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Bioinformatics pp 331–364Cite as

Phylogenetic Model Evaluation

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Part of the book series: Methods in Molecular Biology™ ((MIMB,volume 452))

Abstract

Most phylogenetic methods are model-based and depend on Markov models designed to approximate the evolutionary rates between nucleotides or amino acids. When Markov models are selected for analysis of alignments of these characters, it is assumed that they are close approximations of the evolutionary processes that gave rise to the data. A variety of methods have been developed for estimating the fit of Markov models, and some of these methods are now frequently used for the selection of Markov models. In a growing number of cases, however, it appears that the investigators have used the model-selection methods without acknowledging their inherent shortcomings. This chapter reviews the issue of model selection and model evaluation.

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References

  1. Zakharov, E. V., Caterino, M. S., Sperling, F. A. H. (2004) Molecular phylogeny, historical biogeography, and divergence time estimates for swallowtail butterflies of the genus Papilio (Lepidoptera: Papilionidae). Syst Biol 53, 193–215.

    PubMed  Google Scholar 

  2. Brochier, C., Forterre, P., Gribaldo, S. (2005) An emerging phylogenetic core of Archaea: phylogenies of transcription and translation machineries converge following addition of new genome sequences. BMC Evol Biol 5, 36.

    PubMed  Google Scholar 

  3. Hardy, M. P., Owczarek, C. M., Jermiin, L. S., et al. (2004) Characterization of the type I interferon locus and identification of novel genes. Genomics 84, 331–345.

    PubMed  CAS  Google Scholar 

  4. de Queiroz, K., Gauthier, J. (1994) Toward a phylogenetic system of biological nomenclature. Trends Ecol Evol 9, 27–31.

    PubMed  Google Scholar 

  5. Board, P. G., Coggan, M., Chelnavayagam, G., et al. (2000) Identification, characterization and crystal structure of the Omega class of glutathione transferases. J Biol Chem 275, 24798–24806.

    PubMed  CAS  Google Scholar 

  6. Pagel, M. (1999) Inferring the historical patterns of biological evolution. Nature 401, 877–884.

    PubMed  CAS  Google Scholar 

  7. Charleston, M. A., Robertson, D. L. (2002) Preferential host switching by primate lentiviruses can account for phylogenetic similarity with the primate phylogeny. Syst Biol 51, 528–535.

    PubMed  CAS  Google Scholar 

  8. Jermann, T. M., Opitz, J. G., Stackhouse, J., et al. (1995) Reconstructing the evolutionary history of the artiodactyl ribonuclease superfamily. Nature 374, 57–59.

    PubMed  CAS  Google Scholar 

  9. Posada, D., Crandall, K. A. (1998) MOD-ELTEST: testing the model of DNA substitution. Bioinformatics 14, 817–818.

    PubMed  CAS  Google Scholar 

  10. Abascal, F., Zardoya, R., Posada, D. (2005) ProtTest: selection of best-fit models of protein evolution. Bioinformatics 21, 2104–2105.

    PubMed  CAS  Google Scholar 

  11. Weisburg, W. G., Giovannoni, S. J., Woese, C. R. (1989) The Deinococcus and Thermus phylum and the effect of ribosomal RNA composition on phylogenetic tree construction. Syst Appl Microbiol 11, 128–134.

    PubMed  CAS  Google Scholar 

  12. Loomis, W. F., Smith, D. W. (1990) Molecular phylogeny of Dictyostelium discoideum by protein sequence comparison. Proc Natl Acad Sci USA 87, 9093–9097.

    PubMed  CAS  Google Scholar 

  13. Penny, D., Hendy, M. D., Zimmer, E. A., et al. (1990) Trees from sequences: panacea or Pandora's box? Aust Syst Biol 3, 21–38.

    Google Scholar 

  14. Lockhart, P. J., Howe, C. J., Bryant, D. A., et al. (1992) Substitutional bias confounds inference of cyanelle origins from sequence data. J Mol Evol 34, 153–162.

