Open AccessA novel method to identify topological domains using Hi‐C data
Author(s) -
Wang Yang,
Li Yanjian,
Gao Juntao,
Zhang Michael Q.
Publication year - 2015
Publication title -
quantitative biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.707
H-Index - 15
eISSN - 2095-4697
pISSN - 2095-4689
DOI - 10.1007/s40484-015-0047-9
Subject(s) - chromatin , chromosome conformation capture , cluster analysis , computational biology , chromosome , domain (mathematical analysis) , computer science , genome , biology , data mining , topology (electrical circuits) , evolutionary biology , genetics , artificial intelligence , gene , mathematics , combinatorics , mathematical analysis , gene expression , enhancer
Over the last decade the 3C‐based (Chromosome Conformation Capture, 3C) approaches have been developed to describe the frequency of chromatin interaction. The invention of Hi‐C allows us to obtain genome‐wide chromatin interaction map. However, it is challenging to develop efficient and robust analytical tools to interpret the Hi‐C data. Here we present a new method called Clustering based Hi‐C Domain Finder (CHDF), which is based on the difference of interaction intensity inside/outside domains, to identify Hi‐C domains. We also compared CHDF with existing methods including Direction Index (DI) and HiCseg. CHDF can define more chromatin domains validated by higher resolution local chromatin structure data (Chromosome Conformation Capture Carbon Copy (5C) data). Using Hi‐C data of lower sequencing depth, chromatin structure identified by CHDF is closer to that discovered by data of higher sequencing depth. Furthermore, the implement of CHDF is faster than the other two. Using CHDF, we are potentially able to discover more hints and clues about chromatin structural elements at domain level.