Maximum likelihood and Bayesian methods for estimating the distribution of selective effects among classes of mutations using DNA polymorphism data - PubMed (original) (raw)
Maximum likelihood and Bayesian methods for estimating the distribution of selective effects among classes of mutations using DNA polymorphism data
Carlos D Bustamante et al. Theor Popul Biol. 2003 Mar.
Abstract
Maximum likelihood and Bayesian approaches are presented for analyzing hierarchical statistical models of natural selection operating on DNA polymorphism within a panmictic population. For analyzing Bayesian models, we present Markov chain Monte-Carlo (MCMC) methods for sampling from the joint posterior distribution of parameters. For frequentist analysis, an Expectation-Maximization (EM) algorithm is presented for finding the maximum likelihood estimate of the genome wide mean and variance in selection intensity among classes of mutations. The framework presented here provides an ideal setting for modeling mutations dispersed through the genome and, in particular, for the analysis of how natural selection operates on different classes of single nucleotide polymorphisms (SNPs).
Similar articles
- Estimating the scaled mutation rate and mutation bias with site frequency data.
Vogl C. Vogl C. Theor Popul Biol. 2014 Dec;98:19-27. doi: 10.1016/j.tpb.2014.10.002. Epub 2014 Oct 18. Theor Popul Biol. 2014. PMID: 25453604 - Comparison of Bayesian and maximum-likelihood inference of population genetic parameters.
Beerli P. Beerli P. Bioinformatics. 2006 Feb 1;22(3):341-5. doi: 10.1093/bioinformatics/bti803. Epub 2005 Nov 29. Bioinformatics. 2006. PMID: 16317072 - Bayesian and maximum likelihood estimation of genetic maps.
York TL, Durrett RT, Tanksley S, Nielsen R. York TL, et al. Genet Res. 2005 Apr;85(2):159-68. doi: 10.1017/S0016672305007494. Genet Res. 2005. PMID: 16174334 - Joint analysis of demography and selection in population genetics: where do we stand and where could we go?
Li J, Li H, Jakobsson M, Li S, Sjödin P, Lascoux M. Li J, et al. Mol Ecol. 2012 Jan;21(1):28-44. doi: 10.1111/j.1365-294X.2011.05308.x. Epub 2011 Oct 14. Mol Ecol. 2012. PMID: 21999307 Review. - Complex system approaches to genetic analysis Bayesian approaches.
Wilson MA, Baurley JW, Thomas DC, Conti DV. Wilson MA, et al. Adv Genet. 2010;72:47-71. doi: 10.1016/B978-0-12-380862-2.00003-5. Adv Genet. 2010. PMID: 21029848 Free PMC article. Review.
Cited by
- Background selection as baseline for nucleotide variation across the Drosophila genome.
Comeron JM. Comeron JM. PLoS Genet. 2014 Jun 26;10(6):e1004434. doi: 10.1371/journal.pgen.1004434. eCollection 2014 Jun. PLoS Genet. 2014. PMID: 24968283 Free PMC article. - Most rare missense alleles are deleterious in humans: implications for complex disease and association studies.
Kryukov GV, Pennacchio LA, Sunyaev SR. Kryukov GV, et al. Am J Hum Genet. 2007 Apr;80(4):727-39. doi: 10.1086/513473. Epub 2007 Mar 8. Am J Hum Genet. 2007. PMID: 17357078 Free PMC article. - Estimating selection on nonsynonymous mutations.
Loewe L, Charlesworth B, Bartolomé C, Nöel V. Loewe L, et al. Genetics. 2006 Feb;172(2):1079-92. doi: 10.1534/genetics.105.047217. Epub 2005 Nov 19. Genetics. 2006. PMID: 16299397 Free PMC article. - Inference of Distribution of Fitness Effects and Proportion of Adaptive Substitutions from Polymorphism Data.
Tataru P, Mollion M, Glémin S, Bataillon T. Tataru P, et al. Genetics. 2017 Nov;207(3):1103-1119. doi: 10.1534/genetics.117.300323. Epub 2017 Sep 25. Genetics. 2017. PMID: 28951530 Free PMC article. - Genome-wide patterns of nucleotide polymorphism in domesticated rice.
Caicedo AL, Williamson SH, Hernandez RD, Boyko A, Fledel-Alon A, York TL, Polato NR, Olsen KM, Nielsen R, McCouch SR, Bustamante CD, Purugganan MD. Caicedo AL, et al. PLoS Genet. 2007 Sep;3(9):1745-56. doi: 10.1371/journal.pgen.0030163. Epub 2007 Aug 6. PLoS Genet. 2007. PMID: 17907810 Free PMC article.