name=variableMetadata$name, namecustom=namecustom, variableMetadata[,!(colnames(variableMetadata) %in% c("name"))])
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56 return(variableMetadata)
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57 }
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59 #The function annotateDiffreport without the corr function which bugs
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60 annotatediff <- function(xset=xset, listArguments=listArguments, variableMetadataOutput="variableMetadata.tsv") {
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61 # Resolve the bug with x11, with the function png
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62 options(bitmapType='cairo')
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64 #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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65 res=try(is.null(xset@filled))
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66
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67 # ------ annot -------
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68 listArguments[["calcCiS"]]=as.logical(listArguments[["calcCiS"]])
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69 listArguments[["calcIso"]]=as.logical(listArguments[["calcIso"]])
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70 listArguments[["calcCaS"]]=as.logical(listArguments[["calcCaS"]])
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71
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72 # common parameters
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73 listArguments4annotate = list(object=xset,
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74 nSlaves=listArguments[["nSlaves"]],sigma=listArguments[["sigma"]],perfwhm=listArguments[["perfwhm"]],
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75 maxcharge=listArguments[["maxcharge"]],maxiso=listArguments[["maxiso"]],minfrac=listArguments[["minfrac"]],
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76 ppm=listArguments[["ppm"]],mzabs=listArguments[["mzabs"]],quick=listArguments[["quick"]],
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77 polarity=listArguments[["polarity"]],max_peaks=listArguments[["max_peaks"]],intval=listArguments[["intval"]])
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78
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79 # quick == FALSE
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80 if(listArguments[["quick"]]==FALSE) {
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81 listArguments4annotate = append(listArguments4annotate,
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82 list(graphMethod=listArguments[["graphMethod"]],cor_eic_th=listArguments[["cor_eic_th"]],pval=listArguments[["pval"]],
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83 calcCiS=listArguments[["calcCiS"]],calcIso=listArguments[["calcIso"]],calcCaS=listArguments[["calcCaS"]]))
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84 # no ruleset
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85 if (!is.null(listArguments[["multiplier"]])) {
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86 listArguments4annotate = append(listArguments4annotate,
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87 list(multiplier=listArguments[["multiplier"]]))
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88 }
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89 # ruleset
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90 else {
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91 rulset=read.table(listArguments[["rules"]], h=T, sep=";")
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92 if (ncol(rulset) < 4) rulset=read.table(listArguments[["rules"]], h=T, sep="\t")
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93 if (ncol(rulset) < 4) rulset=read.table(listArguments[["rules"]], h=T, sep=",")
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94 if (ncol(rulset) < 4) {
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95 error_message="Your ruleset file seems not well formatted. The column separators accepted are ; , and tabulation"
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96 print(error_message)
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97 stop(error_message)
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98 }
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99
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100 listArguments4annotate = append(listArguments4annotate,
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101 list(rules=rulset))
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102 }
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103 }
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104
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105
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106 # launch annotate
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107 xa = do.call("annotate", listArguments4annotate)
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108 peakList=getPeaklist(xa,intval=listArguments[["intval"]])
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109 peakList=cbind(groupnames(xa@xcmsSet),peakList); colnames(peakList)[1] = c("name");
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110
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111 # --- Multi condition : diffreport ---
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112 diffrepOri=NULL
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113 if (!is.null(listArguments[["runDiffreport"]]) & nlevels(sampclass(xset))>=2) {
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114 #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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115 res=try(is.null(xset@filled))
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116 classes=levels(sampclass(xset))
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117 x=1:(length(classes)-1)
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118 for (i in seq(along=x) ) {
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119 y=1:(length(classes))
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120 for (n in seq(along=y)){
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121 if(i+n <= length(classes)){
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122 filebase=paste(classes[i],class2=classes[i+n],sep="-vs-")
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123
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124 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"]],missing=0)
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125
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126 diffrepOri = diffrep
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127
