MIA-Sig: multiplex chromatin interaction analysis by signal processing and statistical algorithms.

Authors

Minji Kim, The Jackson LaboratoryFollow
Meizhen Zheng, The Jackson LaboratoryFollow
Simon Zhongyuan Tian, The Jackson LaboratoryFollow
Byoungkoo Lee, The Jackson LaboratoryFollow
Jeffrey Chuang, The Jackson LaboratoryFollow
Yijun Ruan, The Jackson LaboratoryFollow

Document Type

Article

Publication Date

11-25-2019

Keywords

JGM

JAX Source

Genome Biol 2019 Nov 25; 20(1):251

Volume

20

Issue

1

First Page

251

Last Page

251

ISSN

1474-760X

PMID

31767038

DOI

https://doi.org/10.1186/s13059-019-1868-z

Grant

Jackson Laboratory Director's Innovation Fund, HG009409, DK107967, Human Frontier Science Program, Florine Roux Endowment

Abstract

The single-molecule multiplex chromatin interaction data are generated by emerging 3D genome mapping technologies such as GAM, SPRITE, and ChIA-Drop. These datasets provide insights into high-dimensional chromatin organization, yet introduce new computational challenges. Thus, we developed MIA-Sig, an algorithmic solution based on signal processing and information theory. We demonstrate its ability to de-noise the multiplex data, assess the statistical significance of chromatin complexes, and identify topological domains and frequent inter-domain contacts. On chromatin immunoprecipitation (ChIP)-enriched data, MIA-Sig can clearly distinguish the protein-associated interactions from the non-specific topological domains. Together, MIA-Sig represents a novel algorithmic framework for multiplex chromatin interaction analysis.

Comments

This open access article is licensed under a Creative Commons Attribution 4.0 International License

Recommended Citation

Kim M, Zheng M, Tian S, Lee B, Chuang J, Ruan Y. MIA-Sig: multiplex chromatin interaction analysis by signal processing and statistical algorithms. Genome Biol 2019 Nov 25; 20(1):251