    PubMed  CAS  Google Scholar 

  15. Lockhart, P. J., Penny, D., Hendy, M. D., et al. (1992) Controversy on chloroplast origins. FEBS Lett 301, 127–131.

    PubMed  CAS  Google Scholar 

  16. Hasegawa, M., Hashimoto, T. (1993) Ribosomal RNA trees misleading? Nature 361, 23.

    PubMed  CAS  Google Scholar 

  17. Olsen, G. J., Woese, C. R. (1993) Ribos-omal RNA: a key to phylogeny. FASEB J 7, 113–123.

    PubMed  CAS  Google Scholar 

  18. Sogin, M. L., Hinkle, G., Leipe, D. D. (1993) Universal tree of life. Nature 362, 795.

    PubMed  CAS  Google Scholar 

  19. Klenk, H. P., Palm, P., Zillig, W. (1994) DNA-dependent RNA polymerases as phylogenetic marker molecules. Syst Appl Microbiol 16, 638–647.

    CAS  Google Scholar 

  20. Foster, P. G., Jermiin, L. S., Hickey, D. A. (1997) Nucleotide composition bias affects amino acid content in proteins coded by animal mitochondria. J Mol Evol 44, 282–288.

    PubMed  CAS  Google Scholar 

  21. van den Bussche, R. A., Baker, R. J., Huelsenbeck, J. P., et al. (1998) Base compositional bias and phylogenetic analyses: a test of the “flying DNA” hypothesis. Mol Phylogenet Evol 10, 408–416.

    Google Scholar 

  22. Foster, P. G., Hickey, D. A. (1999) Compositional bias may affect both DNA-based and protein-based phylogenetic reconstructions. J Mol Evol 48, 284–290.

    PubMed  CAS  Google Scholar 

  23. Chang, B. S. W., Campbell, D. L. (2000) Bias in phylogenetic reconstruction of vertebrate rhodopsin sequences. Mol Biol Evol 17, 1220–1231.

    PubMed  CAS  Google Scholar 

  24. Conant, G. C., Lewis, P. O. (2001) Effects of nucleotide composition bias on the success of the parsimony criterion on phylogenetic inference. Mol Biol Evol 18, 1024–1033.

    PubMed  CAS  Google Scholar 

  25. Tarrío, R., Rodriguez-Trelles, F., Ayala, F. J. (2001) Shared nucleotide composition biases among species and their impact on phylogenetic reconstructions of the Drosophilidae. Mol Biol Evol 18, 1464–1473.

    PubMed  Google Scholar 

  26. Goremykin, V. V., Hellwig, F. H. (2005) Evidence for the most basal split in land plants dividing bryophyte and tracheophyte lineages. Plant Syst Evol 254, 93–103.

    Google Scholar 

  27. Barry, D., Hartigan, J. A. (1987) Statistical analysis of hominoid molecular evolution. Stat Sci 2, 191–210.

    Google Scholar 

  28. Reeves, J. (1992) Heterogeneity in the substitution process of amino acid sites of proteins coded for by the mitochondrial DNA. J Mol Evol 35, 17–31.

    PubMed  CAS  Google Scholar 

  29. Steel, M. A., Lockhart, P. J., Penny, D. (1993) Confidence in evolutionary trees from biological sequence data. Nature 364, 440–442.

    PubMed  CAS  Google Scholar 

  30. Lake, J. A. (1994) Reconstructing evolutionary trees from DNA and protein sequences: paralinear distances. Proc Natl Acad Sci USA 91, 1455–1459.

    PubMed  CAS  Google Scholar 

  31. Lockhart, P. J., Steel, M. A., Hendy, M. D., et al. (1994) Recovering evolutionary trees under a more realistic model of sequence evolution. Mol Biol Evol 11, 605–612.

    PubMed  CAS  Google Scholar 

  32. Steel, M. A. (1994) Recovering a tree from the leaf colourations it generates under a Markov model. Appl Math Lett 7, 19–23.

    Google Scholar 

  33. Galtier, N., Gouy, M. (1995) Inferring phylogenies from DNA sequences of unequal base compositions. Proc Natl Acad Sci USA 92, 11317–11321.

