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• W3003886807 abstract "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." @default.
• W3003886807 created "2020-02-07" @default.
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• W3003886807 date "2020-01-31" @default.
• W3003886807 modified "2023-10-16" @default.
• W3003886807 title "decorate: differential epigenetic correlation test" @default.
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• W3003886807 doi "https://doi.org/10.1093/bioinformatics/btaa067" @default.
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