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

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...

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Bibliographic Details
Main Authors: Minji Kim, Meizhen Zheng, Simon Zhongyuan Tian, Byoungkoo Lee, Jeffrey H. Chuang, Yijun Ruan
Format: Article
Language:English
Published: BMC 2019-11-01
Series:Genome Biology
Subjects:
Online Access:http://link.springer.com/article/10.1186/s13059-019-1868-z
Description
Summary: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.
ISSN:1474-760X