    PubMed  CAS  Google Scholar 

  34. Steel, M. A., Lockhart, P. J., Penny, D. (1995) A frequency-dependent significance test for parsimony. Mol Phylogenet Evol 4, 64–71.

    PubMed  CAS  Google Scholar 

  35. Yang, Z., Roberts, D. (1995) On the use of nucleic acid sequences to infer early branches in the tree of life. Mol Biol Evol 12, 451–458.

    PubMed  CAS  Google Scholar 

  36. Gu, X., Li, W.-H. (1996) Bias-corrected paralinear and logdet distances and tests of molecular clocks and phylogenies under nonstationary nucleotide frequencies. Mol Biol Evol 13, 1375–1383.

    PubMed  CAS  Google Scholar 

  37. Gu, X., Li, W.-H. (1998) Estimation of evolutionary distances under stationary and non-stationary models of nucleotide substitution. Proc Natl Acad Sci USA 95, 5899–5905.

    PubMed  CAS  Google Scholar 

  38. Galtier, N., Gouy, M. (1998) Inferring pattern and process: maximum-likelihood implementation of a nonhomogenous model of DNA sequence evolution for phylogenetic analysis. Mol Biol Evol 15, 871–879.

    PubMed  CAS  Google Scholar 

  39. Galtier, N., Tourasse, N., Gouy, M. (1999) A nonhyperthermophilic common ancestor to extant life forms. Science 283, 220–221.

    PubMed  CAS  Google Scholar 

  40. Tamura, K., Kumar, S. (2002) Evolutionary distance estimation under heterogeneous substitution pattern among lineages. Mol Biol Evol 19, 1727–1736.

    PubMed  CAS  Google Scholar 

  41. Foster, P. G. (2004) Modeling compositional heterogeneity. Syst Biol 53, 485–495.

    PubMed  Google Scholar 

  42. Thollesson, M. (2004) LDDist: a Perl module for calculating LogDet pair-wise distances for protein and nucleotide sequences. Bioinformatics 20, 416–418.

    PubMed  CAS  Google Scholar 

  43. Jayaswal, V., Jermiin, L. S., Robinson, J. (2005) Estimation of phylogeny using a general Markov model. Evol Bioinf Online 1, 62–80.

    Google Scholar 

  44. Jayaswal, V., Robinson, J., Jermiin, L. S. (2007) Estimation of phylogeny and invariant sites under the General Markov model of nucleotide sequence evolution. Syst Biol, 56, 155–162.

    CAS  Google Scholar 

  45. Sullivan, J., Arellano, E. A., Rogers, D. S. (2000) Comparative phylogeography of Mesoamerican highland rodents: concerted versus independent responses to past climatic fluctuations. Am Nat 155, 755–768.

    PubMed  Google Scholar 

  46. Demboski, J. R., Sullivan, J. (2003) Extensive mtDNA variation within the yellow-pine chipmunk, Tamias amoenus (Rodentia: Sciuridae), and phylogeographic inferences for northwestern North America. Mol Phylogenet Evol 26, 389–408.

    PubMed  CAS  Google Scholar 

  47. Carstens, B. C., Stevenson, A. L., Degen-hardt, J. D., et al. (2004) Testing nested phylogenetic and phylogeographic hypotheses in the Plethodon vandykei species group. Syst Biol 53, 781–792.

    PubMed  Google Scholar 

  48. Tavaré, S. (1986) Some probabilistic and statistical problems on the analysis of DNA sequences. Lect Math Life Sci 17, 57–86.

    Google Scholar 

  49. Ababneh, F., Jermiin, L. S., Robinson, J. (2006) Generation of the exact distribution and simulation of matched nucleotide sequences on a phylogenetic tree. J Math Model Algor 5, 291–308.

    Google Scholar 

  50. Bryant, D., Galtier, N., Poursat, M.-A. (2005) Likelihood calculation in molecular phylogenetics, in (Gascuel, O., ed.), Mathematics in Evolution and Phylogeny. Oxford University Press, Oxford, UK, pp. 33–62.

