Modelling genetic variations with fragmentation-coagulation processes

Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011, NIPS 2011

Volumn , Issue , 2011, Pages

  Teh, Yee Whye ^a   Blundell, Charles ^a   Elliott, Lloyd T ^a  

^a UNIVERSITY COLLEGE LONDON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

COAGULATION; POPULATION STATISTICS;

BAYESIAN NONPARAMETRIC MODELING; COAGULATION PROCESS; EQUILIBRIUM DISTRIBUTIONS; FLEXIBLE MODEL; GENETIC VARIATION; HIDDEN-MARKOV MODELS; MODEL FRAGMENTATION; PROCESS-MODELS; SEQUENTIAL DATA; SPLITTING AND MERGING;

HIDDEN MARKOV MODELS;

EID: 85162312555     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (31)

1. The International HapMap Consortium. The international HapMap project. Nature, 426:789-796, 2003.
2. The 1000 Genomes Project Consortium. A map of human genome variation from population-scale sequencing. Nature, 467:1061-1073, 2010.
3. M. J. Daly, J. D. Rioux, S. F. Schaffner, T. J. Hudson, and R. S. Lander. High-resolution haplotype structure in the human genome. Nature Genetics, 29:229-232, 2001.
4. L. Rabiner. A tutorial on hidden Markov models and selected applications in speech recognition. Proceedings of the IEEE, 77:257-285, 1989.
5. P. Scheet and M. Stephens. A fast and flexible statistical model for large-scale population genotype data: Applications to inferring missing genotypes and haplotypic phase. The American Journal of Human Genetics, 78(4):629-644, 2006.
6. A. Jasra, C. C. Holmes, and D. A. Stephens. Markov chain Monte Carlo methods and the label switching problem in Bayesian mixture modeling. Statistical Science, 20(1):50-67, 2005.
7. M. J. Beal, Z. Ghahramani, and C. E. Rasmussen. The infinite hidden Markov model. In Advances in Neural Information Processing Systems, volume 14, 2002.
8. Y. W. Teh, M. I. Jordan, M. J. Beal, and D. M. Blei. Hierarchical Dirichlet processes. Journal of the American Statistical Association, 101(476):1566-1581, 2006.
9. E. P. Xing and K. Sohn. Hidden Markov Dirichlet process: Modeling genetic recombination in open ancestral space. Bayesian Analysis, 2(2), 2007.
10. R. R. Hudson. Properties of a neutral allele model with intragenic recombination. Theoretical Population Biology, 23(2):183-201, 1983.
11. M. Stephens and P. Donnelly. A comparison of Bayesian methods for haplotype reconstruction from population genotype data. American Journal of Human Genetics, 73:1162-1169.
12. N. Li and M. Stephens. Modeling Linkage Disequilibrium and Identifying Recombination Hotspots Using Single-Nucleotide Polymorphism Data. Genetics, 165(4):2213-2233, 2003.
13. J. Marchini, B. Howie, S. Myers, G. McVean, and P. Donnelly. A new multipoint method for genome-wide association studies by imputation of genotypes. Nature Genetics, 39(7):906-913, 2007.
14. B. L. Browning and S. R. Browning. A unified approach to genotype imputation and haplotype-phase inference for large data sets of trios and unrelated individuals. American Journal of Human Genetics, 84:210-223, 2009.
15. D. Aldous. Exchangeability and related topics. In Ećole d'Été de Probabiliteś de Saint-Flour XIII-1983, pages 1-198. Springer, Berlin, 1985.
16. J. Pitman. Combinatorial Stochastic Processes. Lecture Notes in Mathematics. Springer-Verlag, 2006.
17. D. Blackwell and J. B. MacQueen. Ferguson distributions via Pólya urn schemes. Annals of Statistics, 1:353-355, 1973.
18. E. Çinlar. Introduction to Stochastic Processes. Prentice Hall, 1975.
19. R. M. Neal. Slice sampling. Annals of Statistics, 31:705-767, 2003.
20. J. F. C. Kingman. On the genealogy of large populations. Journal of Applied Probability, 19:27-43, 1982. Essays in Statistical Science.
21. J. F. C. Kingman. The coalescent. Stochastic Processes and their Applications, 13:235-248, 1982.
22. G. A. T. McVean and N. J. Cardin. Approximating the coalescent with recombination. Philosophical Transactions of the Royal Society of London B: Biological Sciences, 360(1459):1387-1393, 2005.
23. P. Marjoram and J. Wall. Fast "coalescent" simulation. BMC Genetics, 7(1):16, 2006.
24. J. Bertoin. Random Fragmentation and Coagulation Processes. Cambridge University Press, 2006.
25. J. Pitman and M. Yor. The two-parameter Poisson-Dirichlet distribution derived from a stable subordinator. Annals of Probability, 25:855-900, 1997.
26. J. Pitman. Coalescents with multiple collisions. Annals of Probability, 27:1870-1902, 1999.
27. J. Gasthaus and Y. W. Teh. Improvements to the sequence memoizer. In Advances in Neural Information Processing Systems, 2010.
28. V. Rao and Y. W. Teh. Fast MCMC sampling for Markov jump processes and continuous time Bayesian networks. In Proceedings of the International Conference on Uncertainty in Artificial Intelligence, 2011.
29. NHLBI Program for Genomic Applications. SeattleSNPs. June 2011. http://pga.gs.washington.edu.
30. B. N. Howie, P. Donnelly, and J. Marchini. A flexible and accurate genotype imputation method for the next generation of genome-wide association studies. PLoS Genetics, (6), 2009.
31. J. Berestycki. Exchangeable fragmentation-coalescence processes and their equilibrium measures. http://arxiv.org/abs/math/0403154, 2004.