Introduction to scHiCNorm

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scHiCNorm is a software package for eliminating systematic biases in single-cell Hi-C data. Considering that single-cell Hi-C data are zero-inflated, here we use zero-inflated (Poisson and Negative Binomial) and hurdle (Poisson and Negative Binomial) models to remove biases, including cutting sites, GC content, and mappability.

Download

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Source code can be downloaded here (16K). And you can get the feature files (DpnII, cutting enzyme) for Human-hg19 (620M), Human-hg38 (622M), Mouse-mm9 (544M), and Mouse-mm10 (545M). You can also download the feature files for a specific chromosome here.

Reference

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Tong Liu and Zheng Wang. scHiCNorm: a software package to eliminate systematic biases in single-cell Hi-C data. Bioinformatics 2018;34(6):1046-1047.

Contact

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For any questions or suggestions, please contact:
Dr. Zheng Wang
Department of Computer Science
University of Miami