Next Generation Microarray Bioinformatics

Volume 802 of the series Methods in Molecular Biology pp 275-291


Analyzing ChIP-seq Data: Preprocessing, Normalization, Differential Identification, and Binding Pattern Characterization

  • Cenny TaslimAffiliated withDepartment of Molecular Virology, Immunology & Medical Genetics, The Ohio State UniversityDepartment of Statistics, The Ohio State University
  • , Kun HuangAffiliated withDepartment of Biomedical Informatics, The Ohio State University
  • , Tim HuangAffiliated withDepartment of Molecular Virology, Immunology & Medical Genetics, The Ohio State University
  • , Shili LinAffiliated withDepartment of Statistics, The Ohio State University Email author 

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Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is a high-throughput antibody-based method to study genome-wide protein–DNA binding interactions. ChIP-seq technology allows scientist to obtain more accurate data providing genome-wide coverage with less starting material and in shorter time compared to older ChIP-chip experiments. Herein we describe a step-by-step guideline in analyzing ChIP-seq data including data preprocessing, nonlinear normalization to enable comparison between different samples and experiments, statistical-based method to identify differential binding sites using mixture modeling and local false discovery rates (fdrs), and binding pattern characterization. In addition, we provide a sample analysis of ChIP-seq data using the steps provided in the guideline.

Key words

ChIP-seq Finite mixture model Model-based classification Nonlinear normalization Differential analysis