HiCNorm: removing biases in Hi-C data via Poisson regression.
basic_science · Level V
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- Record sourced from PubMed, PMID 23023982.
- Also identified by DOI 10.1093/bioinformatics/bts570 and PMC identifier 3509491.
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Abstract
We propose a parametric model, HiCNorm, to remove systematic biases in the raw Hi-C contact maps, resulting in a simple, fast, yet accurate normalization procedure. Compared with the existing Hi-C normalization method developed by Yaffe and Tanay, HiCNorm has fewer parameters, runs >1000 times faster and achieves higher reproducibility. Freely available on the web at: http://www.people.fas.harvard.edu/∼junliu/HiCNorm/. jliu@stat.harvard.edu Supplementary data are available at Bioinformatics online.
Medical subject headings
- Chromosome Mapping
- Linear Models
- Software