view lib.r @ 9:7da9252dd983 draft

planemo upload commit 9d47e3b467dbbe0af0d90a937c5e9f2c4b958c4b

# lib.r version="2.2.1"

#The function create a pdf from the different png generated by diffreport
diffreport_png2pdf <- function(filebase, new_file_path) {

  pdfEicOutput = paste(new_file_path,filebase,"-eic_visible_pdf",sep="")
  pdfBoxOutput = paste(new_file_path,filebase,"-box_visible_pdf",sep="")

  system(paste("gm convert ",filebase,"_eic/*.png ",filebase,"_eic.pdf",sep=""))
  system(paste("gm convert ",filebase,"_box/*.png ",filebase,"_box.pdf",sep=""))

  file.copy(paste(filebase,"_eic.pdf",sep=""), pdfEicOutput)
  file.copy(paste(filebase,"_box.pdf",sep=""), pdfBoxOutput)
}

#The function annotateDiffreport without the corr function which bugs
annotatediff <- function(xset=xset, listArguments=listArguments, variableMetadataOutput="variableMetadata.tsv", dataMatrixOutput="dataMatrix.tsv",new_file_path=NULL) {
  # Resolve the bug with x11, with the function png
  options(bitmapType='cairo')

  #Check if the fillpeaks step has been done previously, if it hasn't, there is an error message and the execution is stopped.
  res=try(is.null(xset@filled))

  # ------ annot -------
  listArguments[["calcCiS"]]=as.logical(listArguments[["calcCiS"]])
  listArguments[["calcIso"]]=as.logical(listArguments[["calcIso"]])
  listArguments[["calcCaS"]]=as.logical(listArguments[["calcCaS"]])

  #graphMethod parameter bugs where this parameter is not defined in quick=true
  if(listArguments[["quick"]]==TRUE) {
    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"]])
  }
  else {
    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"]])

  }  
  peakList=getPeaklist(xa,intval=listArguments[["intval"]])
  peakList=cbind(groupnames(xa@xcmsSet),peakList); colnames(peakList)[1] = c("name");


  # --- Multi condition : diffreport --- 
  diffrep=NULL
  if (!is.null(listArguments[["runDiffreport"]]) & nlevels(sampclass(xset))>=2) {
    #Check if the fillpeaks step has been done previously, if it hasn't, there is an error message and the execution is stopped.
    res=try(is.null(xset@filled))
    classes=levels(sampclass(xset))
    x=1:(length(classes)-1)
    for (i in seq(along=x) ) {
      y=1:(length(classes))
      for (n in seq(along=y)){
        if(i+n <= length(classes)){
          filebase=paste(classes[i],class2=classes[i+n],sep="-vs-")

          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"]])
          #combines results
          diffreportTSV=merge(peakList, diffrep[,c("name","fold","tstat","pvalue")], by.x="name", by.y="name", sort=F)
          diffreportTSV=cbind(diffreportTSV[,!(colnames(diffreportTSV) %in% c(sampnames(xa@xcmsSet)))],diffreportTSV[,(colnames(diffreportTSV) %in% c(sampnames(xa@xcmsSet)))])

          if(listArguments[["sortpval"]]){
            diffreportTSV=diffreportTSV[order(diffreportTSV$pvalue), ]
          }
    
          if (listArguments[["convert_param"]]){
              #converting the retention times (seconds) into minutes
              diffreportTSV$rt=diffreportTSV$rt/60;diffreportTSV$rtmin=diffreportTSV$rtmin/60; diffreportTSV$rtmax=diffreportTSV$rtmax/60;
          }
          write.table(diffreportTSV, sep="\t", quote=FALSE, row.names=FALSE, file=paste(new_file_path,filebase,"-tabular_visible_tabular",sep=""))

          if (listArguments[["eicmax"]] != 0) {
              diffreport_png2pdf(filebase, new_file_path)
          }
        }
      }
    }
  }




  # --- variableMetadata ---
  variableMetadata=peakList[,!(make.names(colnames(peakList)) %in% c(make.names(sampnames(xa@xcmsSet))))]
  # if we have 2 conditions, we keep stat of diffrep
  if (!is.null(listArguments[["runDiffreport"]]) & nlevels(sampclass(xset))==2) {
    variableMetadata = merge(variableMetadata, diffrep[,c("name","fold","tstat","pvalue")],by.x="name", by.y="name", sort=F)
    if(exists("listArguments[[\"sortpval\"]]")){
      variableMetadata=variableMetadata[order(variableMetadata$pvalue), ]
    }
  }

  variableMetadataOri=variableMetadata
  if (listArguments[["convert_param"]]){
    #converting the retention times (seconds) into minutes
    print("converting the retention times into minutes in the variableMetadata")
    variableMetadata$rt=variableMetadata$rt/60;variableMetadata$rtmin=variableMetadata$rtmin/60; variableMetadata$rtmax=variableMetadata$rtmax/60;
  }
  #Transform metabolites name
  variableMetadata$name= paste("M",round(variableMetadata$mz,digits=listArguments[["num_digits"]]),"T",round(variableMetadata$rt),sep="")    
  write.table(variableMetadata, sep="\t", quote=FALSE, row.names=FALSE, file=variableMetadataOutput)

