R/getSumreplicateschild.R

In kuppal2/xmsPANDA: R Package for Biomarker Discovery, Network, and Data Exploratory Analysis

getSumreplicateschild <-
function(curdata,alignment.tool,numreplicates,rep.max.missing.thresh,method="mean",missing.val)
{
  #curdata<-t(curdata)
  #write.table(curdata,file="test.txt",sep="\t",row.names=FALSE)
  numfeats=dim(curdata)[1]
  numsamp=dim(curdata)[2]
  # if(FALSE){
  resvec_1<-lapply(1:numfeats,function(r)
  {
    newrow={}
    finalmat={}
    #for(samp in seq(1,(numsamp),numreplicates))
    {
      # i=samp
      #j=i+numreplicates-1
      
      curdata_int=curdata[r,]
      
      #if(is.na(missing.val)==FALSE){
      #           check_zeros=which(curdata_int==missing.val)
      #           }else{
      check_zeros=which(is.na(curdata_int)==TRUE)
      #           	}
      na_thresh=round(rep.max.missing.thresh*numreplicates)
      
      
      if(length(check_zeros)>na_thresh)
      {
        meanval<-missing.val
      }
      else
      {
        #temporarily replace the missing intensities, set to 0 in apLCMS,
        #with mean intensity value of the corresponding replicates (with non-zero values)
        #curdata_int[check_zeros]=mean(t(curdata_int[-c(check_zeros)]))
        if(length(check_zeros)>0)
        {
          if(method=="mean"){
            meanval<-mean(t(curdata_int[-check_zeros]),na.rm=TRUE)
          }else{
            meanval<-median(t(curdata_int[-check_zeros]),na.rm=TRUE)
          }
        }
        else
        {
          if(method=="mean"){
            meanval<-mean(t(curdata_int),na.rm=TRUE)
          }else{
            meanval<-median(t(curdata_int),na.rm=TRUE)
          }
        }
        
      }
      newrow<-cbind(newrow,meanval)
    }
    
    
    finalmat<-rbind(finalmat, newrow)
    return(finalmat)
  })
  
  #colnames(final_set)<-colnames_data
  #rownames(final_set)=NULL
  return(resvec_1)
  
  
  
}