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Analyzing ChIP-seq Data: Preprocessing, Normalization, Differential Identification, and Binding Pattern Characterization.
Methods Mol Biol. 2012;802:275-91
Authors: Taslim C, Huang K, Huang T, Lin S
Abstract
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.
PMID: 22130887 [PubMed - in process]
More...
Analyzing ChIP-seq Data: Preprocessing, Normalization, Differential Identification, and Binding Pattern Characterization.
Methods Mol Biol. 2012;802:275-91
Authors: Taslim C, Huang K, Huang T, Lin S
Abstract
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.
PMID: 22130887 [PubMed - in process]
More...