ChromDMM: a Dirichlet-multinomial mixture model for clustering heterogeneous epigenetic data.

ABSTRACT:

Motivation

Research on epigenetic modifications and other chromatin features at genomic regulatory elements elucidates essential biological mechanisms including the regulation of gene expression. Despite the growing number of epigenetic datasets, new tools are still needed to discover novel distinctive patterns of heterogeneous epigenetic signals at regulatory elements.

Results

We introduce ChromDMM, a product Dirichlet-multinomial mixture model for clustering genomic regions that are characterized by multiple chromatin features. ChromDMM extends the mixture model framework by profile shifting and flipping that can probabilistically account for inaccuracies in the position and strand-orientation of the genomic regions. Owing to hyper-parameter optimization, ChromDMM can also

SUBMITTER: Osmala M 

PROVIDER: S-EPMC9364382 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature