R/getVennv2.R

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

getVennv2 <-
function(dataA,name_a, dataB,name_b,mz.thresh=10,time.thresh=30,alignment.tool=NA, xMSanalyzer.outloc,use.unique.mz=FALSE,plotvenn=TRUE)
{
	dir.create(xMSanalyzer.outloc,showWarnings=FALSE)
	
    plotvenn=FALSE
	data_a<-as.data.frame(dataA)
    data_b<-as.data.frame(dataB)
	rm(dataA)
	rm(dataB)

	############################################
#find.Overlapping.mzs<-function(dataA, dataB, mz.thresh=10, time.thresh=NA, alignment.tool=NA)
	
	if(use.unique.mz==TRUE){
	data_a<-find.Unique.mzs.sameset(dataA=data_a,dataB=data_a,mz.thresh=mz.thresh,time.thresh=time.thresh,alignment.tool=alignment.tool)
	data_a<-data_a$uniqueA
	
	#print(dim(data_a))
	
	data_b<-find.Unique.mzs.sameset(dataA=data_b,dataB=data_b,mz.thresh=mz.thresh,time.thresh=time.thresh,alignment.tool=alignment.tool)
	data_b<-data_b$uniqueA
	}
	common<-find.Overlapping.mzs(data_a,data_b,mz.thresh,time.thresh=time.thresh,alignment.tool=alignment.tool)
	
	if(length(common)>0){
	commonA<-data_a[c(common$index.A),]
	commonA<-unique(commonA)
	
	commonB<-data_b[c(common$index.B),]
	commonB<-unique(commonB)
	
	data_a<-data_a[-c(common$index.A),]
	data_b<-data_b[-c(common$index.B),]
	
	

	rm_index<-which(data_a$mz%in%common$mz.data.A)
	
	if(length(rm_index)>0){
		uniqueA<-data_a[-rm_index,]
	}else{
		uniqueA<-data_a
	}
	
	rm_index<-which(data_b$mz%in%common$mz.data.B)
	
	if(length(rm_index)>0){
		uniqueB<-data_b[-rm_index,]
	}else{
		uniqueB<-data_b
	}
	
	#uniqueA<-data_a[-c(common$index.A),]
	#uniqueB<-data_b[-c(common$index.B),]
	num_commonA<-length(unique(common$index.A))
	num_commonB<-length(unique(common$index.B))
	
	num_common<-min(num_commonA,num_commonB)[1]
	}else{
	uniqueA<-data_a
	uniqueB<-data_b
	num_common<-0
	commonA<-{}
	commonB<-{}
	}
	num_commonA<-num_common
	num_commonB<-num_common
	num_uniqueA<-dim(uniqueA)[1]
	num_uniqueB<-dim(uniqueB)[1]
	
	#print(num_commonA)
	#print(num_uniqueA)
	g1 <-c(seq(1,(num_commonA+num_uniqueA)))
	g2<-c(seq(1,(num_commonB+num_uniqueB)))

	g1[1:num_commonA]=paste("x_",g1[1:num_commonA],sep="")
	g2[1:num_commonB]=paste("x_",g2[1:num_commonB],sep="")
	
	if(num_uniqueA>0){
	g1[(num_commonA+1):(num_commonA+num_uniqueA)]=paste("y_",g1[(num_commonA+1):(num_commonA+num_uniqueA)],sep="")
	}
	if(num_uniqueA>0){
		g2[(num_commonB+1):(num_commonB+num_uniqueB)]=paste("z_",g2[(num_commonB+1):(num_commonB+num_uniqueB)],sep="")
	}
	set1=as.character(g1)
	set2=as.character(g2)
	universe <- sort(unique(c(set1,set2)))
	
	Counts <- matrix(0, nrow=length(universe), ncol=2)
	colnames(Counts) <- c(name_a, name_b)
	for (i in 1:length(universe))
	{
		Counts[i,1] <- universe[i] %in% set1
		Counts[i,2] <- universe[i] %in% set2
	}
	fname<-paste(xMSanalyzer.outloc,"/Venn", name_a,"_",name_b,"_",mz.thresh,"ppm",time.thresh,"s.pdf",sep="")
	
	
	return(list("common"=common,"commonA"=commonA,"uniqueA"=uniqueA,"commonB"=commonB,"uniqueB"=uniqueB))
	
}