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Quantitative Biology

ISSN 2095-4689

ISSN 2095-4697(Online)

CN 10-1028/TM

邮发代号 80-971

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Quantitative Biology  2015, Vol. 3 Issue (2): 81-89   https://doi.org/10.1007/s40484-015-0047-9
  RESEARCH ARTICLE 本期目录
A novel method to identify topological domains using Hi-C data
Yang Wang1,Yanjian Li1,2,Juntao Gao1,*(),Michael Q. Zhang1,3,*()
1. MOE Key Laboratory of Bioinformatics; Bioinformatics Division and Center for Synthetic & Systems Biology, TNLIST; Department of Automation, Tsinghua University, Beijing 100084, China
2. Department of Basic Medical Sciences, School of Medicine, Tsinghua University, Beijing 100084, China
3. Department of Molecular and Cell Biology, Center for Systems Biology, the University of Texas at Dallas, Richardson, TX 75080, USA
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Abstract：

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.
Key words： chromatin domain    Hi-C    dynamic programming
收稿日期: 2015-04-10      出版日期: 2015-08-21
Corresponding Author(s): Juntao Gao,Michael Q. Zhang   
 引用本文:   
. [J]. Quantitative Biology, 2015, 3(2): 81-89.
Yang Wang, Yanjian Li, Juntao Gao, Michael Q. Zhang. A novel method to identify topological domains using Hi-C data. Quant. Biol., 2015, 3(2): 81-89.
 链接本文:  
https://academic.hep.com.cn/qb/CN/10.1007/s40484-015-0047-9
https://academic.hep.com.cn/qb/CN/Y2015/V3/I2/81
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