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bioRxiv · 10.1101/2020.07.09.195289

COCOA: Coordinate covariation analysis of epigenetic heterogeneity

John T. Lawson·Jason P. Smith·Stefan Bekiranov·Francine E Garrett-Bakelman·Nathan C. Sheffield
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Abstract

A key challenge in epigenetics is to determine the biological significance of epigenetic variation among individuals. Here, 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 COCOAs 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 as a Bioconductor R package (http://bioconductor.org/packages/COCOA).

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John T. Lawson, Jason P. Smith, Stefan Bekiranov, Francine E Garrett-Bakelman, Nathan C. Sheffield. 2020-07-10. COCOA: Coordinate covariation analysis of epigenetic heterogeneity. https://doi.org/10.1101/2020.07.09.195289

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