1. by mounting conda
2. Firstly HiCPro comes digest_genome.py digested fragment obtained BED program files and chromosomes' size spreadsheet file, requires restriction enzyme cleavage sites and the reference genome information
3. indexed falcon_contig.fasta with bowtie2
HiCPro first bowtie, respectively PE reads employed for comparison
For failure to carry out trim on the ratio of reads and re-alignment
Each R1 & R2 reads the result of the merger than twice
4. Using HiCPro combined PE reads the program mergeSAM.py
HiCPro than using the results of the program mapped_2hic_fragments.py converted to pieces of information Hi-C
Merging all the valid pairs, and removes PCR duplication
Using HiCPro of merge_statfiles.py program bowtie2 merge more than the statistical results of the
It is to build a matrix with BIN_SIZE
Using ice made normalization of raw matrix
The statistical comparison rate, drawing on the statistical results
Reference Source:
Servant, Nicolas, et al. "HiC-Pro: an optimized and flexible pipeline for Hi-C data processing." Genome biology 16.1 (2015): 259.
https://www.jianshu.com/p/9e9261dc5db1