    Google Scholar 

  51. Penny, D., Hendy, M. D., Steel, M. A. (1992) Progress with methods for constructing evolutionary trees. Trends Ecol Evol 7, 73–79.

    PubMed  CAS  Google Scholar 

  52. Drouin, G., Prat, F., Ell, M., et al. (1999) Detecting and characterizing gene conversion between multigene family members. Mol Biol Evol 16, 1369–1390.

    PubMed  CAS  Google Scholar 

  53. Posada, D., Crandall, K. A. (2001) Evaluation of methods for detecting recombination from DNA sequences: computer simulations. Proc Natl Acad Sci USA 98, 13757–13762.

    PubMed  CAS  Google Scholar 

  54. Posada, D. (2002) Evaluation of methods for detecting recombination from DNA sequences: empirical data. Mol Biol Evol 19, 708–717.

    PubMed  CAS  Google Scholar 

  55. Martin, D. P., Williamson, C., Posada, D. (2005) RDP2: Recombination detection and analysis from sequence alignments. Bioinformatics 21, 260–262.

    PubMed  CAS  Google Scholar 

  56. Bruen, T. C., Philippe, H., Bryant, D. (2006) A simple and robust statistical test for detecting the presence of recombination. Genetics 172, 2665–2681.

    PubMed  CAS  Google Scholar 

  57. Ragan, M. A. (2001) On surrogate methods for detecting lateral gene transfer. FEMS Microbiol Lett 201, 187–191.

    PubMed  CAS  Google Scholar 

  58. Dufraigne, C., Fertil, B., Lespinats, S., et al. (2005) Detection and characterization of horizontal transfers in prokaryotes using genomic signature. Nucl Acid Res 33, e6.

    Google Scholar 

  59. Azad, R. K., Lawrence, J. G. (2005) Use of artificial genomes in assessing methods for atypical gene detection. PLoS Comp Biol 1, 461–473.

    CAS  Google Scholar 

  60. Tsirigos, A., Rigoutsos, I. (2005) A new computational method for the detection of horizontal gene transfer events. Nucl Acid Res 33, 922–933.

    CAS  Google Scholar 

  61. Ragan, M. A., Harlow, T. J., Beiko, R. G. (2006) Do different surrogate methods detect lateral genetic transfer events of different relative ages? Trends Microbiol 14, 4–8.

    PubMed  CAS  Google Scholar 

  62. Beiko, R. G., Hamilton, N. (2006) Phyloge-netic identification of lateral genetic transfer events. BMC Evol Biol 6, 15.

    PubMed  Google Scholar 

  63. Fitch, W. M. (1986) An estimation of the number of invariable sites is necessary for the accurate estimation of the number of nucleotide substitutions since a common ancestor. Prog Clin Biol Res 218, 149–159.

    PubMed  CAS  Google Scholar 

  64. Lockhart, P. J., Larkum, A. W. D., Steel, M. A., et al. (1996) Evolution of chlorophyll and bacteriochlorophyll: the problem of invariant sites in sequence analysis. Proc Natl Acad Sci USA 93, 1930–1934.

    PubMed  CAS  Google Scholar 

  65. Yang, Z. (1996) Among-site rate variation and its impact on phylogenetic analysis. Trends Ecol Evol 11, 367–372.

    PubMed  CAS  Google Scholar 

  66. Waddell, P. J., Steel, M. A. (1997) General time reversible distances with unequal rates across sites: mixing Г and inverse Gaussian distributions with invariant sites. Mol Phylogenet Evol 8, 398–414.

    PubMed  CAS  Google Scholar 

  67. Gowri-Shankar, V., Rattray, M. (2006) Compositional heterogeneity across sites: Effects on phylogenetic inference and modeling the correlations between base frequencies and substitution rate. Mol Biol Evol 23, 352–364.

    PubMed  CAS  Google Scholar 

  68. Schöniger, M., von Haeseler, A. (1994) A stochastic model for the evolution of auto-correlated DNA sequences. Mol Phylogenet Evol 3, 240–247.

