HiCNorm: Removing biases in Hi-C data via Poisson regression

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. © The Author 2012. Published by Oxford University Press. All rights reserved.