Dataset Information

Decorate: differential epigenetic correlation test.

ABSTRACT:

Motivation

Identifying correlated epigenetic features and finding differences in correlation between individuals with disease compared to controls can give novel insight into disease biology. This framework has been successful in analysis of gene expression data, but application to epigenetic data has been limited by the computational cost, lack of scalable software and lack of robust statistical tests.

Results

Decorate, differential epigenetic correlation test, identifies correlated epigenetic features and finds clusters of features that are differentially correlated between two or more subsets of the data. The software scales to genome-wide datasets of epigenetic assays on hundreds of individuals. We apply decorate to four large-scale datasets of DNA methylation, ATAC-seq and histone modification ChIP-seq.

Availability and implementation

decorate R package is available from https://github.com/GabrielHoffman/decorate.

Supplementary information

Supplementary data are available at Bioinformatics online.

SUBMITTER: Hoffman GE

PROVIDER: S-EPMC7203736 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Publications

decorate: differential epigenetic correlation test.

Hoffman Gabriel E GE Bendl Jaroslav J Girdhar Kiran K Roussos Panos P

Bioinformatics (Oxford, England) 20200501 9

<h4>Motivation</h4>Identifying correlated epigenetic features and finding differences in correlation between individuals with disease compared to controls can give novel insight into disease biology. This framework has been successful in analysis of gene expression data, but application to epigenetic data has been limited by the computational cost, lack of scalable software and lack of robust statistical tests.<h4>Results</h4>Decorate, differential epigenetic correlation test, identifies correla ...[more]

PMID: 32003784

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