Literature DB >> 35733020

Bioinformatics Methods for ChIP-seq Histone Analysis.

Nicolas Servant1,2,3,4.   

Abstract

The field of genomics and genome-wide analysis has exploded since around 2008 with the development of high-throughput omics approaches, largely driven by the emergence of the next-generation sequencing technologies. Among the different biological applications supported by recent sequencing technologies, ChIP-seq (Chromatin ImmunoPrecipitation followed by Sequencing) is one of the most powerful techniques which has dramatically changed our view of the epigenetics landscape of cells.In this chapter, I will present and discuss the main steps of bioinformatic and biostatistical analysis of ChIP-seq data (Fig. 1). While this technique has been widely used to study transcription factor binding sites, I will focus here on the analysis of histone modifications.
© 2022. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  Bioinformatics; ChIP-seq; Differential binding; Peak calling; Quality controls

Mesh:

Substances:

Year:  2022        PMID: 35733020     DOI: 10.1007/978-1-0716-2481-4_13

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


  43 in total

1.  Quantitative ChIP-Seq normalization reveals global modulation of the epigenome.

Authors:  David A Orlando; Mei Wei Chen; Victoria E Brown; Snehakumari Solanki; Yoon J Choi; Eric R Olson; Christian C Fritz; James E Bradner; Matthew G Guenther
Journal:  Cell Rep       Date:  2014-10-30       Impact factor: 9.423

2.  Accuracy of Next Generation Sequencing Platforms.

Authors:  Edward J Fox; Kate S Reid-Bayliss; Mary J Emond; Lawrence A Loeb
Journal:  Next Gener Seq Appl       Date:  2014

3.  The Sequence Alignment/Map format and SAMtools.

Authors:  Heng Li; Bob Handsaker; Alec Wysoker; Tim Fennell; Jue Ruan; Nils Homer; Gabor Marth; Goncalo Abecasis; Richard Durbin
Journal:  Bioinformatics       Date:  2009-06-08       Impact factor: 6.937

4.  ChIP-seq guidelines and practices of the ENCODE and modENCODE consortia.

Authors:  Stephen G Landt; Georgi K Marinov; Anshul Kundaje; Pouya Kheradpour; Florencia Pauli; Serafim Batzoglou; Bradley E Bernstein; Peter Bickel; James B Brown; Philip Cayting; Yiwen Chen; Gilberto DeSalvo; Charles Epstein; Katherine I Fisher-Aylor; Ghia Euskirchen; Mark Gerstein; Jason Gertz; Alexander J Hartemink; Michael M Hoffman; Vishwanath R Iyer; Youngsook L Jung; Subhradip Karmakar; Manolis Kellis; Peter V Kharchenko; Qunhua Li; Tao Liu; X Shirley Liu; Lijia Ma; Aleksandar Milosavljevic; Richard M Myers; Peter J Park; Michael J Pazin; Marc D Perry; Debasish Raha; Timothy E Reddy; Joel Rozowsky; Noam Shoresh; Arend Sidow; Matthew Slattery; John A Stamatoyannopoulos; Michael Y Tolstorukov; Kevin P White; Simon Xi; Peggy J Farnham; Jason D Lieb; Barbara J Wold; Michael Snyder
Journal:  Genome Res       Date:  2012-09       Impact factor: 9.043

5.  Predicting the molecular complexity of sequencing libraries.

Authors:  Timothy Daley; Andrew D Smith
Journal:  Nat Methods       Date:  2013-02-24       Impact factor: 28.547

6.  Quantifying ChIP-seq data: a spiking method providing an internal reference for sample-to-sample normalization.

Authors:  Nicolas Bonhoure; Gergana Bounova; David Bernasconi; Viviane Praz; Fabienne Lammers; Donatella Canella; Ian M Willis; Winship Herr; Nouria Hernandez; Mauro Delorenzi
Journal:  Genome Res       Date:  2014-04-07       Impact factor: 9.043

7.  An Alternative Approach to ChIP-Seq Normalization Enables Detection of Genome-Wide Changes in Histone H3 Lysine 27 Trimethylation upon EZH2 Inhibition.

Authors:  Brian Egan; Chih-Chi Yuan; Madeleine Lisa Craske; Paul Labhart; Gulfem D Guler; David Arnott; Tobias M Maile; Jennifer Busby; Chisato Henry; Theresa K Kelly; Charles A Tindell; Suchit Jhunjhunwala; Feng Zhao; Charlie Hatton; Barbara M Bryant; Marie Classon; Patrick Trojer
Journal:  PLoS One       Date:  2016-11-22       Impact factor: 3.240

8.  fastp: an ultra-fast all-in-one FASTQ preprocessor.

Authors:  Shifu Chen; Yanqing Zhou; Yaru Chen; Jia Gu
Journal:  Bioinformatics       Date:  2018-09-01       Impact factor: 6.937

9.  Trimmomatic: a flexible trimmer for Illumina sequence data.

Authors:  Anthony M Bolger; Marc Lohse; Bjoern Usadel
Journal:  Bioinformatics       Date:  2014-04-01       Impact factor: 6.937

10.  Tools and best practices for retrotransposon analysis using high-throughput sequencing data.

Authors:  Aurélie Teissandier; Nicolas Servant; Emmanuel Barillot; Deborah Bourc'his
Journal:  Mob DNA       Date:  2019-12-29
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