DChIPRep, an R/Bioconductor package for differential enrichment analysis in chromatin studies

被引:2
作者
Chabbert, Christophe D. [1 ,2 ]
Steinmetz, Lars M. [1 ,3 ,4 ]
Klaus, Bernd [1 ]
机构
[1] European Mol Biol Lab, Genome Biol Unit, Heidelberg, Germany
[2] Astra Zeneca, CRUK Cambridge Inst, Oncol iMed, Cambridge, England
[3] Stanford Univ, Stanford Genome Technol Ctr, Palo Alto, CA 94304 USA
[4] Stanford Univ, Dept Genet, Sch Med, Stanford, CA 94305 USA
关键词
Bioinformatics; Computational Biology; Genomics; ChiP-seq; Chromatin; Histone-modifications; Differential enrichment; Statistics; CHIP-SEQ; BINDING; VISUALIZATION;
D O I
10.7717/peerj.1981
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
The genome-wide study of epigenetic states requires the integrative analysis of histone modification ChIP-seq data. Here, we introduce an easy-to-use analytic framework to compare profiles of enrichment in histone modifications around classes of genomic elements, e.g. transcription start sites (TSS). Our framework is available via the user-friendly R/Bioconductor package DChIPRep. DChIPRep uses biological replicate information as well as chromatin Input data to allow fora rigorous assessment of differential enrichment. DChIPRep is available for download through the Bioconductor project at http://bioconductor.org/packages/DChIPRep. Contact. DChIPRep@gmail.com.
引用
收藏
页数:12
相关论文
共 32 条
[1]   GeneTrack - a genomic data processing and visualization framework [J].
Albert, Istvan ;
Wachi, Shinichiro ;
Jiang, Cizhong ;
Pugh, Franklin .
BIOINFORMATICS, 2008, 24 (10) :1305-1306
[2]   HTSeq-a Python']Python framework to work with high-throughput sequencing data [J].
Anders, Simon ;
Pyl, Paul Theodor ;
Huber, Wolfgang .
BIOINFORMATICS, 2015, 31 (02) :166-169
[3]   Practical Guidelines for the Comprehensive Analysis of ChIP-seq Data [J].
Bailey, Timothy ;
Krajewski, Pawel ;
Ladunga, Istvan ;
Lefebvre, Celine ;
Li, Qunhua ;
Liu, Tao ;
Madrigal, Pedro ;
Taslim, Cenny ;
Zhang, Jie .
PLOS COMPUTATIONAL BIOLOGY, 2013, 9 (11)
[4]   NucleoFinder: a statistical approach for the detection of nucleosome positions [J].
Becker, Jeremie ;
Yau, Christopher ;
Hancock, John M. ;
Holmes, Christopher C. .
BIOINFORMATICS, 2013, 29 (06) :711-716
[5]  
Broad-Institute, 2016, PIC TOOLS BY BROAD I
[6]   A high-throughput ChIP-Seq for large-scale chromatin studies [J].
Christophe D Chabbert ;
Sophie H Adjalley ;
Bernd Klaus ;
Emilie S Fritsch ;
Ishaan Gupta ;
Vicent Pelechano ;
Lars M Steinmetz .
Molecular Systems Biology, 11 (1)
[7]  
Dharmalingam G., 2021, soGGi: visualise ChIP-seq, MNase-seq and motif occurrence as aggregate plots Summarised Over Grouped Genomic Intervals
[8]   Identifying ChIP-seq enrichment using MACS [J].
Feng, Jianxing ;
Liu, Tao ;
Qin, Bo ;
Zhang, Yong ;
Liu, Xiaole Shirley .
NATURE PROTOCOLS, 2012, 7 (09) :1728-1740
[9]   nucleR: a package for non-parametric nucleosome positioning [J].
Flores, Oscar ;
Orozco, Modesto .
BIOINFORMATICS, 2011, 27 (15) :2149-2150
[10]   Ground State Conditions Induce Rapid Reorganization of Core Pluripotency Factor Binding before Global Epigenetic Reprogramming [J].
Galonska, Christina ;
Ziller, Michael J. ;
Karnik, Rahul ;
Meissner, Alexander .
CELL STEM CELL, 2015, 17 (04) :462-470