Continuous chromatin state feature annotation of the human epigenome.

ABSTRACT:

Motivation

Segmentation and genome annotation (SAGA) algorithms are widely used to understand genome activity and gene regulation. These methods take as input a set of sequencing-based assays of epigenomic activity, such as ChIP-seq measurements of histone modification and transcription factor binding. They output an annotation of the genome that assigns a chromatin state label to each genomic position. Existing SAGA methods have several limitations caused by the discrete annotation framework: such annotations cannot easily represent varying strengths of genomic elements, and they cannot easily represent combinatorial elements that simultaneously exhibit multiple types of activity. To remedy these limitations, we propose an annotation strategy that instead outputs a vector of chrom

SUBMITTER: Daneshpajouh H 

PROVIDER: S-EPMC9154241 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature