HiC-DC plus enables systematic 3D interaction calls and differential analysis for Hi-C and HiChIP

被引:25
|
作者
Sahin, Merve [1 ,2 ]
Wong, Wilfred [1 ,2 ]
Zhan, Yingqian [3 ]
Van Deynze, Kinsey [4 ]
Koche, Richard [3 ]
Leslie, Christina S. [1 ]
机构
[1] Mem Sloan Kettering Canc Ctr, Computat & Syst Biol Program, New York, NY 10021 USA
[2] Triinst Training Program Computat Biol & Med, New York, NY USA
[3] Mem Sloan Kettering Canc Ctr, Ctr Epigenet Res, New York, NY USA
[4] Univ Calif San Diego, Bioinformat Program, La Jolla, CA USA
关键词
DNA LOOPS; RESOLUTION; GENOME; PROVIDES;
D O I
10.1038/s41467-021-23749-x
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Recent genome-wide chromosome conformation capture assays such as Hi-C and HiChIP have vastly expanded the resolution and throughput with which we can study 3D genomic architecture and function. Here, we present HiC-DC+, a software tool for Hi-C/HiChIP interaction calling and differential analysis using an efficient implementation of the HiC-DC statistical framework. HiC-DC+ integrates with popular preprocessing and visualization tools and includes topologically associating domain (TAD) and A/B compartment callers. We found that HiC-DC+ can more accurately identify enhancer-promoter interactions in H3K27ac HiChIP, as validated by CRISPRi-FlowFISH experiments, compared to existing methods. Differential HiC-DC+ analyses of published HiChIP and Hi-C data sets in settings of cellular differentiation and cohesin perturbation systematically and quantitatively recovers biological findings, including enhancer hubs, TAD aggregation, and the relationship between promoter-enhancer loop dynamics and gene expression changes. HiC-DC+ therefore provides a principled statistical analysis tool to empower genome-wide studies of 3D chromatin architecture and function. The genome-wide investigation of chromatin organization enables insights into global gene expression control. Here, the authors present a computationally efficient method for the analysis of chromatin organization data and use it to recover principles of 3D organization across conditions.
引用
收藏
页数:11
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