Composite likelihood modeling of neighboring site correlations of DNA sequence substitution rates

Statistical Applications in Genetics and Molecular Biology

Volumn 8, Issue 1, 2009, Pages

  Deng, Ling ^a   Moore, Dirk F ^b  

^a Johnson and Johnson ^*  (United States)

^b UNIVERSITY OF MEDICINE AND DENTISTRY OF NEW JERSEY   (United States)

Author keywords

Bivariate negative binomial distribution; Composite likelihood; Parametric bootstrap; Phylogeny; Substitution rate

Indexed keywords

MITOCHONDRIAL DNA;

ANIMAL; ARTICLE; BIOLOGICAL MODEL; CODON; COMPUTER SIMULATION; GENETICS; MUTATION; NUCLEOTIDE SEQUENCE; PHYLOGENY; PRIMATE; STATISTICAL MODEL;

ANIMALS; BASE SEQUENCE; CODON; COMPUTER SIMULATION; DNA, MITOCHONDRIAL; LIKELIHOOD FUNCTIONS; MODELS, GENETIC; MUTATION; PHYLOGENY; PRIMATES;

EID: 62449329412     PISSN: None     EISSN: 15446115     Source Type: Journal    
DOI: 10.2202/1544-6115.1391     Document Type: Article

References (28)

1. Cox, D.R.and Reid, N. (2004) A note on pseudolikelihood constructed from marginal densities. Biometrika, 91, 729-737
2. Efron, B., Halloran, E. and Holmes, S. (1996) Bootstrap confidence levels for phylogenetic trees, correction. Proc. Natl. Acad. Sci. USA 93, 13429-13434
3. Excoffier, L. and Yang, Z (1999). Substitution rate variation among sites in mitochondrial hypervariable region I of humans and chimpanzees. Molec. Biol. Evol.16, 1357-1368.
4. Fearnhead, P. (2003). Consistency of estimators of the population-scaled recombination rate. Theoret. Pop. Biol. 64, 67-79.
5. Fearnhead, P. and Donnelly, P. (2002) Approximate likelihood methods for estimating local recombination rates (with discussion). J. Roy. Statist. Soc. Ser. B 64, 657-680.
6. Felsenstein, J. (1981) Evolutionary trees from DNA sequences: A maximum likelihood approach. J. Mol. Evol. 17, 368-376.
7. Felsenstein, J. (1985) Confidence limits on phylogenies: An approach using the bootstrap. Evolution 39, 783-791.
8. Felsenstein, J. (2005) PHYLIP (Phylogeny Inference Package) version 3.6. Distributed by the author. Department of Genome Sciences, University of Washington, Seattle. http://evolution.genetics.washington.edu/phylip.html
9. Felsenstein, J. and Churchill, G.A. (1996). A hidden Markov model approach to variation among sites in rate of evolution. Mol. Biol. Evol. 13(1):93-104.
10. Goldman, N. (1993) Statistical tests of models of DNA substitution. J. Mol. Evol. 36, 182-198.
11. Gu, X. and Zhang, J. (1997). A simple method for estimating the parameter of substitution rate variations among sites. Molec. Biol. Evol., 14(11), 1106-1113.
12. Hasegawa, M., H. Kishino, and T. Yano. (1985) Dating of human-ape splitting by a molecular clock of mitochondrial DNA. J. Mol. Evol, 22, 160-174.
13. Henderson, R. and Shimakura, S. (2003). A serially correlated gamma frailty model for longitudinal count data. Biometrika, 90 (2), 355-366.
14. Jensen, J.L. and Pedersen, A-M.K. (2000). Probabilistic models of DNA sequence evolution with context dependent rates of substitution. Adv. Appl. Prob. 32, 499-517.
15. Lake, J.A. (1998) Optimally recovering rate variation information from genomes and sequences: Pattern filtering. Mol. Biol. Evol. 15, 1224-1231.
16. Lindsay, B.G. (1988). Composite likelihood methods. In Statistical Inference from Stochastic Processes, Ed. N. U. Prabhu, pp. 221-39. Providence: American Mathematical Society.
17. Morozov, P., Sitnikova, T., Churchill, G., Ayala, F.J., and Rzhetsky, A. (2000). A new method for characterizing replacement rate variation in molecular sequences: Application of the Fourier and wavelet models to drosophial and mammalian proteins. Genetics 154, 381-395.
18. Nei, M. and Kumar, S (2000). Molecular Evolution and Phylogenetics, Oxford University Press.
19. Pedersen, A-M.K. and Jensen, J.L. (2001) A dependent-rates model and an MCMC-based methodology for the maximum-likelihood analysis of sequences with overlapping reading frames. Mol. Biol. Evol. 18(5), 763-776.
20. Rambaut, A. and Grassly, N. C. (1997) Seq-Gen: An application for the Monte Carlo simulation of DNA sequence evolution along phylogenetic trees. Comput. Appl. Biosci. 13: 235-238. http://tree.bio.ed.ac.uk/software/ seqgen/
21. Tamura K, Dudley J, Nei M & Kumar S (2007) MEGA4: Molecular Evolutionary Genetics Analysis (MEGA) software version 4.0. Molec. Biol. and Evol. 24:1596-1599. http://www.megasoftware.net
22. Thorne, J.L., Kishino, H. and Felsenstein, J. (1992) Inching toward reality: An improved likelihood model of sequence evolution. J. Molec. Evol. 34, 3-16.
23. Varin, C. and Vidoni, P. (2005). A note on composite likelihood inference and model selection. Biometrika 92, 519-528
24. Wang, Q., Salter, L.A. and K. Pearl, D.K. (2002) Estimation of evolutionary parameters with phylogenetic trees. J. Molec. Evol. 55, 684-695
25. Yang, Z. (1993) Maximum likelihood estimation of phylogeny from DNA sequences when substitution rates differ over sites. Mol. Biol. Evol. 10, 1396-1401.
26. Yang, Z. (1994) Maximum likelihood phylogenetic estimation from DNA sequences with variable rates over sites: approximate methods. J. Mol. Evol. 39, 306-314.
27. Yang, Z. (1995) A space-time process model for the evolution of DNA sequences. Genetics, 139: 993-1005.
28. Yang, Z. (2008) PAML: Phylogenetic analysis by maximum likelihood version 4.1. Distributed by the author (http://abacus.gene.ucl.ac.uk/software/ paml.html)