    PubMed  Google Scholar 

  69. Tillier, E. R. M. (1994) Maximum likelihood with multiparameter models of substitution. J Mol Evol 39, 409–417.

    CAS  Google Scholar 

  70. Hein, J., Støvlbœk, J. (1995) A maximum-likelihood approach to analyzing nonover-lapping and overlapping reading frames. J Mol Evol 40, 181–190.

    PubMed  CAS  Google Scholar 

  71. Muse, S. V. (1995) Evolutionary analyses of DNA sequences subject to constraints on secondary structure. Genetics 139, 1429–1439.

    PubMed  CAS  Google Scholar 

  72. Rzhetsky, A. (1995) Estimating substitution rates in ribosomal RNA genes. Genetics 141, 771–783.

    PubMed  CAS  Google Scholar 

  73. Tillier, E. R. M., Collins, R. A. (1995) Neighbor joining and maximum likelihood with RNA sequences: addressing the interdependence of sites. Mol Biol Evol 12, 7–15.

    CAS  Google Scholar 

  74. Pedersen, A.-M. K., Wiuf, C., Christiansen, F. B. (1998) A codon-based model designed to describe lentiviral evolution. Mol Biol Evol 15, 1069–1081.

    PubMed  CAS  Google Scholar 

  75. Tillier, E. R. M., Collins, R. A. (1998) High apparent rate of simultaneous compensatory base-pair substitutions in ribosomal RNA. Genetics 148, 1993–2002.

    PubMed  CAS  Google Scholar 

  76. Higgs, P. G. (2000) RNA secondary structure: physical and computational aspects. Q Rev Biophys 30, 199–253.

    Google Scholar 

  77. Pedersen, A.-M. K., Jensen, J. L. (2001) A dependent-rates model and an MCMC-based methodology for the maximum-likelihood analysis of sequences with overlapping frames. Mol Biol Evol 18, 763–776.

    PubMed  CAS  Google Scholar 

  78. Savill, N. J., Hoyle, D. C., Higgs, P. G. (2001) RNA sequence evolution with secondary structure constraints: comparison of substitution rate models using maximum-likelihood methods. Genetics 157, 339–411.

    Google Scholar 

  79. Jow, H., Hudelot, C., Rattray, M., et al. (2002) Bayesian phylogenerics using an RNA substitution model applied to early mammalian evolution. Mol Biol Evol 19, 1591–1601.

    PubMed  CAS  Google Scholar 

  80. Lockhart, P. J., Steel, M. A., Barbrook, A. C., et al. (1998) A covariotide model explains apparent phylogenetic structure of oxygenic photosynthetic lineages. Mol Biol Evol 15, 1183–1188.

    PubMed  CAS  Google Scholar 

  81. Jukes, T. H., Cantor, C. R. (1969) Evolution of protein molecules, in (Munro, H. N., ed.), Mammalian Protein Metabolism. Academic Press, New York.

    Google Scholar 

  82. Lanave, C., Preparata, G., Saccone, C., et al. (1984) A new method for calculating evolutionary substitution rates. J Mol Evol 20, 86–93.

    PubMed  CAS  Google Scholar 

  83. Naylor, G. P. J., Brown, W. M. (1998) Amphioxus mitochondrial DNA, chordate phylogeny, and the limits of inference based on comparisons of sequences. Syst Biol 47, 61–76.

    PubMed  CAS  Google Scholar 

  84. Ho, S. Y. W., Jermiin, L. S. (2004) Tracing the decay of the historical signal in biological sequence data. Syst Biol 53, 623–637.

    PubMed  Google Scholar 

  85. Jermiin, L. S., Ho, S. Y. W., Ababneh, F., et al. (2004) The biasing effect of compositional heterogeneity on phylogenetic estimates may be underestimated. Syst Biol 53, 638–643.

    PubMed  Google Scholar 

  86. Ababneh, F., Jermiin, L. S., Ma, C., et al. (2006) Matched-pairs tests of homogeneity with applications to homologous nucleotide sequences. Bioinformatics 22, 1225–1231.

    PubMed  CAS  Google Scholar 

  87. Ho, J. W. K., Adams, C. E., Lew, J. B., et al. (2006) SeqVis: Visualization of compositional heterogeneity in large alignments of nucleotides. Bioinformatics 22, 2162–2163.

