Cargando…

COCOA: coordinate covariation analysis of epigenetic heterogeneity

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Lawson, John T., Smith, Jason P., Bekiranov, Stefan, Garrett-Bakelman, Francine E., Sheffield, Nathan C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7487606/
https://www.ncbi.nlm.nih.gov/pubmed/32894181
http://dx.doi.org/10.1186/s13059-020-02139-4
_version_ 1783581521307762688
author Lawson, John T.
Smith, Jason P.
Bekiranov, Stefan
Garrett-Bakelman, Francine E.
Sheffield, Nathan C.
author_facet Lawson, John T.
Smith, Jason P.
Bekiranov, Stefan
Garrett-Bakelman, Francine E.
Sheffield, Nathan C.
author_sort Lawson, John T.
collection PubMed
description 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).
format Online
Article
Text
id pubmed-7487606
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-74876062020-09-15 COCOA: coordinate covariation analysis of epigenetic heterogeneity Lawson, John T. Smith, Jason P. Bekiranov, Stefan Garrett-Bakelman, Francine E. Sheffield, Nathan C. Genome Biol Method 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). BioMed Central 2020-09-07 /pmc/articles/PMC7487606/ /pubmed/32894181 http://dx.doi.org/10.1186/s13059-020-02139-4 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Method
Lawson, John T.
Smith, Jason P.
Bekiranov, Stefan
Garrett-Bakelman, Francine E.
Sheffield, Nathan C.
COCOA: coordinate covariation analysis of epigenetic heterogeneity
title COCOA: coordinate covariation analysis of epigenetic heterogeneity
title_full COCOA: coordinate covariation analysis of epigenetic heterogeneity
title_fullStr COCOA: coordinate covariation analysis of epigenetic heterogeneity
title_full_unstemmed COCOA: coordinate covariation analysis of epigenetic heterogeneity
title_short COCOA: coordinate covariation analysis of epigenetic heterogeneity
title_sort cocoa: coordinate covariation analysis of epigenetic heterogeneity
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7487606/
https://www.ncbi.nlm.nih.gov/pubmed/32894181
http://dx.doi.org/10.1186/s13059-020-02139-4
work_keys_str_mv AT lawsonjohnt cocoacoordinatecovariationanalysisofepigeneticheterogeneity
AT smithjasonp cocoacoordinatecovariationanalysisofepigeneticheterogeneity
AT bekiranovstefan cocoacoordinatecovariationanalysisofepigeneticheterogeneity
AT garrettbakelmanfrancinee cocoacoordinatecovariationanalysisofepigeneticheterogeneity
AT sheffieldnathanc cocoacoordinatecovariationanalysisofepigeneticheterogeneity