Literature DB >> 21938632

Computational analysis of protein-DNA interactions from ChIP-seq data.

Jacques Rougemont1, Felix Naef.   

Abstract

Chromatin immunoprecipitation experiments followed by ultra-high-throughput sequencing (ChIP-seq) is becoming the method of choice to identify transcription factor binding sites in prokaryotes and eukaryotes in vivo. Here, we review the computational steps that are necessary for analyzing the sequenced chromatin fragments, including mapping of short reads onto reference genomes, normalization of multiple conditions, detection of bona fide peaks or binding sites, annotation of sites, characterization of sequence-specific binding affinities, and relationships with biophysical models for protein-DNA interactions. The goal is that following the indicated steps will help the discovery of novel mechanisms underlying transcription regulation in a broad range of experimental systems.

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Year:  2012        PMID: 21938632     DOI: 10.1007/978-1-61779-292-2_16

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  6 in total

1.  Target analysis by integration of transcriptome and ChIP-seq data with BETA.

Authors:  Su Wang; Hanfei Sun; Jian Ma; Chongzhi Zang; Chenfei Wang; Juan Wang; Qianzi Tang; Clifford A Meyer; Yong Zhang; X Shirley Liu
Journal:  Nat Protoc       Date:  2013-11-21       Impact factor: 13.491

2.  HTSstation: a web application and open-access libraries for high-throughput sequencing data analysis.

Authors:  Fabrice P A David; Julien Delafontaine; Solenne Carat; Frederick J Ross; Gregory Lefebvre; Yohan Jarosz; Lucas Sinclair; Daan Noordermeer; Jacques Rougemont; Marion Leleu
Journal:  PLoS One       Date:  2014-01-27       Impact factor: 3.240

3.  Widespread misinterpretable ChIP-seq bias in yeast.

Authors:  Daechan Park; Yaelim Lee; Gurvani Bhupindersingh; Vishwanath R Iyer
Journal:  PLoS One       Date:  2013-12-09       Impact factor: 3.240

4.  Application of experimentally verified transcription factor binding sites models for computational analysis of ChIP-Seq data.

Authors:  Victor G Levitsky; Ivan V Kulakovskiy; Nikita I Ershov; Dmitry Yu Oshchepkov; Vsevolod J Makeev; T C Hodgman; Tatyana I Merkulova
Journal:  BMC Genomics       Date:  2014-01-29       Impact factor: 3.969

5.  Bioinformatics Analysis of Estrogen-Responsive Genes.

Authors:  Adam E Handel
Journal:  Methods Mol Biol       Date:  2016

6.  Modeling Modulation of the Tick Regulome in Response to Anaplasma phagocytophilum for the Identification of New Control Targets.

Authors:  Sara Artigas-Jerónimo; Agustín Estrada-Peña; Alejandro Cabezas-Cruz; Pilar Alberdi; Margarita Villar; José de la Fuente
Journal:  Front Physiol       Date:  2019-04-18       Impact factor: 4.566

  6 in total

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