Estimation of selection intensity under overdominance by bayesian methods

Statistical Applications in Genetics and Molecular Biology

Volumn 8, Issue 1, 2009, Pages

  Buzbas, Erkan Ozge ^a   Joyce, Paul ^a   Abdo, Zaid ^a  

^a UNIVERSITY OF IDAHO   (United States)

Author keywords

Balancing selection k< em> allele models; Bayesian inference; Heterozygote advantage; Overdominance

Indexed keywords

LEUKOCYTE ANTIGEN; HLA ANTIGEN;

ALLELE; ARTICLE; ASSAY; BAYES THEOREM; DOMINANT GENE; DOMINANT INHERITANCE; GENE FREQUENCY; GENE LOCUS; HUMAN; BIOLOGICAL MODEL; COMPUTER SIMULATION; GENETIC SELECTION; GENETICS; POPULATION GENETICS;

BAYES THEOREM; COMPUTER SIMULATION; GENE FREQUENCY; GENETICS, POPULATION; HLA ANTIGENS; HUMANS; MODELS, GENETIC; SELECTION (GENETICS);

EID: 68249109701     PISSN: None     EISSN: 15446115     Source Type: Journal    
DOI: 10.2202/1544-6115.1466     Document Type: Article

References (27)

1. Black, F.L., Hedrick, P.W. (1997). Strong balancing selection at hla loci: Evidence from segregation in south amerindian families. Proc. Natl. Acad. Sci. USA 94(23), 12452-12456.
2. Bustamante, C.D., Nielsen, R., Hartl, D.L. (2002). Maximum likelihood and bayesian methods for estimating the distribution of selective effects among classes of mutations using dna polymorphism data. Theor. Popul. Biol. 63, 91-103.
3. Buzbas, E.O., Joyce, P. (2009). Maximum likelihood estimates under k-allele models with selection can be numerically unstable. Ann. Appl. Stat. (In press).
4. Dagpunar, J.S., (1978). Sampling of variates from a truncated gamma distribution. Journal of Statistical Computation and Simulation 8, 59-64.
5. Damien, P., Wakefield, J., Walker, S.G. (1999). Gibbs sampling for Bayesian non-conjugate and hierarchical models by using auxiliary variables. J. R. Statist. Soc. (Series B). 159, 853-867.
6. Damien, P., Walker, S.G. (2001). Gibbs sampling for Bayesian non-conjugate and hierarchical models by using auxiliary variables. Journal of Computational and Graphical Statistics Vol.10, No.2, 206-215.
7. Donnelly, P., Kurtz, T. (1999). A countable representation of the Fleming-Viot measure-valued diffusion. Ann. Prob. 24, 743-760.
8. Donnelly, P., Nordborg, M., Joyce, P. (2001). Likelihood and simulation methods for a class of nonneutral population genetics models. Genetics 159, 853-867.
9. Ethier, S.N., Griffiths, R.C. (1987). The infinitely-many-sites model as a measure-valued diffusion. Ann. Prob. 15, 515-545.
10. Ethier, S.N. and Kurtz, T.G. (1993). Fleming-viot processes in population genetics. SIAM Journal of Control and Optimization 31, 345-386.
11. Ewens, W. (2004). Mathematical Population Genetics: I, Second ed. Interdisciplinary Applied Mathematics, Vol. 27. Springer-Verlag, New York. Theoretical Introduction.
12. Fearnhead, P. (2006). The stationary distribution of allele frequencies when selection acts at unlinked loci. Theor. Popul. Biol. 70, 376-386.
13. Gelman, A., Carlin, J.B., Stern, H.S., Rubin, D. (2004). Bayesian Data Analysis. Second Ed. Chapman and Hall, Boca Raton, FL.
14. Genz, A., Joyce, P. (2003). Computation of the normalization constant for exponentially weighted Dirichlet Distribution. Computing Science and Statistics, 35, 557-563.
15. Geweke, J. (1991). Efficient Simulation from the Multivariate Normal and Student-t Distributions Subject to Linear Constraints. In E.M. Keramidas (Ed.), Computing Science and Statistics: Proceedings of the Twenty-Third Symposium on the Interface, pp. 571-578, Fairfax: Interface Foundation of North America, Inc.
16. Hastings, W. (1970). Monte carlo sampling methods using markov chains and their application. Biometrika 57, 97-109.
17. Hudson R. (1991). Gene genealogies and the coalescent process. In Futuyma D. and Antanovics J. (Eds.) Oxford Evolutionary Surveys Vol.7, pp.1-44. Oxford University Press.
18. Joyce, P., Genz, A., Buzbas, E.O. Efficient simulation methods for a class of non-neutral population genetics models. Theor. Popul. Biol. (Under Review).
19. Maruyama, T. and Nei, M. (1981). Genetic variability maintained by mutation and over-dominant selection in finite populations. Genetics 98, 441-459.
20. Metropolis, N., Rosenbluth, A.E., Rosenbluth, M.N., Teller, A.H., Teller, E. (1953). Equation of state calculations by fast computing machines. J. Chem. Phys. 21, 1087-1092.
21. Meyer, D., Single, R. M., Mack, S. J., Lancaster, A. K., Nelson, M. P., Erlich, H. A., Fernandez-Vina, M, Thomson, G. (2007). Single locus polymorphism of classical HLA genes. In Hansen, J.A., (Ed.), Immunobiology of the Human MHC: Proceedings of the 13th International Histocompatibility Workshop and Conference, Vol. I, pp. 653-704, Seattle, WA: IHWG Press.
22. Muirhead, C., Slatkin, M. (2000). A Method for Estimating the Intensity of Over-dominant Selection From the Distribution of Allele Frequencies. Genetics 156, 2119-2126.
23. Philippe, A. (1997). Simulation of right and left truncated gamma distributions by mixtures. Statistics and Computing 7, 173-181.
24. Robinson, J., Waller, M.J., Parham, P, de Groot, N., Bontrop, R., Kennedy, L.J., Stoehr, P., Marsh, S.G.E. (2003). Imgt/hla and imgt/mhc: sequence databases for the study of the major histocompatibility complex. Nucleic Acids Research 31, 311-314.
25. Watterson, G.A. (1977) Heterosis or neutrality? Genetics 85, 789-814.
26. Watterson, G.A. (1978). The homozygosity test of neutrality. Genetics 88, 405-417.
27. Wright, S. (1949). Adaptation and selection. In Jepson, G.L., Simpson, G.G., Mayr, E., (Ed.), Genetics, Paleontology, and Evolution, p.383. Princeton Univ. Press, Princeton, NJ.