#### 1,roseq model 

Extract the lines of EBVMutu of each bigwig in merge data (roseq/mergeEBV), make the dataset and input them to the 2 roseq models R & RD(with dna sequence) to predict the 10 Histone modifications after different treating hours.

The output are under roseq/R_EBVxh and roseq/RD_EBVxh

#### 2,chromHMM

Input the 6 Histone modification (.bed) data of EBVMutu from the two roseq model prediction result ，including H3K4me1,H3K4me3,H3K9me3,H3K27me3,H3K27ac,H3K36me3  (chromhmm/inputdata).

First convert them into signal format with python program. Then use the BinarizeSignal,  LearnModel, MakeSegmentation command in chromHMM program, which output a segmentation each time, assigning each location in the genome to an instance of 18 chromatin state.

The results are under chromhmm/MakeSegmentation_output.