    PubMed  CAS  Google Scholar 

  88. Lanave, C., Pesole, G. (1993) Stationary MARKOV processes in the evolution of biological macromolecules. Binary 5, 191–195.

    Google Scholar 

  89. Rzhetsky, A., Nei, M. (1995) Tests of applicability of several substitution models for DNA sequence data. Mol Biol Evol 12, 131–151.

    PubMed  CAS  Google Scholar 

  90. Waddell, P. J., Cao, Y., Hauf, J., et al. (1999) Using novel phylogenetic methods to evaluate mammalian mtDNA, including amino acid-invariant sites-LogDet plus site stripping, to detect internal conflicts in the data, with special reference to the positions of hedgehog, armadillo, and elephant. Syst Biol 48, 31–53.

    PubMed  CAS  Google Scholar 

  91. Bowker, A. H. (1948) A test for symmetry in contingency tables. J Am Stat Assoc 43, 572–574.

    PubMed  CAS  Google Scholar 

  92. Stuart, A. (1955) A test for homogeneity of the marginal distributions in a two-way classification. Biometrika 42, 412–416.

    Google Scholar 

  93. Jermiin, L. S., Ho, S. Y. W., Ababneh, F., et al. (2003) Hetero: a program to simulate the evolution of DNA on a four-taxon tree. Appl Bioinf 2, 159–163.

    CAS  Google Scholar 

  94. Muse, S. V., Weir, B. S. (1992) Testing for equality of evolutionary rates. Genetics 132, 269–276.

    PubMed  CAS  Google Scholar 

  95. Cannings, C., Edwards, A. W. F. (1968) Natural selection and the de Finetti diagram. Ann Hum Genet 31, 421–428.

    PubMed  CAS  Google Scholar 

  96. Huelsenbeck, J. P., Rannala, B. (1997) Phylogenetic methods come of age: Testing hypotheses in an evolutionary context. Science 276, 227–232.

    PubMed  CAS  Google Scholar 

  97. Whelan, S., Goldman, N. (1999) Distributions of statistics used for the comparison of models of sequence evolution in phylogenetics. Mol Biol Evol 16, 11292–11299.

    Google Scholar 

  98. Goldman, N., Whelan, S. (2000) Statistical tests of gamma-distributed rate heterogeneity in models of sequence evolution in phylogenetics. Mol Biol Evol 17, 975–978.

    PubMed  CAS  Google Scholar 

  99. Goldman, N. (1993) Statistical tests of models of DNA substitution. J Mol Evol 36, 182–198.

    PubMed  CAS  Google Scholar 

  100. Telford, M. J., Wise, M. J., Gowri-Shankar, V. (2005) Consideration of RNA secondary structure significantly improves likelihood-based estimates of phylogeny: examples from the bilateria. Mol Biol Evol 22, 1129–1136.

    PubMed  CAS  Google Scholar 

  101. Goldman, N., Yang, Z. (1994) A codon-based model of nucleotide substitution for protein-coding DNA sequences. Mol Biol Evol 11, 725–736.

    PubMed  CAS  Google Scholar 

  102. Muse, S. V., Gaut, B. S. (1994) A likelihood approach for comparing synonymous and nonsynonymous nucleotide substitution rates, with application to the chloroplast genome. Mol Biol Evol 11, 715–724.

    PubMed  CAS  Google Scholar 

  103. Dayhoff, M. O., Schwartz, R. M., Orcutt, B. C. (eds.) (1978) A Model of Evolutionary Change in Proteins. National Biomedical Research Foundation, National Biomedical Research Foundation, Washington, DC.

    Google Scholar 

  104. Jones, D. T., Taylor, W. R., Thornton, J. M. (1992) The rapid generation of mutation data matrices from protein sequences. Comp Appl Biosci 8, 275–282.

    PubMed  CAS  Google Scholar 

  105. Henikoff, S., Henikoff, J. G. (1992) Amino acid substitution matrices from protein blocks. Proc Natl Acad Sci USA 89, 10915–10919.

