Characterizing chromatin landscape from aggregate and single-cell genomic assays using flexible duration modeling.

ABSTRACT: ATAC-seq has become a leading technology for probing the chromatin landscape of single and aggregated cells. Distilling functional regions from ATAC-seq presents diverse analysis challenges. Methods commonly used to analyze chromatin accessibility datasets are adapted from algorithms designed to process different experimental technologies, disregarding the statistical and biological differences intrinsic to the ATAC-seq technology. Here, we present a Bayesian statistical approach that uses latent space models to better model accessible regions, termed ChromA. ChromA annotates chromatin landscape by integrating information from replicates, producing a consensus de-noised annotation of chromatin accessibility. ChromA can analyze single cell ATAC-seq data, correcting many biases generated by

SUBMITTER: Gabitto MI 

PROVIDER: S-EPMC7004981 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature