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

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

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...

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ژورنال

عنوان ژورنال: Nature Communications

سال: 2017

ISSN: 2041-1723

DOI: 10.1038/ncomms15011