Multi-scale chromatin state annotation using a hierarchical hidden Markov model
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Multi-scale chromatin.pdf
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Author(s)
Huang, Jialiang
Glass, Kimberly
Pinello, Luca
Yuan, Guo-Cheng
Marco Rubio, Eugenio
Meuleman, Wouter
Wang, Jianrong
Kellis, Manolis
Date Issued
April 2017
Journal
Nature Communications
Publisher
Nature Publishing Group
Citation
Marco, Eugenio, Wouter Meuleman, Jialiang Huang, Kimberly Glass, Luca Pinello, Jianrong Wang, Manolis Kellis, and Guo-Cheng Yuan. “Multi-Scale Chromatin State Annotation Using a Hierarchical Hidden Markov Model.” Nature Communications 8 (April 7, 2017): 15011.
Version
Final published version
Abstract
Chromatin-state analysis is widely applied in the studies of development and diseases. However, existing methods operate at a single length scale, and therefore cannot distinguish large domains from isolated elements of the same type. To overcome this limitation, we present a hierarchical hidden Markov model, diHMM, to systematically annotate chromatin states at multiple length scales. We apply diHMM to analyse a public ChIP-seq data set. diHMM not only accurately captures nucleosome-level information, but identifies domain-level states that vary in nucleosome-level state composition, spatial distribution and functionality. The domain-level states recapitulate known patterns such as super-enhancers, bivalent promoters and Polycomb repressed regions, and identify additional patterns whose biological functions are not yet characterized. By integrating chromatin-state information with gene expression and Hi-C data, we identify context-dependent functions of nucleosome-level states. Thus, diHMM provides a powerful tool for investigating the role of higher-order chromatin structure in gene regulation.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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Creative Commons Attribution 4.0 International License
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DOI of Published Version
https://doi.org/10.1038/ncomms15011