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128 # renamming of the column rtmed to rt to fit with camera peaklist function output
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129 colnames(diffrep)[colnames(diffrep)=="rtmed"] <- "rt"
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130 colnames(diffrep)[colnames(diffrep)=="mzmed"] <- "mz"
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131
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132 # combines results and reorder columns
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133 diffrep = merge(peakList, diffrep[,c("name","fold","tstat","pvalue")], by.x="name", by.y="name", sort=F)
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134 diffrep = cbind(diffrep[,!(colnames(diffrep) %in% c(sampnames(xa@xcmsSet)))],diffrep[,(colnames(diffrep) %in% c(sampnames(xa@xcmsSet)))])
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135
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136 diffrep = RTSecondToMinute(diffrep, listArguments[["convertRTMinute"]])
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137 diffrep = formatIonIdentifiers(diffrep, numDigitsRT=listArguments[["numDigitsRT"]], numDigitsMZ=listArguments[["numDigitsMZ"]])
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138
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139 if(listArguments[["sortpval"]]){
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140 diffrep=diffrep[order(diffrep$pvalue), ]
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141 }
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142
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143 dir.create("tabular")
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144 write.table(diffrep, sep="\t", quote=FALSE, row.names=FALSE, file=paste("tabular/",filebase,"_tsv.tabular",sep=""))
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145
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146 if (listArguments[["eicmax"]] != 0) {
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147 diffreport_png2pdf(filebase)
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148 }
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149 }
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150 }
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151 }
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152 }
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153
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154 # --- variableMetadata ---
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155 variableMetadata=peakList[,!(make.names(colnames(peakList)) %in% c(make.names(sampnames(xa@xcmsSet))))]
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156 variableMetadata = RTSecondToMinute(variableMetadata, listArguments[["convertRTMinute"]])
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157 variableMetadata = formatIonIdentifiers(variableMetadata, numDigitsRT=listArguments[["numDigitsRT"]], numDigitsMZ=listArguments[["numDigitsMZ"]])
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158 # if we have 2 conditions, we keep stat of diffrep
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159 if (!is.null(listArguments[["runDiffreport"]]) & nlevels(sampclass(xset))==2) {
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160 variableMetadata = merge(variableMetadata, diffrep[,c("name","fold","tstat","pvalue")],by.x="name", by.y="name", sort=F)
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161 if(exists("listArguments[[\"sortpval\"]]")){
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162 variableMetadata=variableMetadata[order(variableMetadata$pvalue), ]
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163 }
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164 }
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165
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166 variableMetadataOri=variableMetadata
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167 write.table(variableMetadata, sep="\t", quote=FALSE, row.names=FALSE, file=variableMetadataOutput)
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168
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169 return(list("xa"=xa,"diffrep"=diffrepOri,"variableMetadata"=variableMetadataOri));
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170
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171 }
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172
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173
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174 combinexsAnnos_function <- function(xaP, xaN, listOFlistArgumentsP,listOFlistArgumentsN, diffrepP=NULL,diffrepN=NULL,pos=TRUE,tol=2,ruleset=NULL,keep_meta=TRUE, convertRTMinute=F, numDigitsMZ=0, numDigitsRT=0, variableMetadataOutput="variableMetadata.tsv"){
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175
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176 #Load the two Rdata to extract the xset objects from positive and negative mode
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177 cat("\tObject xset from positive mode\n")
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178 print(xaP)
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179 cat("\n")
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180
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181 cat("\tObject xset from negative mode\n")
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182 print(xaN)
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183 cat("\n")
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184
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185 cat("\n")
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186 cat("\tCombining...\n")
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187 #Convert the string to numeric for creating matrix
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188 row=as.numeric(strsplit(ruleset,",")[[1]][1])
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189 column=as.numeric(strsplit(ruleset,",")[[1]][2])
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190 ruleset=cbind(row,column)
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191 #Test if the file comes from an older version tool
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192 if ((!is.null(xaP)) & (!is.null(xaN))) {
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193 #Launch the combinexsannos function from CAMERA
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194 cAnnot=combinexsAnnos(xaP, xaN,pos=pos,tol=tol,ruleset=ruleset)
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195 } else {
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196 stop("You must relauch the CAMERA.annotate step with the lastest version.")
