We build a software package scHiCNorm that uses zero-inflated and hurdle models to remove biases from single-cell Hi-C data. Our evaluations prove that our models can effectively eliminate systematic biases for single-cell Hi-C data, which better reveal cell-to-cell variances in terms of chromosomal structures. Availability and implementation scHiCNorm is available at http://dna.cs.miami.edu/scHiCNorm/. Perl scripts are provided that can generate bias features. Pre-built bias features for human (hg19 and hg38) and mouse (mm9 and mm10) are available to download. R scripts can be downloaded to remove biases. Contact zheng.wang@miami.edu Supplementary informationSupplementary dataare available at Bioinformatics online.
CITATION STYLE
Liu, T., & Wang, Z. (2018). ScHiCNorm: A software package to eliminate systematic biases in single-cell Hi-C data. Bioinformatics, 34(6), 1046–1047. https://doi.org/10.1093/bioinformatics/btx747
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