R/getSumreplicates.R

In jaspershen/MSannotator: xMSannotator: R package for network based annotation of metabolomics data.

getSumreplicates <-
function(curdata,alignment.tool,numreplicates,numcluster,rep.max.missing.thresh,summary.method="mean",summary.na.replacement="zeros",missing.val=0)
{
		 mean_replicate_difference<-{}
		sd_range_duplicate_pairs<-{}
		  #print(alignment.tool)
		if(alignment.tool=="apLCMS")
		{
		      col_end=2
		}
		else
		{
		      if(alignment.tool=="XCMS")
		      {
			    col_end=2
		      }
		      else
		      {
			    stop(paste("Invalid value for alignment.tool. Please use either \"apLCMS\" or \"XCMS\"", sep=""))
		      }
		}
		
		curdata_mz_rt_info=curdata[,c(1:col_end)]
		curdata=curdata[,-c(1:col_end)]
		
		
		
		cl<-makeCluster(numcluster)
		numfeats=dim(curdata)[1]
		numsamp=dim(curdata)[2]	

		clusterEvalQ(cl, "getSumreplicateschild")
		sub_samp_list<-list()
	
		sampcount=1
		for(samp in seq(1,(numsamp),numreplicates))
                {
                        i=samp
                        j=i+numreplicates-1
			if(dim(curdata[,c(i:j)])[1]>0){
                        sub_samp_list[[sampcount]]=curdata[,c(i:j)]
                        }
			sampcount=sampcount+1
                }
		
		avg.res<-parSapply(cl,sub_samp_list,getSumreplicateschild,alignment.tool=alignment.tool,numreplicates=numreplicates,rep.max.missing.thresh=rep.max.missing.thresh,method=summary.method,missing.val=missing.val)
		#avg.res<-getAvgreplicateschild(sub_samp_list[[1]],alignment.tool,numreplicates)
		#print("done")
		
		
		stopCluster(cl)
		
		
			
			final_set<-as.data.frame(avg.res)
			colnames_data<-colnames(curdata)
			colnames_data<-colnames_data[seq(1,(numsamp),numreplicates)]
			colnames(final_set)<-colnames_data
			rownames(final_set)=NULL
			#final_set<-cbind(curdata_mz_rt_info,final_set)
		
		final_set<-apply(final_set,2,as.numeric)
		
		
		if(summary.na.replacement=="zeros"){
			
			final_set<-replace(final_set,which(is.na(final_set)==TRUE),0)
		}else{
			if(summary.na.replacement=="halfsamplemin"){
				
			
		final_set<-apply(final_set,2,function(x){naind<-which(is.na(x)==TRUE); if(length(naind)>0){x[naind]<-min(x,na.rm=TRUE)/2}; return(x)})
		}else{
			
			if(summary.na.replacement=="halfdatamin"){
				
				
			min_val<-min(final_set,na.rm=TRUE)*0.5
			final_set<-replace(final_set,which(is.na(final_set)==TRUE),min_val)

			#data_m<-apply(data_m,1,function(x){naind<-which(is.na(x)==TRUE); if(length(naind)>0){x[naind]<-min(x,na.rm=TRUE)/2}; return(x)})
			}else{
			if(summary.na.replacement=="halffeaturemin"){
				
				
			final_set<-apply(final_set,1,function(x){naind<-which(is.na(x)==TRUE); if(length(naind)>0){x[naind]<-min(x,na.rm=TRUE)/2}; return(x)})
			final_set<-t(final_set)
			}
			}
		}
			
			
		}
		
		return(final_set)
}