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197 }
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198
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199 if(pos){
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200 xa=xaP
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201 listOFlistArgumentsP=listOFlistArguments
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202 mode="neg. Mode"
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203 } else {
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204 xa=xaN
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205 listOFlistArgumentsN=listOFlistArguments
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206 mode="pos. Mode"
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207 }
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208
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209 peakList=getPeaklist(xa)
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210 peakList=cbind(groupnames(xa@xcmsSet),peakList); colnames(peakList)[1] = c("name");
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211 variableMetadata=cbind(peakList, cAnnot[, c("isotopes", "adduct", "pcgroup",mode)]);
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212 variableMetadata=variableMetadata[,!(colnames(variableMetadata) %in% c(sampnames(xa@xcmsSet)))]
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213
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214 #Test if there are more than two classes (conditions)
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215 if ( nlevels(sampclass(xaP@xcmsSet))==2 & (!is.null(diffrepN)) & (!is.null(diffrepP))) {
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216 diffrepP = diffrepP[,c("name","fold","tstat","pvalue")]; colnames(diffrepP) = paste("P.",colnames(diffrepP),sep="")
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217 diffrepN = diffrepN[,c("name","fold","tstat","pvalue")]; colnames(diffrepN) = paste("N.",colnames(diffrepN),sep="")
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218
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219 variableMetadata = merge(variableMetadata, diffrepP, by.x="name", by.y="P.name")
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220 variableMetadata = merge(variableMetadata, diffrepN, by.x="name", by.y="N.name")
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221 }
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222
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223 rownames(variableMetadata) = NULL
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224 #TODO: checker
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225 #colnames(variableMetadata)[1:2] = c("name","mz/rt");
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226
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227 variableMetadata = RTSecondToMinute(variableMetadata, convertRTMinute)
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228 variableMetadata = formatIonIdentifiers(variableMetadata, numDigitsRT=numDigitsRT, numDigitsMZ=numDigitsMZ)
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229
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230 #If the user want to keep only the metabolites which match a difference
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231 if(keep_meta){
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232 variableMetadata=variableMetadata[variableMetadata[,c(mode)]!="",]
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233 }
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234
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235 #Write the output into a tsv file
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236 write.table(variableMetadata, sep="\t", quote=FALSE, row.names=FALSE, file=variableMetadataOutput)
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237 return(variableMetadata);
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238
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239 }
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240
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241 # This function get the raw file path from the arguments
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242 getRawfilePathFromArguments <- function(singlefile, zipfile, listArguments) {
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243 if (!is.null(listArguments[["zipfile"]])) zipfile = listArguments[["zipfile"]]
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244 if (!is.null(listArguments[["zipfilePositive"]])) zipfile = listArguments[["zipfilePositive"]]
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245 if (!is.null(listArguments[["zipfileNegative"]])) zipfile = listArguments[["zipfileNegative"]]
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246
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247 if (!is.null(listArguments[["singlefile_galaxyPath"]])) {
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248 singlefile_galaxyPaths = listArguments[["singlefile_galaxyPath"]];
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249 singlefile_sampleNames = listArguments[["singlefile_sampleName"]]
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250 }
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251 if (!is.null(listArguments[["singlefile_galaxyPathPositive"]])) {
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252 singlefile_galaxyPaths = listArguments[["singlefile_galaxyPathPositive"]];
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253 singlefile_sampleNames = listArguments[["singlefile_sampleNamePositive"]]
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254 }
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255 if (!is.null(listArguments[["singlefile_galaxyPathNegative"]])) {
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256 singlefile_galaxyPaths = listArguments[["singlefile_galaxyPathNegative"]];
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257 singlefile_sampleNames = listArguments[["singlefile_sampleNameNegative"]]
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258 }
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259 if (exists("singlefile_galaxyPaths")){
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260 singlefile_galaxyPaths = unlist(strsplit(singlefile_galaxyPaths,","))
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261 singlefile_sampleNames = unlist(strsplit(singlefile_sampleNames,","))
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262
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263 singlefile=NULL
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264 for (singlefile_galaxyPath_i in seq(1:length(singlefile_galaxyPaths))) {
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265 singlefile_galaxyPath=singlefile_galaxyPaths[singlefile_galaxyPath_i]
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266 singlefile_sampleName=singlefile_sampleNames[singlefile_galaxyPath_i]
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267 singlefile[[singlefile_sampleName]] = singlefile_galaxyPath
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268 }
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269 }
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270 for (argument in c("zipfile","zipfilePositive","zipfileNegative","singlefile_galaxyPath","singlefile_sampleName","singlefile_galaxyPathPositive","singlefile_sampleNamePositive","singlefile_galaxyPathNegative","singlefile_sampleNameNegative")) {
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271 listArguments[[argument]]=NULL
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272 }
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273 return(list(zipfile=zipfile, singlefile=singlefile, listArguments=listArguments))
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274 }
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275
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276
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277 # This function retrieve the raw file in the working directory
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278 # - if zipfile: unzip the file with its directory tree
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279 # - if singlefiles: set symlink with the good filename
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280 retrieveRawfileInTheWorkingDirectory <- function(singlefile, zipfile) {
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281 if(!is.null(singlefile) && (length("singlefile")>0)) {
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282 for (singlefile_sampleName in names(singlefile)) {
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283 singlefile_galaxyPath = singlefile[[singlefile_sampleName]]
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284 if(!file.exists(singlefile_galaxyPath)){
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285 error_message=paste("Cannot access the sample:",singlefile_sampleName,"located:",singlefile_galaxyPath,". Please, contact your administrator ... if you have one!")
