Introduction

ChIP-seq is a powerful technology to measure the protein binding or histone modification strength in the whole genome scale. Although there are a number of methods available for single ChIP-seq data analysis (e.g. 'peak detection'), rigorous statistical method for quantitative comparison of multiple ChIP-seq datasets with the considerations of data from control experiment, signal to noise ratios, biological variations and multiple-factor experimental designs is under-developed.In this work, we develop a statistical method to perform quantitative comparison of multiple ChIP-seq datasets and detect genomic regions showing differential protein binding or histone modification. We first detect peaks from all datasets and then union them to form a single set of candidate regions. The read counts from IP experiment at the candidate regions are assumed to follow Poisson distribution. The underlying Poisson rates are modeled as an experiment-specific function of artifacts and biological signals. We then obtain the estimated biological signals and compare them through the hypothesis testing procedure in a linear model framework. Simulations and real data analyses demonstrate that the proposed method provides more accurate and robust results compared with existing ones.An R software package ChIPComp is freely available at http://web1.sph.emory.edu/users/hwu30/software/ChIPComp.html.

Publications

  1. A novel statistical method for quantitative comparison of multiple ChIP-seq datasets.
    Cite this
    Chen L, Wang C, Qin ZS, Wu H, 2015-06-01 - Bioinformatics (Oxford, England)

Credits

  1. Li Chen
    Developer

    Department of Mathematics and Computer Science, Atlanta, United States of America

  2. Chi Wang
    Developer

    Department of Mathematics and Computer Science, Atlanta, United States of America

  3. Zhaohui S Qin
    Developer

    Department of Mathematics and Computer Science, Atlanta, United States of America

  4. Hao Wu
    Investigator

    Department of Mathematics and Computer Science, Atlanta, United States of America

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Summary
AccessionBT006484
Tool TypeApplication
Category
PlatformsLinux/Unix
TechnologiesR
User InterfaceTerminal Command Line
Download Count0
Country/RegionUnited States of America
Submitted ByHao Wu