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scHiCNorm: a software package to eliminate systematic biases in single-cell Hi-C data.
Bioinformatics 2018 March 16
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 https://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: [email protected].
Supplementary information: Supplementary data are available at Bioinformatics online.
Availability and implementation: scHiCNorm is available at https://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: [email protected].
Supplementary information: Supplementary data are available at Bioinformatics online.
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