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286 print(error_message); stop(error_message)
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287 }
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288
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289 file.symlink(singlefile_galaxyPath,singlefile_sampleName)
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290 }
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291 directory = "."
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292
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293 }
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294 if(!is.null(zipfile) && (zipfile!="")) {
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295 if(!file.exists(zipfile)){
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296 error_message=paste("Cannot access the Zip file:",zipfile,". Please, contact your administrator ... if you have one!")
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297 print(error_message)
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298 stop(error_message)
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299 }
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300
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301 #list all file in the zip file
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302 #zip_files=unzip(zipfile,list=T)[,"Name"]
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303
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304 #unzip
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305 suppressWarnings(unzip(zipfile, unzip="unzip"))
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306
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307 #get the directory name
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308 filesInZip=unzip(zipfile, list=T);
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309 directories=unique(unlist(lapply(strsplit(filesInZip$Name,"/"), function(x) x[1])));
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310 directories=directories[!(directories %in% c("__MACOSX")) & file.info(directories)$isdir]
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311 directory = "."
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312 if (length(directories) == 1) directory = directories
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313
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314 cat("files_root_directory\t",directory,"\n")
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315
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316 }
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317 return (directory)
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318 }
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319
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320 #@TODO: remove this function as soon as we can use xcms 3.x.x from Bioconductor 3.7
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321 # https://github.com/sneumann/CAMERA/issues/33#issuecomment-405168524
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322 # https://github.com/sneumann/xcms/commit/950a3fe794cdb6b0fda88696e31aab3d97a3b7dd
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323 ############################################################
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324 ## getEIC
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325 getEIC <- function(object, mzrange, rtrange = 200,
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326 groupidx, sampleidx = sampnames(object),
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327 rt = c("corrected", "raw")) {
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328
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329 files <- filepaths(object)
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330 grp <- groups(object)
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331 samp <- sampnames(object)
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332 prof <- profinfo(object)
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333
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334 rt <- match.arg(rt)
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335
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336 if (is.numeric(sampleidx))
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337 sampleidx <- sampnames(object)[sampleidx]
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338 sampidx <- match(sampleidx, sampnames(object))
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339
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340 if (!missing(groupidx)) {
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341 if (is.numeric(groupidx))
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342 groupidx <- groupnames(object)[unique(as.integer(groupidx))]
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343 grpidx <- match(groupidx, groupnames(object, template = groupidx))
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344 }
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345
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346 if (missing(mzrange)) {
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347 if (missing(groupidx))
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348 stop("No m/z range or groups specified")
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349 if (any(is.na(groupval(object, value = "mz"))))
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350 warning(
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351 "`NA` values in xcmsSet. Use fillPeaks() on the object to fill",
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352 "-in missing peak values. Note however that this will also ",
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353 "insert intensities of 0 for peaks that can not be filled in.")
