Saturation analysis of ChIP-seq data for reproducible identification of binding peaks

Genome Research

Volumn 25, Issue 9, 2015, Pages 1391-1400

  Hansen, Peter ^a   Hecht, Jochen ^a,b   Ibrahim, Daniel M ^a,b   Krannich, Alexander ^a   Truss, Matthias ^a   Robinson, Peter N ^a,b,c  

^a CHARITÉ UNIVERSITÄTSMEDIZIN BERLIN   (Germany)

^b MAX PLANCK INSTITUTE FOR MOLECULAR GENETICS   (Germany)

^c FREIE UNIVERSITÄT BERLIN   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

DNA BINDING PROTEIN; TRANSCRIPTION FACTOR; PROTEIN BINDING;

ALGORITHM; ARTICLE; BINDING SITE; CHROMATIN IMMUNOPRECIPITATION; CONTROLLED STUDY; DNA BINDING; NEXT GENERATION SEQUENCING; PRIORITY JOURNAL; PROTEIN BINDING; PROTEIN DNA INTERACTION; REPRODUCIBILITY; TRANSCRIPTION INITIATION SITE; GENETICS; GENOMICS; HIGH THROUGHPUT SEQUENCING; HUMAN; METABOLISM; NUCLEOTIDE MOTIF; PROCEDURES;

ALGORITHMS; BINDING SITES; CHROMATIN IMMUNOPRECIPITATION; DNA-BINDING PROTEINS; GENOMICS; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING; HUMANS; NUCLEOTIDE MOTIFS; PROTEIN BINDING; REPRODUCIBILITY OF RESULTS; TRANSCRIPTION FACTORS; TRANSCRIPTION INITIATION SITE;

EID: 84940982012     PISSN: 10889051     EISSN: 15495469     Source Type: Journal    
DOI: 10.1101/gr.189894.115     Document Type: Article

References (32)

