DeepExDC interprets genomic compartmentalization changes in single-cell Hi-C data.

ABSTRACT: Single-cell Hi-C (scHi-C) technology enables probing of higher-order chromatin structures in individual cells. It provides an opportunity to get a deeper insight into genomic compartmentalization changes of single cells across different conditions, paving the way to a common understanding of the interplay among compartmental organization, genome functions, and cellular phenotypes. Unfortunately, there are only a few methods currently available for the differential analysis of A/B compartments on Hi-C data at the bulk level; the computational analysis of compartmentalization changes at the single-cell level is a field in its infancy. Herein, we propose DeepExDC, an interpretable 1D convolutional neural network for differential analysis of A/B compartments in scHi-C data on a genome-wide sca

SUBMITTER: Lyu H 

PROVIDER: S-EPMC12206447 | biostudies-literature | 2025 May

REPOSITORIES: biostudies-literature