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354 mzmin <- apply(groupval(object, value = "mzmin"), 1, min, na.rm = TRUE)
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355 mzmax <- apply(groupval(object, value = "mzmax"), 1, max, na.rm = TRUE)
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356 mzrange <- matrix(c(mzmin[grpidx], mzmax[grpidx]), ncol = 2)
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357 ## if (any(is.na(groupval(object, value = "mz"))))
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358 ## stop('Please use fillPeaks() to fill up NA values !')
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359 ## mzmin <- -rowMax(-groupval(object, value = "mzmin"))
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360 ## mzmax <- rowMax(groupval(object, value = "mzmax"))
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361 ## mzrange <- matrix(c(mzmin[grpidx], mzmax[grpidx]), ncol = 2)
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362 } else if (all(c("mzmin","mzmax") %in% colnames(mzrange)))
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363 mzrange <- mzrange[,c("mzmin", "mzmax"),drop=FALSE]
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364 else if (is.null(dim(mzrange)))
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365 stop("mzrange must be a matrix")
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366 colnames(mzrange) <- c("mzmin", "mzmax")
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367
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368 if (length(rtrange) == 1) {
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369 if (missing(groupidx))
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370 rtrange <- matrix(rep(range(object@rt[[rt]][sampidx]), nrow(mzrange)),
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371 ncol = 2, byrow = TRUE)
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372 else {
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373 rtrange <- retexp(grp[grpidx,c("rtmin","rtmax"),drop=FALSE], rtrange)
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374 }
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375 } else if (is.null(dim(rtrange)))
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376 stop("rtrange must be a matrix or single number")
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377 colnames(rtrange) <- c("rtmin", "rtmax")
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378
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379 ## Ensure that we've got corrected retention time if requested.
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380 if (is.null(object@rt[[rt]]))
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381 stop(rt, " retention times not present in 'object'!")
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382
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383 ## Ensure that the defined retention time range is within the rtrange of the
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384 ## object: we're using the max minimal rt of all files and the min maximal rt
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385 rtrs <- lapply(object@rt[[rt]], range)
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386 rtr <- c(max(unlist(lapply(rtrs, "[", 1))),
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387 min(unlist(lapply(rtrs, "[", 2))))
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388 ## Check if we've got a range which is completely off:
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389 if (any(rtrange[, "rtmin"] >= rtr[2] | rtrange[, "rtmax"] <= rtr[1])) {
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390 outs <- which(rtrange[, "rtmin"] >= rtr[2] |
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391 rtrange[, "rtmax"] <= rtr[1])
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392 stop(length(outs), " of the specified 'rtrange' are completely outside ",
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393 "of the retention time range of 'object' which is (", rtr[1], ", ",
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394 rtr[2], "). The first was: (", rtrange[outs[1], "rtmin"], ", ",
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395 rtrange[outs[1], "rtmax"], "!")
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396 }
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397 lower_rt_outside <- rtrange[, "rtmin"] < rtr[1]
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398 upper_rt_outside <- rtrange[, "rtmax"] > rtr[2]
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399 if (any(lower_rt_outside) | any(upper_rt_outside)) {
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400 ## Silently fix these ranges.
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401 rtrange[lower_rt_outside, "rtmin"] <- rtr[1]
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402 rtrange[upper_rt_outside, "rtmax"] <- rtr[2]
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403 }
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404
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405 if (missing(groupidx))
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406 gnames <- character(0)
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407 else
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408 gnames <- groupidx
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409
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410 eic <- vector("list", length(sampleidx))
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411 names(eic) <- sampleidx
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412
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413 for (i in seq(along = sampidx)) {
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414
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415 ## cat(sampleidx[i], "")
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416 flush.console()
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417 ## getXcmsRaw takes care of rt correction, susetting to scanrage and other
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418 ## stuff.
