ChIPnorm: a statistical method for normalizing and identifying differential regions in histone modification ChIP-seq libraries.

ABSTRACT: The advent of high-throughput technologies such as ChIP-seq has made possible the study of histone modifications. A problem of particular interest is the identification of regions of the genome where different cell types from the same organism exhibit different patterns of histone enrichment. This problem turns out to be surprisingly difficult, even in simple pairwise comparisons, because of the significant level of noise in ChIP-seq data. In this paper we propose a two-stage statistical method, called ChIPnorm, to normalize ChIP-seq data, and to find differential regions in the genome, given two libraries of histone modifications of different cell types. We show that the ChIPnorm method removes most of the noise and bias in the data and outperforms other normalization methods. We correlat

SUBMITTER: Nair NU 

PROVIDER: S-EPMC3411705 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature