CscoreTool-M infers 3D sub-compartment probabilities within cell population.

ABSTRACT:

Motivation

Computational inference of genome organization based on Hi-C sequencing has greatly aided the understanding of chromatin and nuclear organization in three dimensions (3D). However, existing computational methods fail to address the cell population heterogeneity. Here we describe a probabilistic-modeling-based method called CscoreTool-M that infers multiple 3D genome sub-compartments from Hi-C data.

Results

The compartment scores inferred using CscoreTool-M represents the probability of a genomic region locating in a specific sub-compartment. Compared to published methods, CscoreTool-M is more accurate in inferring sub-compartments corresponding to both active and repressed chromatin. The compartment scores calculated by CscoreTool-M also help to quantify the level

SUBMITTER: Zheng X 

PROVIDER: S-EPMC10206090 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature