Principles of ChIP-seq Data Analysis Illustrated with Examples

被引:0
|
作者
Ambrosini, Giovanna [1 ]
Dreos, Rene [1 ]
Bucher, Philipp [1 ]
机构
[1] Swiss Fed Inst Technol Lausanne EPFL, Swiss Inst Expt Canc Res ISREC, CH-1015 Lausanne, Switzerland
关键词
ChIP-seq; DNase I hypersensitive sites; transcription factor binding sites; histone marks; bioinformatics analysis; PROTEIN-DNA INTERACTIONS; PROFILES;
D O I
暂无
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Chromatin immunoprecipitation (ChIP) followed by high-throughput sequencing (ChIP-seq) is a powerful method to determine how transcription factors and other chromatin-associated proteins interact with DNA in order to regulate gene transcription. A single ChIP-seq experiment produces large amounts of highly reproducible data. The challenge is to extract knowledge from the data by thoughtful application of appropriate bioinformatics tools. Here we present a concise introduction into ChIP-seq data analysis in the form of a tutorial based on tools developed by our group. We expose biological questions, explain methods and provide guidelines for the interpretation of the results. While this article focuses on ChIP-seq, most of the algorithms and tools we present are applicable to other chromatin profiling assays based on next generation sequencing (NGS) technology as well.
引用
收藏
页码:682 / 694
页数:13
相关论文
共 50 条
  • [31] CistromeFinder for ChIP-seq and DNase-seq data reuse
    Sun, Hanfei
    Qin, Bo
    Liu, Tao
    Wang, Qixuan
    Liu, Jing
    Wang, Juan
    Lin, Xueqiu
    Yang, Yulin
    Taing, Len
    Rao, Prakash K.
    Brown, Myles
    Zhang, Yong
    Long, Henry W.
    Liu, X. Shirley
    BIOINFORMATICS, 2013, 29 (10) : 1352 - 1354
  • [32] A short survey of computational analysis methods in analysing ChIP-seq data
    Kim H.
    Kim J.
    Selby H.
    Gao D.
    Tong T.
    Phang T.L.
    Tan A.C.
    Human Genomics, 5 (2) : 117 - 123
  • [33] No more mixed signals: Improved ChIP-seq data analysis with greenscreen
    Artur, Mariana A. S.
    PLANT CELL, 2022, 34 (12): : 4673 - 4674
  • [34] Large-Scale Quality Analysis of Published ChIP-seq Data
    Marinov, Georgi K.
    Kundaje, Anshul
    Park, Peter J.
    Wold, Barbara J.
    G3-GENES GENOMES GENETICS, 2014, 4 (02): : 209 - 223
  • [35] An automated analysis pipeline for a large set of ChIP-seq data: AutoChIP
    Taemook Kim
    Wooseok Lee
    Kyudong Han
    Keunsoo Kang
    Genes & Genomics, 2015, 37 : 305 - 311
  • [36] A fully Bayesian hidden Ising model for ChIP-seq data analysis
    Mo, Qianxing
    BIOSTATISTICS, 2012, 13 (01) : 113 - 128
  • [37] An automated analysis pipeline for a large set of ChIP-seq data: AutoChIP
    Kim, Taemook
    Lee, Wooseok
    Han, Kyudong
    Kang, Keunsoo
    GENES & GENOMICS, 2015, 37 (03) : 305 - 311
  • [38] Analysis of Gene Regulatory Networks Inferred from ChIP-seq Data
    Stamoulakatou, Eirini
    Piccardi, Carlo
    Masseroli, Marco
    BIOINFORMATICS AND BIOMEDICAL ENGINEERING, IWBBIO 2019, PT I, 2019, 11465 : 319 - 331
  • [39] Saturation analysis of ChIP-seq data for reproducible identification of binding peaks
    Hansen, Peter
    Hecht, Jochen
    Ibrahim, Daniel M.
    Krannich, Alexander
    Truss, Matthias
    Robinson, Peter N.
    GENOME RESEARCH, 2015, 25 (09) : 1391 - 1400
  • [40] A decade of ChIP-seq
    Marinov, Georgi K.
    BRIEFINGS IN FUNCTIONAL GENOMICS, 2018, 17 (02) : 77 - 79