Assessment of substitution model adequacy using frequentist and Bayesian methods

Molecular Biology and Evolution

Volumn 27, Issue 12, 2010, Pages 2790-2803

  Ripplinger, Jennifer ^a   Sullivan, Jack ^a  

^a UNIVERSITY OF IDAHO   (United States)

Author keywords

Bayesian; Goldman Cox; maximum likelihood; model adequacy; parametric bootstrap; posterior predictive simulation

Indexed keywords

ARTICLE; BAYES THEOREM; BOOTSTRAPPING; EMPIRICAL RESEARCH; PARAMETER; PERFORMANCE; PREDICTION; STATISTICAL MODEL;

BAYES THEOREM; COMPUTER SIMULATION; EVOLUTION, MOLECULAR; LIKELIHOOD FUNCTIONS; MODELS, GENETIC; PHYLOGENY; RESEARCH DESIGN;

EID: 78649389370     PISSN: 07374038     EISSN: 15371719     Source Type: Journal    
DOI: 10.1093/molbev/msq168     Document Type: Article

References (59)

1. Abdo Z, Minin VN, Joyce P, Sullivan J. 2004. Accounting for uncertainty in the tree topology has little effect on the decision-theoretic approach to model selection in phylogeny estimation. Mol Biol Evol. 22:691-703.
2. Akaike H. 1973. Information theory and an extension of the maximum likelihood principle. In: Petrov BN, Caski F, editors. Proceedings of the Second International Symposium on Information Theory. Budapest (Hungary): Akademiai Kiado. p. 267-281.
3. Bollback JP. 2002. Bayesian model adequacy and choice in phylogenetics. Mol Biol Evol. 19:1171-1180.
4. Bollback JP. 2005. Posterior mapping and predictive distributions. In: Nielsen R, editor. Statistical methods in molecular evolution. New York: Springer. p. 1-25.
5. Brandli L, Lawson Handley LJ, Vogel P, Perrin N. 2005. Evolutionary history of the greater white-toothed shrew (Crocidura russula) inferred from analysis of mtDNA, Y and X chromosome markers. Mol Phylogenet Evol. 37:832-844.
6. Brown JM, Lemmon AR. 2007. The importance of data partitioning and the utility of Bayes factors in Bayesin phylogenetics. Syst Biol. 56:643-655.
7. Buckley TR, Simon C, Chambers GK. 2001. Exploring among-site rate variation models in a maximum-likelihood framework using empirical data: Effects of model assumptions on estimates of topology, branch lengths, and bootstrap support. Syst Biol. 50:67-86.
8. Carstens BC, Degenhardt JD, Stevenson AS, Sullivan J. 2005. Accounting for coalescent stochasticity in testing phylogeo-graphic hypotheses: testing models of Pleistocene population structure in the Idaho giant salamander Dicamptodon aterrimus. Mol Ecol. 14:255-265.
9. Castoe TA, Doan TM, Parkinson CL. 2004. Data partitions and complex models in Bayesian analysis: the phylogeny of Gymnophthalmid lizards. Syst Biol. 53:448-469.
10. Demboski J, Sullivan J. 2003. Extensive mtDNA variation within the yellow-pine chipmunk, Tamias amoenus (Rodentia: Sciuridae), and phylogeographic inferences for northwest North America. Mol Phylogenet Evol. 26:389-408.
11. Felsenstein J. 1978. Cases in which parsimony or compatibility methods will be positively misleading. Syst Zool. 27:401-410.
12. Felsenstein J. 1981. Evolutionary trees from DNA sequences: a maximum-likelihood approach. J Mol Evol. 17:368-376.
13. Fiala KL, Sokal RR. 1985. Factors determining the accuracy of cladogram estimation: evaluation using computer simulation. Evolution 39:609-622.
14. Foster PG. 2004. Modeling compositional heterogeneity. Syst Biol. 53:485-495.
