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COCOA: coordinate covariation analysis of epigenetic heterogeneity

Authors :
John T. Lawson
Jason P. Smith
Stefan Bekiranov
Francine E. Garrett-Bakelman
Nathan C. Sheffield
Source :
Genome Biology, Vol 21, Iss 1, Pp 1-23 (2020)
Publication Year :
2020
Publisher :
BMC, 2020.

Abstract

Abstract A key challenge in epigenetics is to determine the biological significance of epigenetic variation among individuals. We present Coordinate Covariation Analysis (COCOA), a computational framework that uses covariation of epigenetic signals across individuals and a database of region sets to annotate epigenetic heterogeneity. COCOA is the first such tool for DNA methylation data and can also analyze any epigenetic signal with genomic coordinates. We demonstrate COCOA’s utility by analyzing DNA methylation, ATAC-seq, and multi-omic data in supervised and unsupervised analyses, showing that COCOA provides new understanding of inter-sample epigenetic variation. COCOA is available on Bioconductor ( http://bioconductor.org/packages/COCOA ).

Details

Language :
English
ISSN :
1474760X
Volume :
21
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Genome Biology
Publication Type :
Academic Journal
Accession number :
edsdoj.bc97834d68b740c984d5e872e29801cd
Document Type :
article
Full Text :
https://doi.org/10.1186/s13059-020-02139-4