require(limma)
	
makeGroupContrasts<-function(groups){
	unique.groups<-unique(groups)
	results <- rep("", length(unique.groups)*(length(unique.groups)-1)/2)
	counter<-1
	for (i in 1:(length(unique.groups)-1))
		for (j in (i+1):length(unique.groups)){
			results[counter]<-paste(unique.groups[i],"-", unique.groups[j], sep="")
			counter<-counter+1
			}
	results
	}
	
	

RunIndividualsAgainstRefForScore<-function(indiv.data, ref.data, ref.groups){
	results <- matrix(NA, nrow=dim(indiv.data)[1], ncol=dim(indiv.data)[2])
	rownames(results)<-rownames(indiv.data)
	colnames(results)<-colnames(indiv.data)
	for (i in 1:dim(indiv.data)[2]){
		data<-cbind(indiv.data[,i], ref.data)
		indiv.name<-colnames(indiv.data)[i]
		groups<-c(indiv.name, ref.groups)
		colX <- RunOneGroupForScore(data, groups, indiv.name)
		results[,i]<-colX
		cat("sample", indiv.name, "done\n")
		}
	results
	}



RunOneGroupForScore<-function(data,groups, groupX){
	f<-factor(groups, levels=unique(groups))
	design<-model.matrix(~0+f)
	colnames(design)<-unique(groups)
	mycontrasts<-makeContrasts(contrasts= makeGroupContrastsForOne(groupX,groups), levels=design)
	fit<-lmFit(data, design)
	fit2<-eBayes(contrasts.fit(fit, mycontrasts))
	
	fit.test<-p.adjust(fit2$p.value, method="bonferroni")
	select <- fit.test > 0.05
	fit.coef <- fit2$coef
	fit.coef[select] <- 0
	apply(fit.coef, 1, sum)

}

makeGroupContrastsForOne<-function(groupX, groups){
	unique.groups<-unique(groups)
	results <- rep("", length(unique.groups)-1)
	counter <- 1
	for (groupY in unique.groups)
		if (groupX!=groupY){
			results[counter]<-paste(groupX,"-", groupY, sep="")
			counter <- counter+1
			}
	results
	}