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 firstname.lastname@example.org Supplementary informationSupplementary dataare available at Bioinformatics online.
ASJC Scopus subject areas
- Statistics and Probability
- Molecular Biology
- Computer Science Applications
- Computational Theory and Mathematics
- Computational Mathematics