HyperChIP: identification of hypervariable signals across ChIP-seq or ATAC-seq samples

Haojie Chen; Shiqi Tu; Chongze Yuan; Feng Tian; Yijing Zhang; Yihua Sun; Zhen Shao

doi:10.1186/s13059-022-02627-9

HyperChIP: identification of hypervariable signals across ChIP-seq or ATAC-seq samples

Genome Biol. 2022 Feb 28;23(1):62. doi: 10.1186/s13059-022-02627-9.

Authors

Haojie Chen^#^{1

2}, Shiqi Tu^#³, Chongze Yuan⁴, Feng Tian^{1

2}, Yijing Zhang⁵, Yihua Sun⁴, Zhen Shao^{6

7}

Affiliations

¹ CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China.
² University of Chinese Academy of Sciences, Beijing, 100049, China.
³ CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China. tushiqi@picb.ac.cn.
⁴ Department of Thoracic Surgery and State Key Laboratory of Genetic Engineering, Fudan University Shanghai Cancer Center, Shanghai, 200032, China.
⁵ State Key Laboratory of Genetic Engineering, Collaborative Innovation Center of Genetics and Development, Department of Biochemistry, Institute of Plant Biology, School of Life Sciences, Fudan University, Shanghai, 200438, China.
⁶ CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China. shaozhen@picb.ac.cn.
⁷ University of Chinese Academy of Sciences, Beijing, 100049, China. shaozhen@picb.ac.cn.

^# Contributed equally.

Abstract

Identifying genomic regions with hypervariable ChIP-seq or ATAC-seq signals across given samples is essential for large-scale epigenetic studies. In particular, the hypervariable regions across tumors from different patients indicate their heterogeneity and can contribute to revealing potential cancer subtypes and the associated epigenetic markers. We present HyperChIP as the first complete statistical tool for the task. HyperChIP uses scaled variances that account for the mean-variance dependence to rank genomic regions, and it increases the statistical power by diminishing the influence of true hypervariable regions on model fitting. A pan-cancer case study illustrates the practical utility of HyperChIP.

Keywords: ATAC-seq; ChIP-seq; Epigenetic heterogeneity; Hypervariable regions; Large-scale cancer studies.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Chromatin Immunoprecipitation Sequencing*
Genomics
High-Throughput Nucleotide Sequencing*
Humans
Sequence Analysis, DNA