Integrated nested laplace approximation for bayesian nonparametric phylodynamics

Uncertainty in Artificial Intelligence - Proceedings of the 28th Conference, UAI 2012

Volumn , Issue , 2012, Pages 726-735

  Palacios, Julia A ^a   Minin, Vladimir N ^a  

^a UNIVERSITY OF WASHINGTON   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATE BAYESIAN INFERENCE; GAUSSIAN PROCESSES; HUMAN INFLUENZA VIRUS; LAPLACE APPROXIMATION; MARKOV CHAIN MONTE CARLO METHOD; NONPARAMETRIC BAYESIAN METHODS; POPULATION GENETICS; POSTERIOR DISTRIBUTIONS;

ARTIFICIAL INTELLIGENCE; BAYESIAN NETWORKS; HISTORY; INFERENCE ENGINES; LAPLACE TRANSFORMS; VIRUSES;

POPULATION STATISTICS;

EID: 84873440646     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (31)

1. Adams, R. P., Murray, I., and MacKay, D. J. (2009). Tractable nonparametric Bayesian inference in Poisson processes with Gaussian process intensities. Proceedings of the 26th Annual International Conference on Machine Learning, pages 9-16.
2. Bishop, C. (2006). Pattern Recognition and Machine Learning. Springer New York. Campos
3. P. F., Willerslev, E., Sher, A., Orlando, L., Axelsson, E., Tikhonov, A., Aaris-Sørensen, K., Greenwood, A. D., Kahlke, R., Kosintsev, P., Krakhmalnaya, T., Kuznetsova, T., Lemey, P., MacPhee, R., Norris, C. A., Shepherd, K., Suchard, M. A., Zazula, G. D., Shapiro, B., and Gilbert, M. T. P. (2010). Ancient DNA analyses exclude humans as the driving force behind late pleistocene musk ox (Ovibos moschatus) population dynamics. Proceedings of the National Academy of Sciences, 107(12):5675-5680.
4. Cseke, B. and Heskes, T. (2010). Improving posterior marginal approximations in latent Gaussian models. In Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, volume 9, pages 121-128.
5. Drummond, A. and Rambaut, A. (2007). BEAST: Bayesian evolutionary analysis by sampling trees. BMC Evolutionary Biology, 7(1):214.
6. Drummond, A. J., Nicholls, G. K., Rodrigo, A. G., and Solomon, W. (2002). Estimating mutation parameters, population history and genealogy simultaneously from temporally spaced sequence data. Genetics161(3):1307-1320.
7. Drummond, A. J., Rambaut, A., Shapiro, B., and Pybus, O. G. (2005). Bayesian coalescent inference of past population dynamics from molecular sequences. Molecular Biology and Evolution, 22(5):1185-1192.
8. Felsenstein, J. (1992). Estimating effective population size from samples of sequences: inefficiency of pairwise and segregating sites as compared to phylogenetic estimates. Genetical Research, 59(2):139-147.
9. Felsenstein, J. and Rodrigo, A. G. (1999). Coalescent approaches to HIV population genetics. In The Evolution of HIV, pages 233-272.
10. Johns Hopkins University Press. Fraser, C., Donnelly, C. A., Cauchemez, S., Hanage, W. P., Van Kerkhove, M. D., Hollingsworth, T. D., Griffin, J., Baggaley, R. F., Jenkins, H. E., Lyons, E. J., Jombart, T., Hinsley, W. R., Grassly, N. C., Balloux, F., Ghani, A. C., Ferguson, N. M., Rambaut, A., Pybus, O. G., Lopez-Gatell, H., Alpuche-Aranda, C. M., Chapela, I. B., Zavala, E. P., Guevara, D. M. E., Checchi, F., Garcia, E., Hugonnet, S., Roth, C., and Collaboration, T. W. R. P. A. (2009). Pandemic potential of a strain of influenza A (H1N1): Early findings. Science, 324(5934):1557-1561.
11. Fu, Y. (1994). Estimating effective population size or mutation rate using the frequencies of mutations of various classes in a sample of DNA sequences. Genetics, 138(4):1375-1386.
