EPIGENE: genome-wide transcription unit annotation using a multivariate probabilistic model of histone modifications.

ABSTRACT:

Background

Understanding the transcriptome is critical for explaining the functional as well as regulatory roles of genomic regions. Current methods for the identification of transcription units (TUs) use RNA-seq that, however, require large quantities of mRNA rendering the identification of inherently unstable TUs, e.g. miRNA precursors, difficult. This problem can be alleviated by chromatin-based approaches due to a correlation between histone modifications and transcription.

Results

Here, we introduce EPIGENE, a novel chromatin segmentation method for the identification of active TUs using transcription-associated histone modifications. Unlike the existing chromatin segmentation approaches, EPIGENE uses a constrained, semi-supervised multivariate hidden Markov model (HMM)

SUBMITTER: Sahu A 

PROVIDER: S-EPMC7137282 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature