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Nat Commun. 2015 Aug 18;6:7973. doi: 10.1038/ncomms8973.

Systematic chromatin state comparison of epigenomes associated with diverse properties including sex and tissue type.

Author information

1
1] Electrical Engineering and Computer Science Department, Computer Science and Artificial Intelligence Laboratory, MIT, 32 Vassar Street, 32D-524, Cambridge, Massachusetts 02139, USA [2] Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.

Abstract

Epigenomic data sets provide critical information about the dynamic role of chromatin states in gene regulation, but a key question of how chromatin state segmentations vary under different conditions across the genome has remained unaddressed. Here we present ChromDiff, a group-wise chromatin state comparison method that generates an information-theoretic representation of epigenomes and corrects for external covariate factors to better isolate relevant chromatin state changes. By applying ChromDiff to the 127 epigenomes from the Roadmap Epigenomics and ENCODE projects, we provide novel group-wise comparative analyses across sex, tissue type, state and developmental age. Remarkably, we find that distinct sets of epigenomic features are maximally discriminative for different group-wise comparisons, in each case revealing distinct enriched pathways, many of which do not show gene expression differences. Our methodology should be broadly applicable for epigenomic comparisons and provides a powerful new tool for studying chromatin state differences at the genome scale.

PMID:
26282110
PMCID:
PMC4557131
DOI:
10.1038/ncomms8973
[Indexed for MEDLINE]
Free PMC Article

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