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ScHiCNorm: a software package to eliminate systematic biases in single-cell Hi-C data.


ABSTRACT: Summary: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 information:Supplementary data are available at Bioinformatics online.

PROVIDER: S-EPMC5860379 | BioStudies |

REPOSITORIES: biostudies

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