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419 lcraw <- getXcmsRaw(object, sampleidx = sampidx[i], rt=rt)
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420 currenteic <- xcms::getEIC(lcraw, mzrange, rtrange, step = prof$step)
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421 eic[[i]] <- currenteic@eic[[1]]
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422 rm(lcraw)
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423 gc()
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424 }
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425 ## cat("\n")
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426
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427 invisible(new("xcmsEIC", eic = eic, mzrange = mzrange, rtrange = rtrange,
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428 rt = rt, groupnames = gnames))
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429 }
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430
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431 #@TODO: remove this function as soon as we can use xcms 3.x.x from Bioconductor 3.7
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432 # https://github.com/sneumann/CAMERA/issues/33#issuecomment-405168524
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433 # https://github.com/sneumann/xcms/commit/950a3fe794cdb6b0fda88696e31aab3d97a3b7dd
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434 ############################################################
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435 ## diffreport
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436 diffreport = function(object,
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437 class1 = levels(sampclass(object))[1],
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438 class2 = levels(sampclass(object))[2],
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439 filebase = character(),
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440 eicmax = 0, eicwidth = 200,
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441 sortpval = TRUE,
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442 classeic = c(class1,class2),
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443 value = c("into","maxo","intb"),
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444 metlin = FALSE,
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445 h = 480, w = 640, mzdec=2,
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446 missing = numeric(), ...) {
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447
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448 if ( nrow(object@groups)<1 || length(object@groupidx) <1) {
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449 stop("No group information. Use group().")
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450 }
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451
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452 if (!is.numeric(w) || !is.numeric(h))
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453 stop("'h' and 'w' have to be numeric")
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454 ## require(multtest) || stop("Couldn't load multtest")
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455
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456 value <- match.arg(value)
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457 groupmat <- groups(object)
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458 if (length(groupmat) == 0)
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459 stop("No group information found")
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460 samples <- sampnames(object)
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461 n <- length(samples)
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462 classlabel <- sampclass(object)
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463 classlabel <- levels(classlabel)[as.vector(unclass(classlabel))]
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464
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465 values <- groupval(object, "medret", value=value)
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466 indecies <- groupval(object, "medret", value = "index")
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467
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468 if (!all(c(class1,class2) %in% classlabel))
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469 stop("Incorrect Class Labels")
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470
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471 ## c1 and c2 are column indices of class1 and class2 resp.
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472 c1 <- which(classlabel %in% class1)
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473 c2 <- which(classlabel %in% class2)
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474 ceic <- which(classlabel %in% classeic)
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475 if (length(intersect(c1, c2)) > 0)
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476 stop("Intersecting Classes")
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477
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478 ## Optionally replace NA values with the value provided with missing
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479 if (length(missing)) {
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480 if (is.numeric(missing)) {
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481 ## handles NA, Inf and -Inf
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482 values[, c(c1, c2)][!is.finite(values[, c(c1, c2)])] <- missing[1]
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483 } else
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484 stop("'missing' should be numeric")
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485 }
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486 ## Check against missing Values
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487 if (any(is.na(values[, c(c1, c2)])))
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488 warning("`NA` values in xcmsSet. Use fillPeaks() on the object to fill",
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489 "-in missing peak values. Note however that this will also ",
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490 "insert intensities of 0 for peaks that can not be filled in.")
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491
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492 mean1 <- rowMeans(values[,c1,drop=FALSE], na.rm = TRUE)
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493 mean2 <- rowMeans(values[,c2,drop=FALSE], na.rm = TRUE)
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494
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495 ## Calculate fold change.
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496 ## For foldchange <1 set fold to 1/fold
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497 ## See tstat to check which was higher
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498 fold <- mean2 / mean1
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499 fold[!is.na(fold) & fold < 1] <- 1/fold[!is.na(fold) & fold < 1]
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500
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501 testval <- values[,c(c1,c2)]
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502 ## Replace eventual infinite values with NA (CAMERA issue #33)
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503 testval[is.infinite(testval)] <- NA
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504 testclab <- c(rep(0,length(c1)),rep(1,length(c2)))
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505
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506 if (min(length(c1), length(c2)) >= 2) {
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507 tstat <- mt.teststat(testval, testclab, ...)
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508 pvalue <- xcms:::pval(testval, testclab, tstat)
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509 } else {
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510 message("Too few samples per class, skipping t-test.")