12. Griffiths, R. C. and Tavare, S. (1994). Sampling theory for neutral alleles in a varying environment. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 344(1310):403-410.
13. Hein, J., Schierup, M. H., and Wiuf, C. (2005). Gene Genealogies, Variation and Evolution: A Primer in Coalescent Theory. Oxford University Press, USA, 1st edition.
14. Heled, J. and Drummond, A. (2008). Bayesian inference of population size history from multiple loci. BMC Evolutionary Biology, 8(1):1-289.
15. Ho, S. Y. W. and Shapiro, B. (2011). Skyline-plot methods for estimating demographic history from nucleotide sequences. Molecular Ecology Resources, 11(3):423-434.
16. Illian, J., Sorbye, S. H., and Rue, H. (2012). A toolbox for fitting complex spatial point process models using integrated nested Laplace approximation (INLA). Annals of Applied Statistics, 1(2).
17. Kingman, J. (1982). The coalescent. Stochastic Processes and Their Applications, 13(3):235-248.
18. Kuhner, M., Yamato, J., and Felsenstein, J. (1995). Estimating effective population size and mutation rate from sequence data using Metropolis-Hastings sampling. Genetics, 140(4):1421-1430.
19. Li, H. and Durbin, R. (2011). Inference of human population history from individual whole-genome sequences. Nature, 475(7357):493-496.
20. McVean, G. and Cardin, N. (2005). Approximating the coalescent with recombination. Philos Trans R Soc Lond B Biol Sci, 360(1459):1387-1393.
21. Minin, V. N., Bloomquist, E. W., and Suchard, M. A. (2008). Smooth skyride through a rough skyline: Bayesian coalescent-based inference of population dynamics. Molecular Biology and Evolution, 25(7):1459-1471.
22. Møller, J., Syversveen, A. R., and Waagepetersen, R. P. (1998). Log Gaussian Cox processes. Scandinavian Journal of Statistics, 25(3):451-482.
23. Nordborg, M. (2001). Coalescent theory. In Handbook of Statistical Genetics, chapter Coalescent Theory, pages 179-212.
24. John Wiley &Sons, Chichester, U.K. Opgen-Rhein, R., Fahrmeir, L., and Strimmer, K. (2005). Inference of demographic history from genealogical trees using reversible jump Markov chain Monte Carlo. BMC Evolutionary Biology, 5:1-6.
25. Palacios, J. A. and Minin, V. N. (2011). Gaussian process-based Bayesian nonparametric inference of population trajectories from gene genealogies. ArXiv e-prints, arXiv:1112.4138v1 [stat.ME].
26. Pybus, O. G., Drummond, A. J., Nakano, T., Robertson, B. H., and Rambaut, A. (2003). The epidemiology and iatrogenic transmission of hepatitis C virus in Egypt: A Bayesian coalescent approach. Molecular Biology and Evolution, 20(3):381-387.
27. Pybus, O. G., Rambaut, A., and Harvey, P. H. (2000). An integrated framework for the inference of viral population history from reconstructed genealogies. Genetics, 155(3):1429-1437.
28. Rue, H. and Held, L. (2005). Gaussian Markov Random Fields: Theory and Applications.
29. Chapman and Hall. Rue, H., Martino, S., and Chopin, N. (2009). Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations. Journal of the Royal Statistical Society: Series B, 71(2):319-392.
30. Rue, H., Steinsland, I., and Erland, S. (2004). Approximating hidden Gaussian Markov random fields. Journal of the Royal Statistical Society. Series B, 66(4):pp. 877-892.
31. Slatkin, M. and Hudson, R. R. (1991). Pairwise comparisons of mitochondrial DNA sequences in stable and exponentially growing populations. Genetics, 129(2):555-562.