1. Arya G, Maitra A, Grigoryev SA. 2010. A structural perspective on the where, how, why, and what of nucleosome positioning. J Biomol Struct Dyn 27: 803-820.
2. Bailey TL. 2011. DREME: motif discovery in transcription factor ChIP-seq data. Bioinformatics 27: 1653-1659.
3. Bardet AF, Steinmann J, Bafna S, Knoblich JA, Zeitlinger J, Stark A. 2013. Identification of transcription factor binding sites from ChIP-seq data at high resolution. Bioinformatics 29: 2705-2713.
4. Benjamini Y, Hochberg Y. 1995. Controlling the false discovery rate: A practical and powerful approach to multiple testing. J R Stat Soc Series B (Methodol) 57: 289-300.
5. Cairns BR. 2009. The logic of chromatin architecture and remodelling at promoters. Nature 461: 193-198.
6. Doring A, Weese D, Rausch T, Reinert K. 2008. SeqAn: An efficient, generic C++ library for sequence analysis. BMC Bioinformatics 9: 11.
7. The ENCODE Consortium. 2012. An integrated encyclopedia of DNA elements in the human genome. Nature 489: 57-74.
8. Feller W. 1968. An introduction to probability theory and its applications, Vol. I, 3rd ed. John Wiley & Sons, Inc., New York.
9. Feng J, Liu T, Qin B, Zhang Y, Liu XS. 2012. Identifying ChIP-seq enrichment using MACS. Nat Protoc 7: 1728-1740.
10. Grant CE, Bailey TL, Noble WS. 2011. FIMO: scanning for occurrences of a given motif. Bioinformatics 27: 1017-1018.
11. Ibrahim DM, Hansen P, Rodelsperger C, Stiege AC, Doelken SC, Horn D, Jager M, Janetzki C, Krawitz P, Leschik G, et al. 2013. Distinct global shifts in genomic binding profiles of limb malformation-associated HOXD13 mutations. Genome Res 23: 2091-2102.
12. Kharchenko PV, Tolstorukov MY, Park PJ. 2008. Design and analysis of ChIP-seq experiments for DNA-binding proteins. Nat Biotechnol 26: 1351-1359.
13. Kim H, Kim J, Selby H, Gao D, Tong T, Phang TL, Tan AC. 2011. A short survey of computational analysis methods in analysing ChIP-seq data. Hum Genomics 5: 117-123.
14. Laajala TD, Raghav S, Tuomela S, Lahesmaa R, Aittokallio T, Elo LL. 2009. A practical comparison of methods for detecting transcription factor binding sites in ChIP-seq experiments. BMC Genomics 10: 618.
15. Landt SG, Marinov GK, Kundaje A, Kheradpour P, Pauli F, Batzoglou S, Bernstein BE, Bickel P, Brown JB, Cayting P, et al. 2012. ChIP-seq guidelines and practices of the ENCODE and modENCODE consortia. Genome Res 22: 1813-1831.
16. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R. 2009. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25: 2078-2079.
17. Li Q, Brown J, Huang H, Bickel P. 2011. Measuring reproducibility of highthroughput experiments. Ann Appl Stat 5: 1752-1779.
18. Machanick P, Bailey TL. 2011. MEME-ChIP: motif analysis of large DNA datasets. Bioinformatics 27: 1696-1697.
19. Newkirk D, Biesinger J, Chon A, Yokomori K, Xie X. 2011. AREM: Aligning short reads from ChIP-sequencing by expectation maximization. J Comput Biol 18: 1495-1505.
20. Park PJ. 2009. ChIP-seq: Advantages and challenges of a maturing technology. Nat Rev Genet 10: 669-680.
21. Peng W, Zhao K. 2011. An integrated strategy for identification of both sharp and broad peaks from next-generation sequencing data. Genome Biol 12: 120.
22. Pepke S, Wold B, Mortazavi A. 2009. Computation for ChIP-seq and RNAseq studies. Nat Methods 6(11 Suppl): S22-S32.
23. Quinlan AR, Hall IM. 2010. BEDTools: A flexible suite of utilities for comparing genomic features. Bioinformatics 26: 841-842.
24. Robertson G, Hirst M, Bainbridge M, Bilenky M, Zhao Y, Zeng T, Euskirchen G, Bernier B, Varhol R, Delaney A, et al. 2007. Genome-wide profiles of STAT1 DNA association using chromatin immunoprecipitation and massively parallel sequencing. Nat Methods 4: 651-657.
25. Rosenbloom KR, Sloan CA, Malladi VS, Dreszer TR, Learned K, Kirkup VM, Wong MC, Maddren M, Fang R, Heitner SG, et al. 2013. ENCODE data in the UCSC Genome Browser: year 5 update. Nucleic Acids Res 41 (Database issue): D56-D63.
26. Rozowsky J, Euskirchen G, Auerbach RK, Zhang ZD, Gibson T, Bjornson R, Carriero N, Snyder M, Gerstein MB. 2009. PeakSeq enables systematic scoring of ChIP-seq experiments relative to controls. Nat Biotechnol 27: 66-75.
27. Rye MB, Saetrom P, Drablos F. 2011. A manually curated ChIP-seq benchmark demonstrates room for improvement in current peak-finder programs. Nucleic Acids Res 39: E25.
28. Stadelmayer B, Micas G, Gamot A, Martin P, Malirat N, Koval S, Raffel R, Sobhian B, Severac D, Rialle S, et al. 2014. Integrator complex regulates NELF-mediated RNA polymerase II pause/release and processivity at coding genes. Nat Commun 5: 5531.
29. Szalkowski AM, Schmid CD. 2011. Rapid innovation in ChIP-seq peak-calling algorithms is outdistancing benchmarking efforts. Brief Bioinform 12: 626-633.
30. Wilbanks EG, Facciotti MT. 2010. Evaluation of algorithm performance in ChIP-seq peak detection. PLoS One 5: E11471.
31. Xing H, Mo Y, LiaoW, Zhang MQ. 2012. Genome-wide localization of protein-DNA binding and histone modification by a Bayesian change-point method with ChIP-seq data. PLoS Comput Biol 8: E1002613.
32. Zhang Y, Liu T, Meyer CA, Eeckhoute J, Johnson DS, Bernstein BE, Nusbaum C, Myers RM, Brown M, Li W, et al. 2008. Model-based analysis of ChIPSeq (MACS). Genome Biol 9: R137.