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

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 demonstrate...

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Detalles Bibliográficos
Autores principales: Liu, Huiling, Ma, Wenxiu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Applications Note
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10598576/
https://www.ncbi.nlm.nih.gov/pubmed/37847655
http://dx.doi.org/10.1093/bioinformatics/btad625
Descripción
Sumario: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).

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