  # --- dataMatrix ---
  dataMatrix = peakList[,(make.names(colnames(peakList)) %in% c(make.names(sampnames(xa@xcmsSet))))]
  dataMatrix=cbind(peakList$name,dataMatrix); colnames(dataMatrix)[1] = c("name");

  if (listArguments[["convert_param"]]){
    #converting the retention times (seconds) into minutes
    print("converting the retention times into minutes in the dataMatrix ids")
    peakList$rt=peakList$rt/60
  }
  dataMatrix$name= paste("M",round(peakList$mz,digits=listArguments[["num_digits"]]),"T",round(peakList$rt),sep="")
  write.table(dataMatrix, sep="\t", quote=FALSE, row.names=FALSE, file=dataMatrixOutput)
  
  return(list("xa"=xa,"diffrep"=diffrep,"variableMetadata"=variableMetadataOri));

}


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"){

  #Load the two Rdata to extract the xset objects from positive and negative mode
  cat("\tObject xset from positive mode\n")
  print(xaP)
  cat("\n")  

  cat("\tObject xset from negative mode\n")
  print(xaN)
  cat("\n")
    
  cat("\n")
  cat("\tCombining...\n")
  #Convert the string to numeric for creating matrix
  row=as.numeric(strsplit(ruleset,",")[[1]][1])
  column=as.numeric(strsplit(ruleset,",")[[1]][2])
  ruleset=cbind(row,column)
  #Test if the file comes from an older version tool
  if ((!is.null(xaP)) & (!is.null(xaN))) {
    #Launch the combinexsannos function from CAMERA
    cAnnot=combinexsAnnos(xaP, xaN,pos=pos,tol=tol,ruleset=ruleset)
  } else {
    stop("You must relauch the CAMERA.annotate step with the lastest version.")
  }

  

  if(pos){
    xa=xaP
    listOFlistArgumentsP=listOFlistArguments
    mode="neg. Mode"
  } else {
    xa=xaN
    listOFlistArgumentsN=listOFlistArguments
    mode="pos. Mode"
  }
  intval = "into"; for (steps in names(listOFlistArguments)) { if (!is.null(listOFlistArguments[[steps]]$intval)) intval = listOFlistArguments[[steps]]$intval }
  peakList=getPeaklist(xa,intval=intval)
  peakList=cbind(groupnames(xa@xcmsSet),peakList); colnames(peakList)[1] = c("name");
  variableMetadata=cbind(peakList, cAnnot[, c("isotopes", "adduct", "pcgroup",mode)]);
  variableMetadata=variableMetadata[,!(colnames(variableMetadata) %in% c(sampnames(xa@xcmsSet)))]

  #Test if there are more than two classes (conditions)
  if ( nlevels(sampclass(xaP@xcmsSet))==2 & (!is.null(diffrepN)) & (!is.null(diffrepP))) {
    diffrepP = diffrepP[,c("name","fold","tstat","pvalue")]; colnames(diffrepP) = paste("P.",colnames(diffrepP),sep="")
    diffrepN = diffrepN[,c("name","fold","tstat","pvalue")]; colnames(diffrepN) = paste("N.",colnames(diffrepN),sep="")
    
    variableMetadata = merge(variableMetadata, diffrepP, by.x="name", by.y="P.name")
    variableMetadata = merge(variableMetadata, diffrepN, by.x="name", by.y="N.name")
  } 
    
  rownames(variableMetadata) = NULL
  #TODO: checker
  #colnames(variableMetadata)[1:2] = c("name","mz/rt");

  #If the user want to convert the retention times (seconds) into minutes.
  if (listArguments[["convert_param"]]){
    #converting the retention times (seconds) into minutes
    cat("\tConverting the retention times into minutes\n")
    variableMetadata$rtmed=cAnnot$rt/60; variableMetadata$rtmin=cAnnot$rtmin/60; variableMetadata$rtmax=cAnnot$rtmax/60;
  }

  #If the user want to keep only the metabolites which match a difference
  if(keep_meta){
    variableMetadata=variableMetadata[variableMetadata[,c(mode)]!="",]
  }
      
  #Write the output into a tsv file
  write.table(variableMetadata, sep="\t", quote=FALSE, row.names=FALSE, file=variableMetadataOutput)
  return(variableMetadata);

}