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Nat Protoc. 2017 Dec;12(12):2478-2492. doi: 10.1038/nprot.2017.124. Epub 2017 Nov 9.

Chromatin-state discovery and genome annotation with ChromHMM.

Ernst J1,2,3,4,5, Kellis M6,7.

Author information

1
Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, California, USA.
2
Department of Computer Science, University of California, Los Angeles, Los Angeles, California, USA.
3
Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research at University of California, Los Angeles, Los Angeles, California, USA.
4
Jonsson Comprehensive Cancer Center, University of California, Los Angeles, Los Angeles, California, USA.
5
Molecular Biology Institute, University of California, Los Angeles, Los Angeles, California, USA.
6
Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.
7
MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, Massachusetts, USA.

Abstract

Noncoding DNA regions have central roles in human biology, evolution, and disease. ChromHMM helps to annotate the noncoding genome using epigenomic information across one or multiple cell types. It combines multiple genome-wide epigenomic maps, and uses combinatorial and spatial mark patterns to infer a complete annotation for each cell type. ChromHMM learns chromatin-state signatures using a multivariate hidden Markov model (HMM) that explicitly models the combinatorial presence or absence of each mark. ChromHMM uses these signatures to generate a genome-wide annotation for each cell type by calculating the most probable state for each genomic segment. ChromHMM provides an automated enrichment analysis of the resulting annotations to facilitate the functional interpretations of each chromatin state. ChromHMM is distinguished by its modeling emphasis on combinations of marks, its tight integration with downstream functional enrichment analyses, its speed, and its ease of use. Chromatin states are learned, annotations are produced, and enrichments are computed within 1 d.

PMID:
29120462
PMCID:
PMC5945550
DOI:
10.1038/nprot.2017.124
[Indexed for MEDLINE]
Free PMC Article

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