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511 tstat <- pvalue <- rep(NA,nrow(testval))
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512 }
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513 stat <- data.frame(fold = fold, tstat = tstat, pvalue = pvalue)
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514 if (length(levels(sampclass(object))) >2) {
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515 pvalAnova<-c()
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516 for(i in 1:nrow(values)){
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517 var<-as.numeric(values[i,])
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518 ano<-summary(aov(var ~ sampclass(object)) )
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519 pvalAnova<-append(pvalAnova, unlist(ano)["Pr(>F)1"])
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520 }
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521 stat<-cbind(stat, anova= pvalAnova)
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522 }
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523 if (metlin) {
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524 neutralmass <- groupmat[,"mzmed"] + ifelse(metlin < 0, 1, -1)
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525 metlin <- abs(metlin)
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526 digits <- ceiling(-log10(metlin))+1
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527 metlinurl <-
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528 paste("http://metlin.scripps.edu/simple_search_result.php?mass_min=",
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529 round(neutralmass - metlin, digits), "&mass_max=",
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530 round(neutralmass + metlin, digits), sep="")
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531 values <- cbind(metlin = metlinurl, values)
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532 }
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533 twosamp <- cbind(name = groupnames(object), stat, groupmat, values)
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534 if (sortpval) {
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535 tsidx <- order(twosamp[,"pvalue"])
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536 twosamp <- twosamp[tsidx,]
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537 rownames(twosamp) <- 1:nrow(twosamp)
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538 values<-values[tsidx,]
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539 } else
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540 tsidx <- 1:nrow(values)
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541
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542 if (length(filebase))
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543 write.table(twosamp, paste(filebase, ".tsv", sep = ""), quote = FALSE, sep = "\t", col.names = NA)
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544
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545 if (eicmax > 0) {
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546 if (length(unique(peaks(object)[,"rt"])) > 1) {
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547 ## This looks like "normal" LC data
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548
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549 eicmax <- min(eicmax, length(tsidx))
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550 eics <- getEIC(object, rtrange = eicwidth*1.1, sampleidx = ceic,
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551 groupidx = tsidx[seq(length = eicmax)])
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552
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553 if (length(filebase)) {
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554 eicdir <- paste(filebase, "_eic", sep="")
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555 boxdir <- paste(filebase, "_box", sep="")
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556 dir.create(eicdir)
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557 dir.create(boxdir)
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558 if (capabilities("png")){
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559 xcms:::xcmsBoxPlot(values[seq(length = eicmax),],
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560 sampclass(object), dirpath=boxdir, pic="png", width=w, height=h)
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561 png(file.path(eicdir, "%003d.png"), width = w, height = h)
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562 } else {
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563 xcms:::xcmsBoxPlot(values[seq(length = eicmax),],
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564 sampclass(object), dirpath=boxdir, pic="pdf", width=w, height=h)
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565 pdf(file.path(eicdir, "%003d.pdf"), width = w/72,
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566 height = h/72, onefile = FALSE)
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567 }
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568 }
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569 plot(eics, object, rtrange = eicwidth, mzdec=mzdec)
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570
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571 if (length(filebase))
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572 dev.off()
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573 } else {
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574 ## This looks like a direct-infusion single spectrum
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575 if (length(filebase)) {
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576 eicdir <- paste(filebase, "_eic", sep="")
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577 boxdir <- paste(filebase, "_box", sep="")
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578 dir.create(eicdir)
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579 dir.create(boxdir)
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580 if (capabilities("png")){
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581 xcmsBoxPlot(values[seq(length = eicmax),],
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582 sampclass(object), dirpath=boxdir, pic="png",
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583 width=w, height=h)
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584 png(file.path(eicdir, "%003d.png"), width = w, height = h,
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lecorguille
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585 units = "px")
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586 } else {
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587 xcmsBoxPlot(values[seq(length = eicmax),],
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lecorguille
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588 sampclass(object), dirpath=boxdir, pic="pdf",
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lecorguille
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589 width=w, height=h)
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590 pdf(file.path(eicdir, "%003d.pdf"), width = w/72,
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lecorguille
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591 height = h/72, onefile = FALSE)
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592 }
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593 }
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594
11
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lecorguille
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595 plotSpecWindow(object, gidxs = tsidx[seq(length = eicmax)], borderwidth=1)
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596
11
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lecorguille
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597 if (length(filebase))
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598 dev.off()
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599 }
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600 }
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601
11
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602 invisible(twosamp)
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603 }