scHiCDiff: detecting differential chromatin interactions in single-cell Hi-C data

Author:

Liu Huiling1,Ma Wenxiu1ORCID

Affiliation:

1. Department of Statistics, University of California Riverside , Riverside, CA 92521, United States

Abstract

Abstract Summary Here, we presented the scHiCDiff software tool that provides both nonparametric tests and parametirc models to detect differential chromatin interactions (DCIs) from single-cell Hi-C data. We thoroughly evaluated the scHiCDiff methods on both simulated and real data. Our results demonstrated that scHiCDiff, especially the zero-inflated negative binomial model option, can effectively detect reliable and consistent single-cell DCIs between two conditions, thereby facilitating the study of cell type-specific variations of chromatin structures at the single-cell level. Availability and implementation scHiCDiff is implemented in R and freely available at GitHub (https://github.com/wmalab/scHiCDiff).

Funder

National Institute of Health

National Science Foundation

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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