15. Frati F, Simon C, Sullivan J, Swofford DL. 1997. Evolution of the mitochondrial cytochrome oxidase II gene in Collembola. J Mol Evol. 44:145-158.
16. Gatesy J. 2007. A tenth crucial question regarding model use in phylogenetics. Trends Ecol Evol. 22:509-510.
17. Gaut BS, Lewis PO. 1995. Success of maximum likelihood phylogeny inference in the four-taxon case. Mol Biol Evol. 12:152-162.
18. Gelman A, Meng X-L, Stern H. 1996. Posterior predictive assessment of model fitness via realized discrepancies. Stat Sin. 6:733-807.
19. Goldman N. 1993. Statistical tests of models of DNA substitution. J Mol Evol. 36:182-198.
20. Goldman N, Yang Z. 1994. A codon-based model of nucleotide substitution for protein-coding DNA sequences. Mol Biol Evol. 11:725-736.
21. Hasegawa M, Kishino K, Yano T. 1985. Dating the human-ape splitby a molecular clock of mitochondrial DNA. J Mol Evol.22:160-174.
22. Huelsenbeck JP. 2002. Testing a covariotide model of DNAsubstitution. Mol Biol Evol. 19:698-707.
23. Huelsenbeck JP, Rannala B, Masly JP. 2000. Accommodatingphylogenetic uncertainty in evolutionary studies. Science288:2349-2350.
24. Huelsenbeck JP, Ronquist F, Nielson R, Bollback JP. 2001. Bayesianinference of phylogeny and its impact on evolutionary biology.Science 294:2310-2314.
25. Jukes TH, Cantor CR. 1969. Evolution of protein molecules. In:Munro HN, editor. Mammalian protein metabolism. New York:Academic Press. p. 21-132.
26. Kelchner SA, Thomas MA. 2007. Model use in phylogenetics: ninekey questions. Trends Ecol Evol. 22:87-94.
27. Kimura M. 1980. A simple method of estimating evolutionary rate ofbase substitutions through comparative studies of nucleotidesequences. J Mol Evol. 16:111-120.
28. Kimura M. 1981. Estimation of evolutionary distances betweenhomologous nucleotide sequences. Proc Nattl Acad Sci USA.78:454-458.
29. Lemmon AR, Moriarty EC. 2004. The importance of proper modelassumptions in Bayesian phylogenetics. Syst Biol. 53:265-277.
30. Lockhart PJ, Steel MA, Hendy MD, Penny D. 1994. Recoveringevolutionary trees under a more realistic model of sequenceevolution. Mol Biol Evol. 11:605-612.
31. Minin V, Abdo Z, Joyce P, Sullivan J. 2003. Performance-basedselection of likelihood models for phylogeny estimation. SystBiol. 52:1-10.
32. Mirabolfathy M, Cooke DEL, Duncan JM, Williams NA, Ershad D,Rahimian H, Alizadeh A. 2001. Phytophthora pistaciae sp. nov.and Phytophthora melonis (Katsura): the principal causes of pistachio gummosis in Iran. Mycol Res. 105:1166-1175.
33. Nylander JAA. 2004. MrModeltest v2. Program distributed by theauthor. Uppsala (Sweden): Evolutionary Biology Centre, UppsalaUniversity.
34. Posada D, Buckley TR. 2004. Model selection and model averaging inphylogenetics: advantages of Akaike information criterion andBayesian approaches over likelihood ratio tests. Syst Biol.53:793-808.
35. Posada D, Crandall KA. 1998. Modeltest: testing the model of DNAsubstitution. Bioinformatics 14:817-818.
36. Rambaut A, Grassly NC. 1997. Seq-Gen: an application for theMonte Carlo simulation of DNA sequence evolution alongphylogenetic trees. Comput Appl Biosci. 13:235-238.
37. Reeves JH. 1992. Heterogeneity in the substitution process of aminoacid sites of proteins coded for by mitochondrial DNA. J MolEvol. 35:17-31.
