General Information
| Description | Removing biases in Hi-C data via Poisson regression |
| Homepage | http://www.people.fas.harvard.edu/~junliu/HiCNorm/ |
Publications
HiCNorm: removing biases in Hi-C data via Poisson regression
Summary:
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.
Availability:
Freely available on the web at: http://www.people.fas.harvard.edu/∼junliu/HiCNorm/.
Contact:
jliu@stat.harvard.edu
Supplementary information
: Supplementary data are available at Bioinformatics online.
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