Gabriel E Hoffman1,2,3, Jaroslav Bendl1,2,3,4, Kiran Girdhar1,2,3,4, Panos Roussos1,2,3,4,5. 1. Pamela Sklar Division of Psychiatric Genomics. 2. Icahn Institute for Data Science and Genomic Technology. 3. Department of Genetics and Genomic Sciences. 4. Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA. 5. Mental Illness Research, Education, and Clinical Center (VISN 2 South), James J. Peters VA Medical Center, Bronx, NY, 10468, USA.
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.
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.
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