    PubMed  CAS  Google Scholar 

  106. Adachi, J., Hasegawa, M. (1996) Model of amino acid substitution in proteins encoded by mitochondrial DNA. J Mol Evol 42, 459–468.

    PubMed  CAS  Google Scholar 

  107. Cao, Y., Janke, A., Waddell, P. J., et al. (1998) Conflict among individual mitochondrial proteins in resolving the phylogeny of eutherian orders. J Mol Evol 47, 307–322.

    PubMed  CAS  Google Scholar 

  108. Yang, Z., Nielsen, R., Hasegawa, M. (1998) Models of amino acid substitution and applications to mitochondrial protein evolution. Mol Biol Evol 15, 1600–1611.

    PubMed  CAS  Google Scholar 

  109. Müller, T., Vingron, M. (2000) Modeling amino acid replacement. J Comp Biol 7, 761–776.

    Google Scholar 

  110. Adachi, J., Waddell, P. J., Martin, W., et al. (2000) Plastid genome phylogeny and a model of amino acid substitution for proteins encoded by chloroplast DNA. J Mol Evol 50, 348–358.

    PubMed  CAS  Google Scholar 

  111. Whelan, S., Goldman, N. (2001) A general empirical model of protein evolution derived from multiple protein families using a maximum likelihood approach. Mol Biol Evol 18, 691–699.

    PubMed  CAS  Google Scholar 

  112. Dimmic, M. W., Rest, J. S., Mindell, D. P., Goldstein, R. A. (2002) RtREV: an amino acid substitution matrix for inference of ret-rovirus and reverse transcriptase phylogeny. J Mol Evol 55, 65–73.

    PubMed  CAS  Google Scholar 

  113. Abascal, F., Posada, D., Zardoya, R. (2007) MtArt: a new model of amino acid replacement for Arthropoda. Mol Biol Evol 24, 1–5.

    PubMed  CAS  Google Scholar 

  114. Shapiro, B., Rambaut, A., Drummond, A. J. (2005) Choosing appropriate substitution models for the phylogenetic analysis of protein-coding sequences. Mol Biol Evol 23, 7–9.

    PubMed  Google Scholar 

  115. Hyman, I. T., Ho, S. Y. W., Jermiin, L. S. (2007) Molecular phylogeny of Australian Helicarionidae, Microcystidae and related groups (Gastropoda: Pulmonata: Stylom-matophora) based on mitochondrial DNA. Mol Phylogenet Evol, 45, 792–812.

    CAS  Google Scholar 

  116. Galtier, N. (2001) Maximum-likelihood phylogenetic analysis under a covarion-like model. Mol Biol Evol 18, 866–873.

    PubMed  CAS  Google Scholar 

  117. Hudelot, C., Gowri-Shankar, V., Jow, H., et al. (2003) RNA-based phylogenetic methods: Application to mammalian mitochondrial RNA sequences. Mol Phylogenet Evol 28, 241–252.

    PubMed  CAS  Google Scholar 

  118. Murray, S., Flø Jørgensen, M., Ho, S. Y. W., et al. (2005) Improving the analysis of dino-flagelate phylogeny based on rDNA. Protist 156, 269–286.

    PubMed  CAS  Google Scholar 

  119. Felsenstein, J. (1981) Evolutionary trees from DNA sequences: a maximum likelihood approach. J Mol Evol 17, 368–376.

    PubMed  CAS  Google Scholar 

  120. Hasegawa, M., Kishino, H., Yano, T. (1985) Dating of the human-ape splitting by a molecular clock of mitochondrial DNA. J Mol Evol 22, 160–174.

    PubMed  CAS  Google Scholar 

  121. Kimura, M. (1980) A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucle-otide sequences. J Mol Evol 16, 111–120.

    PubMed  CAS  Google Scholar 

  122. Zharkikh, A. (1994) Estimation of evolutionary distances between nucleotide sequences. J Mol Evol 39, 315–329.

    PubMed  CAS  Google Scholar 

  123. Burnham, K. P., Anderson, D. R. (2002) Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach. