#hierarchical hypothesis testing approach
# 08.08.2016
# Author : Wei Hung Pan

# import library
# https://bioconductor.org/packages/release/bioc/html/DSS.html
library(DSS)

#import data; 5 Germ free vs 5 conventional 
BS_list<-list(); k<-rep(NA,10)
For (i in 1:10){
	k[i]<-paste0(“sample”,i,”.txt”)
	BS_list[[i]]<-read.table(k, header=T)
}

BSobj <- makeBSseqData( BS_list, k )


#run differential methylation test on single position
dmlTest <- DMLtest(BSobj, group1=k[1:5], group2=k[6:10])

# find differential methylation region
DMR<- callDMR(dmlTest, delta= 0.2, p.threshold=0.1, minlen=200)

#extract the methylation sites within the differential methylation region
for( i in DMR$chr){
	Regi<-subset(DMR, chr==i)
	DML<-subset(dmlTest, chr==i)
	InDMR<-rep(0,dim(DML)[2])
	for (j in 1:dim(Regi)[2]){
		for(k in 1:dim(DML)[2]){
			InDMR[i]=1
		}
	}
	if(i ==“chr1”){
	DML_inR<-DML[which(InDMR==1),]
	}
	else{ DML_inR<-rbind(DML_inR,DML[which(InDMR==1)) }
}

#calculate the FDR based on the selected ones
FDR_new<-adj.pvalue(DML$pval)

#the final list after multiple correction
Final_DML<-DML[which(FDR_new<0.05)]

#export the data frame
Write.table(Final_DML, “final_list.txt”)