title: Statistical analysis of ChIP-seq data with MOSAiCS.
abstract: Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) is invaluable for identifying genome-wide binding of transcription factors and mapping of epigenomic profiles. We present a statistical protocol for analyzing ChIP-seq data. We describe guidelines for data preprocessing and quality control and provide detailed examples of identifying ChIP-enriched regions using the Bioconductor package "mosaics."
authors.affiliation: Department of Statistics, University of Wisconsin, Madison, WI, USA.
authors.forename: Guannan
authors.initials: G
authors.lastname: Sun
authors.forename: Dongjun
authors.initials: D
authors.lastname: Chung
authors.forename: Kun
authors.initials: K
authors.lastname: Liang
authors.forename: Sündüz
authors.initials: S
authors.lastname: Keleş
mesh_terms: D001665:Binding Sites; D047369:Chromatin Immunoprecipitation / Q000379:methods; D016678:Genome; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D006801:Humans; D015233:Models, Statistical; D012044:Regression Analysis; D012984:Software; D014157:Transcription Factors / Q000378:metabolism
chemical_list: D014157:Transcription Factors