Nature Communications (Apr 2017)

Multi-scale chromatin state annotation using a hierarchical hidden Markov model

  • Eugenio Marco,
  • Wouter Meuleman,
  • Jialiang Huang,
  • Kimberly Glass,
  • Luca Pinello,
  • Jianrong Wang,
  • Manolis Kellis,
  • Guo-Cheng Yuan

DOI
https://doi.org/10.1038/ncomms15011
Journal volume & issue
Vol. 8, no. 1
pp. 1 – 9

Abstract

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The impact of chromatin structure on gene expression makes it integral to our understanding of developmental and disease processes. Here, the authors introduce a hierarchical hidden Markov model to systematically annotate chromatin states at multiple length scales, and demonstrate its utility for the elucidation of the role of chromatin structure in gene expression.