Multiple testing of local maxima for detection of peaks in ChIP-Seq data

Annals of Applied Statistics

Volumn 7, Issue 1, 2013, Pages 471-494

  Schwartzman, Armin ^a   Jaffe, Andrew ^a   Gavrilov, Yulia ^a   Meyer, Clifford A ^a  

^a JOHNS HOPKINS BLOOMBERG SCHOOL OF PUBLIC HEALTH   (United States)

Author keywords

False discovery rate; Kernel smoothing; Matched filter; Poisson sequence; Topological inference

Indexed keywords

EID: 84876035152     PISSN: 19326157     EISSN: 19417330     Source Type: Journal    
DOI: 10.1214/12-AOAS594     Document Type: Article

References (26)

1. Arkin, B. L. and Leenis, L. M. (2000). Nonparametric estimation of the cumulative intensity function for a nonhomogeneous Poisson process from overlapping realizations. Management Science 46 989-998.
2. Barski, A. and Zhao, K. (2009). Genomic location analysis by ChIP-Seq. J. Cell. Biochem. 107 11-18.
3. Benjamini, Y. and Hochberg, Y. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. J. Roy. Statist. Soc. Ser. B 57 289-300.
4. Bolstad, W. M. (1995). The multiprocess dynamic Poisson model. J. Amer. Statist. Assoc. 90 227-232.
5. Fejes, A., Robertson, G., Bilenky, M., Varhol, R., Bainbridge, M. and Jones, S. (2008). FindPeaks 3.1: A tool for identifying areas of enrichment from massively parallel short-read sequencing technology. Bioinformatics 24 1720-1730.
6. Harvey, A. C. and Durbin, J. (1986). The effects of seat belt legislation on British road casualties: A case study in structural time series modelling. J. Roy. Statist. Soc. 149 187-227.
7. Helmers, R., Mangku, I. W. and Zitikis, R. (2003). Consistent estimation of the intensity function of a cyclic Poisson process. J. Multivariate Anal. 84 19-39.
8. Hower, V., Evans, S. N. and Pachter, L. (2011). Shape-based identification for ChIP-Seq. BMC Bioinformatics 12 15.
9. Jaffe, A. E., Feinberg, A. P., Irizarry, R. A. and Leek, J. T. (2012). Significance analysis and statistical dissection of variably methylated regions. Biostatistics 13 166-178.
10. Ji, H., Jiang, H., Ma, W., Johnson, D. S., Myers, R. M. and Wong, W. H. (2008). An integrated software system for analyzing ChIP-chip and ChIP-Seq data. Nature Biotechnology 26 1293-1300.
11. Johnson, D. S., Mortazavi, A., Myers, R. M. and Wold, B. (2007). Genome-wide mapping of in vivo protein-DNA interactions. Science 316 1497-1502.
12. Mikkelsen, T. S., Ku, M., Jaffe, D. B., Issac, B., Lieberman, E., Giannoukos, G., Alvarez, P., Brockman, W., Kim, T. K., Koche, R. P., Lee, W., Mendenhall, E., O'Donovan, A., Presser, A., Russ, C., Xie, X., Meissner, A., Wernig, M., Jaenisch, R., Nusbaum, C., Lander, E. S. and Bernstein, B. E. (2007). Genome-wide maps of chromatin state in pluripotent and lineage-committed cells. Nature 448 553-560.
13. North, D. O. (1943). An analysis of the factors which determine signal/noise discrimination in pulsed carrier systems. Technical Report No. PTR-6C, RCA Labs, Princeton, NJ.
14. Park, P. J. (2009). ChIP-seq: Advantages and challenges of a maturing technology. Nat. Rev. Genet. 10 669-680.
15. Pratt, W. K. (1991). Digital Image Processing. Wiley, New York.
16. Sakharkar, M. K., Chow, V. T. K. and Kangueane, P. (2004). Distributions of exons and introns in the human genome. In Silico Biology 4 0032.
17. Schwartzman, A., Gavrilov, Y. and Adler, R. J. (2011). Multiple testing of local maxima for detection of peaks in 1D. Ann. Statist. 39 3290-3319.
18. Simon, M. (1995). Digital Communication Techniques: Signal Design and Detection. Prentice Hall, Englewood Cliffs, NJ.
19. Spyrou, C., Stark R., Lynch, A. G. and Tavar, S. (2009). Bayesian analysis of ChIP-Seq data. BMC Bioinformatics 10 299.
20. Turin, G. L. (1960). An introduction to matched filters. Trans. IRE IT-6 311-329.
21. Valouev, A., Johnson, D. S., Sundquist, A., Medina, C., Anton, E., Batzglou, S., Myers, R. M. and Sidow, A. (2008). Genome-wide analysis of transcription factor binding sites based on ChIP-Seq data. Nature Methods 5 829-834.
22. Wasserman, L. (2006). All of Nonparametric Statistics. Springer, New York.
23. West, M., Harrison, P. J. and Migon, H. S. (1985). Dynamic generalized linear models and Bayesian forecasting. J. Amer. Statist. Assoc. 80 73-97.
24. Zhang, Y., Liu, T., Meyer, C. A., Eeckhoute, J., Johnson, D. S., Bernstein, B. E., Nussbaum, C., Myers, R. M., Brown, M., Li, W. and Liu, X. S. (2008). Model-based analysis of ChIP-Seq (MACS). Genome Biology 9 R137.
25. Zhang, X., Robertson, G., Krzywinski, M., Ning, K., Droit, A., Jones, S. and Gottardo, R. (2011). PICS: Probabilistic inference for ChIP-seq. Biometrics 67 151-163.
26. Zhao, M. and Xie, M. (1996). On maximum likelihood estimation for a general non-homogeneous Poisson process. Scand. J. Stat. 23 597-607