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Peak calling

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Computional method used in analyzing DNA

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. When the protein is a transcription factor, the enriched area is its transcription factor binding site (TFBS). Popular software programs include MACS. Wilbanks and colleagues is a survey of the ChIP-seq peak callers, and Bailey et al. 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 or m6Aseq for detection of post-transcriptional RNA modification sites with software programs, such as exomePeak. 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. However new generation of peak callers such as DFilter 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.

In the context of ChIP-exo, this process is known as 'peak-pair calling'.

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 and MAnorm 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, ODIN. and THOR. Differential peak calling can also be applied in the context of analyzing RNA-binding protein binding sites.

See also

References

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  2. Feng, Jianxing; Liu, Tao; Qin, Bo; Zhang, Yong; Liu, Xiaole Shirley (29 August 2012). "Identifying ChIP-seq enrichment using MACS". Nature Protocols. 7 (9): 1728–1740. doi:10.1038/nprot.2012.101. PMC 3868217. PMID 22936215.
  3. Wilbanks, Elizabeth G.; Facciotti, Marc T. (7 July 2010). "Evaluation of Algorithm Performance in ChIP-Seq Peak Detection". PLOS ONE. 5 (7): e11471. Bibcode:2010PLoSO...511471W. doi:10.1371/journal.pone.0011471. PMC 2900203. PMID 20628599.
  4. Bailey, TL; Krajewski P; Ladunga I; Lefebvre C; Li Q; Liu T; Madrigal P; Taslim C; Zhang J. (14 November 2013). "Practical guidelines for the comprehensive analysis of ChIP-seq data". PLOS Comput Biol. 9 (11): e1003326. Bibcode:2013PLSCB...9E3326B. doi:10.1371/journal.pcbi.1003326. PMC 3828144. PMID 24244136.
  5. Meyer, Kate D.; Saletore, Yogesh; Zumbo, Paul; Elemento, Olivier; Mason, Christopher E.; Jaffrey, Samie R. (31 May 2012). "Comprehensive Analysis of mRNA Methylation Reveals Enrichment in 3′ UTRs and near Stop Codons". Cell. 149 (7): 1635–1646. doi:10.1016/j.cell.2012.05.003. PMC 3383396. PMID 22608085.
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  7. Meng, J.; Cui, X.; Rao, M. K.; Chen, Y.; Huang, Y. (14 April 2013). "Exome-based analysis for RNA epigenome sequencing data". Bioinformatics. 29 (12): 1565–1567. doi:10.1093/bioinformatics/btt171. PMC 3673212. PMID 23589649.
  8. Koohy, Hashem; Down, Thomas A.; Spivakov, Mikhail; Hubbard, Tim; Helmer-Citterich, Manuela (8 May 2014). "A Comparison of Peak Callers Used for DNase-Seq Data". PLOS ONE. 9 (5): e96303. Bibcode:2014PLoSO...996303K. doi:10.1371/journal.pone.0096303. PMC 4014496. PMID 24810143.
  9. Kumar, Vibhor; Masafumi Muratani; Nirmala Arul Rayan; Petra Kraus; Thomas Lufkin; Huck Hui Ng; Shyam Prabhakar (Jul 2013). "Uniform, optimal signal processing of mapped deep-sequencing data". Nature Biotechnology. 31 (7): 615–622. doi:10.1038/nbt.2596. PMID 23770639.
  10. Wong, Ka-Chun; et al. (2014). "SignalSpider: probabilistic pattern discovery on multiple normalized ChIP-Seq signal profiles". Bioinformatics. 31 (1): 17–24. doi:10.1093/bioinformatics/btu604. PMID 25192742.
  11. Madrigal, Pedro (2015). "Identification of Transcription Factor Binding Sites in ChIP-exo using R/Bioconductor". Epigenesys Bioinformatics Protocols. 68.
  12. Keles, Liang (26 October 2011). "Detecting differential binding of transcription factors with ChIP-seq". Bioinformatics. 28 (1): 121–122. doi:10.1093/bioinformatics/btr605. PMC 3244766. PMID 22057161.
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