“Peak calling”的意思、由来-开放百科全书

Peak calling is a computational method used to identify areas in a genome that have been enriched with aligned reads as a consequence of performing a ChIP-sequencing or MeDIP-seq experiment. These areas are those where a protein interacts with DNA.^[1] When the protein is a transcription factor, the enriched area is its transcription factor binding site (TFBS). Popular software programs include MACS.^[2] Wilbanks and colleagues^[3] is a survey of the ChIP-seq peak callers, and Bailey et al.^[4] is a description of practical guidelines for peak calling in ChIP-seq data.

Peak calling may be conducted on transcriptome/exome as well to RNA epigenome sequencing data from MeRIPseq^[5] or m6Aseq^[6] for detection of post-transcriptional RNA modification sites with software programs, such as exomePeak.^[7]

Many of the peak calling tools are optimised for only some kind of assays such as only for transcription-factor ChIP-seq or only for DNase-seq.^[8] However new generation of peak callers such as DFilter^[9] are based on generalised optimal theory of detection and has been shown to work for nearly all kinds for tag profile signals from next-gen sequencing data. It is also possible to do more complex analysis using such tools like combining multiple ChIP-seq signal to detect regulatory sites. ^[10]

Differential peak calling is about identifying significant differences in two ChIP-seq signals. One can distinguish between one-stage and two-stage differential peak callers. One stage differential peak callers work in two phases: first, call peaks on individual ChIP-seq signals and second, combine individual signals and apply statistical tests to estimate differential peaks. DBChIP^[12] and MAnorm^[13] are examples for one stage differential peak callers.

Two stage differential peak callers segment two ChIP-seq signals and identify differential peaks in one step. They take advantage of signal segmentation approaches such as Hidden Markov Models. Examples for two-stage differential peak callers are ChIPDiff,^[14] ODIN.^[15] and THOR.

Differential peak calling can also be applied in the context of analyzing RNA-binding protein binding sites.^[16]