38. Ren F, Tanaka H, Yang Z. 2005. An empirical examination of theutility of codon-substitution models in phylogeny reconstruction. Syst Biol. 54:808-818.
39. Revell LJ, Harmon LJ, Glor RE. 2005. Underparametrized model ofsequence evolution leads to bias in the estimation of diversification rates from molecular phylogenies. Syst Biol. 54:973-983.
40. Ripplinger J, Sullivan J. 2008. Does choice in model selection affectmaximum likelihood analysis Syst Biol. 57:76-85.
41. Robinson DF, Foulds LR. 1981. Comparison of phylogenetic trees.Math Biosci. 53:131-147.
42. Ronquist F, Huelsenbeck JP. 2003. MrBayes 3: Bayesian phyloge-netic inference under mixed models. Bioinformatics 19:1572-1574.
43. Rubin DB. 1984. Bayesianly justifiable and relevant frequencycalculations for the applied statistician. Ann Stat. 12:1151-1172.
44. Sanderson MJ, Kim J. 2000. Parametric phylogenetics Syst Biol.49:817-829.
45. Schoniger M, von Haeseler A. 1994. A stochastic model for theevolution of autocorrelated DNA sequences. Mol PhylogenetEvol. 3:240-247.
46. Schwarz G. 1978. Estimating the dimensions of a model. Ann Stat.6:461-464.
47. Sullivan J, Abdo Z, Joyce P, Swofford DL. 2005. Evaluating theperformance of a successive-approximations approach toparameter optimization in maximum-likelihood phylogenyestimation. Mol Biol Evol. 22:1386-2392.
48. Sullivan J, Joyce P. 2005. Model selection in phylogenetics. Ann RevEcol Evol Syst. 36:445-466.
49. Sullivan J, Markert JA, Kilpatrick CW. 1997. Phylogeography andmolecular systematics of the Peromyscus aztecus species group(Rodentia: Muridae) inferred using parsimony and likelihood.Syst Biol. 46:426-440.
50. Sullivan J, Swofford DL. 1997. Are guinea pigs rodents Theimportance of adequate models in molecular phylogenetics.J Mammal Evol. 4:77-86.
51. Sullivan J, Swofford DL. 2001. Should we use model-based methodsfor phylogenetic inference when we know that assumptionsabout among-site rate variation and nucleotide substitutionpattern are violated? Syst Biol. 50:723-729.
52. Swofford DL. 2002. PAUP*: phylogenetic analysis using parsimony(*and other methods). Version 4.0b10. Sunderland (MA):Sinauer Associates.
53. Swofford DL, Waddell PJ, Huelsenbeck JP, Foster PG, Lewis PO,Rogers JS. 2001. Bias in phylogenetic estimation and its relevanceto the choice between parsimony and likelihood methods. SystBiol. 50:525-539.
54. Tamura K, Nei M. 1993. Estimation of the number of nucleotidesubstitutions in the control region of mitochondrial DNA inhumans and chimpanzees. Mol Biol Evol. 10:512-526.
55. Tavaré S. 1986. Some probabilistic and statistical problems in theanalysis of DNA sequences. In: Miura RM, editor. Somemathematical questions in biology: DNA sequence analysis.Lectures on Mathematics in the Life Sciences. Vol. 17. New YorkAmerican Mathematical Society. p. 57-86.
56. Tuffley C, Steel M. 1998. Modeling the covarion hypothesis ofnucleotide substitution. Math Biosci. 147:63-91.
57. Waddell PJ, Ota R, Penny D. 2009. Measuring fit of sequence data tophylogenetic model: gain of power using marginal tests. J MolEvol. 69:289-299.
58. Whelan S, Lio P, Goldman N. 2001. Molecular phylogenetics: state-of-the-art methods for looking into the past. Trends Genet.17:262-272.
59. Yang Z, Nielsen R, Goldman N, Pedersen AMK. 2000. Codon-substitution models for heterogeneous selection pressure atamino acid sites. Genetics 155:431-449.