Comparative study on ChIP-seq data: normalization and binding pattern characterization.

ABSTRACT:

Motivation

Antibody-based Chromatin Immunoprecipitation assay followed by high-throughput sequencing technology (ChIP-seq) is a relatively new method to study the binding patterns of specific protein molecules over the entire genome. ChIP-seq technology allows scientist to get more comprehensive results in shorter time. Here, we present a non-linear normalization algorithm and a mixture modeling method for comparing ChIP-seq data from multiple samples and characterizing genes based on their RNA polymerase II (Pol II) binding patterns.

Results

We apply a two-step non-linear normalization method based on locally weighted regression (LOESS) approach to compare ChIP-seq data across multiple samples and model the difference using an Exponential-Normal(K) mixture model. Fitted mod

SUBMITTER: Taslim C 

PROVIDER: S-EPMC2800347 | biostudies-literature | 2009 Sep

REPOSITORIES: biostudies-literature