See also

References

1. ^{{cite journal |vauthors=Valouev A, etal |title=Genome-wide analysis of transcription factor binding sites based on ChIP-seq data |journal=Nature Methods |volume=5 |issue=9 |pages=829–834 |date=September 2008 |pmc=2917543 |url=http://www.nature.com/nmeth/journal/v6/n11s/full/nmeth.1371.html |pmid=19160518 |doi=10.1038/nmeth.1246}}
2. ^{{cite journal|last=Feng|first=Jianxing|author2=Liu, Tao |author3=Qin, Bo |author4=Zhang, Yong |author5=Liu, Xiaole Shirley |title=Identifying ChIP-seq enrichment using MACS|journal=Nature Protocols|date=29 August 2012|volume=7|issue=9|pages=1728–1740|doi=10.1038/nprot.2012.101|pmid=22936215|pmc=3868217}}
3. ^{{cite journal|last=Wilbanks|first=Elizabeth G.|author2=Facciotti, Marc T. |title=Evaluation of Algorithm Performance in ChIP-Seq Peak Detection|journal=PLoS ONE|date=7 July 2010|volume=5|issue=7|pages=e11471|doi=10.1371/journal.pone.0011471|pmid=20628599|pmc=2900203}}
4. ^{{cite journal|last=Bailey|first=TL|author2=Krajewski P |author3=Ladunga I |author4=Lefebvre C |author5=Li Q |author6=Liu T |author7=Madrigal P |author8=Taslim C |author9=Zhang J. |title=Practical guidelines for the comprehensive analysis of ChIP-seq data|journal=PLoS Comput Biol|date=14 November 2013|volume=9|issue=11|pages=:e1003326|doi=10.1371/journal.pcbi.1003326|pmid=24244136|pmc=3828144}}
5. ^{{cite journal|last=Meyer|first=Kate D.|author2=Saletore, Yogesh |author3=Zumbo, Paul |author4=Elemento, Olivier |author5=Mason, Christopher E. |author6=Jaffrey, Samie R. |title=Comprehensive Analysis of mRNA Methylation Reveals Enrichment in 3′ UTRs and near Stop Codons|journal=Cell|date=31 May 2012|volume=149|issue=7|pages=1635–1646|doi=10.1016/j.cell.2012.05.003|pmid=22608085|pmc=3383396}}
6. ^{{cite journal |last1=Dominissini |first1=Dan |last2=Moshitch-Moshkovitz |first2=Sharon |last3=Schwartz |first3=Schraga |last4=Salmon-Divon |first4=Mali |last5=Ungar |first5=Lior |last6=Osenberg |first6=Sivan |last7=Cesarkas |first7=Karen |last8=Jacob-Hirsch |first8=Jasmine |last9=Amariglio |first9=Ninette |last10=Kupiec |first10=Martin |last11=Sorek |first11=Rotem |last12=Rechavi |first12=Gideon |title=Topology of the human and mouse m6A RNA methylomes revealed by m6A-seq |journal=Nature |date=28 April 2012 |volume=485 |issue=7397 |pages=201–206 |doi=10.1038/nature11112|pmid=22575960}}
7. ^{{cite journal|last=Meng|first=J.|author2=Cui, X. |author3=Rao, M. K. |author4=Chen, Y. |author5=Huang, Y. |title=Exome-based analysis for RNA epigenome sequencing data|journal=Bioinformatics|date=14 April 2013|volume=29|issue=12|pages=1565–1567|doi=10.1093/bioinformatics/btt171 |pmid=23589649 |pmc=3673212}}
8. ^{{cite journal |last1=Koohy |first1=Hashem |author2=Down, Thomas A. |author3=Spivakov, Mikhail |author4=Hubbard, Tim |author5=Helmer-Citterich, Manuela |title=A Comparison of Peak Callers Used for DNase-Seq Data |journal=PLoS ONE |date=8 May 2014 |volume=9 |issue=5 |pages=e96303 |doi=10.1371/journal.pone.0096303 |pmid=24810143 |pmc=4014496}}
9. ^{{cite journal |last1=Kumar |first1=Vibhor |author2=Masafumi Muratani |author3=Nirmala Arul Rayan |author4=Petra Kraus |author5=Thomas Lufkin |author6=Huck Hui Ng |author7=Shyam Prabhakar |journal=Nature Biotechnology |volume=31 |pages=615–622 |pmid=23770639 |doi=10.1038/nbt.2596 |issue=7 |title=Uniform, optimal signal processing of mapped deep-sequencing data |date=Jul 2013}}
10. ^{{cite journal |last1=Wong |first1=Ka-Chun |display-authors=etal|title=SignalSpider: probabilistic pattern discovery on multiple normalized ChIP-Seq signal profiles |journal=Bioinformatics |date=2014 |volume=31 |issue=1 |pages=17–24 |doi=10.1093/bioinformatics/btu604 |pmid=25192742}}
11. ^{{cite journal |last=Madrigal |first=Pedro |title=Identification of Transcription Factor Binding Sites in ChIP-exo using R/Bioconductor |journal=Epigenesys Bioinformatics Protocols |date=2015 |volume=68 |url=http://www.epigenesys.eu/en/protocols/bio-informatics/1325-identification-of-transcription-factor-binding-sites-in-chip-exo-using-r-bioconductor-prot-68}}
12. ^{{cite journal|last=Keles|first=Liang|title=Detecting differential binding of transcription factors with ChIP-seq|journal=Bioinformatics|date=26 October 2011|doi=10.1093/bioinformatics/btr605|pmid=22057161|volume=28|issue=1|pages=121–122|pmc=3244766}}
13. ^{{cite journal|last=Waxman|first=Shao|author2=Zhang |author3=Yuan |author4=Orkin |title=MAnorm: a robust model for quantitative comparison of ChIP-Seq data sets|journal=Genome Biology|date=16 March 2012|volume=13|issue=3|doi=10.1186/gb-2012-13-3-r16 |pages=R16 |pmid=22424423 |pmc=3439967}}
14. ^{{cite journal|last=Xu|first=Sung|author2=Wei |author3=Lin |title=An HMM approach to genome-wide identification of differential histone modification sites from ChIP-seq data|journal=Bioinformatics|date=28 July 2008|volume=24|issue=20|doi=10.1093/bioinformatics/btn402|pages=2344–2349|pmid=18667444}}
15. ^{{cite journal|last=Allhoff|first=Costa|author2=Sere|author3=Chauvistre|author4=Lin|author5=Zenke|title=Detecting differential peaks in ChIP-seq signals with ODIN|journal=Bioinformatics|date=24 October 2014|volume=30|issue=24|pages=3467–3475|doi=10.1093/bioinformatics/btu722|pmid=25371479}}
16. ^{{cite journal |vauthors=Holmqvist E, Wright PR, Li L, Bischler T, Barquist L, Reinhardt R, Backofen R, Vogel J |title=Global RNA recognition patterns of post-transcriptional regulators Hfq and CsrA revealed by UV crosslinking in vivo. |journal=EMBO J |year=2016 |pmid=27044921 |doi=10.15252/embj.201593360 |volume=35 |issue=9 |pages=991–1011|pmc=5207318 }}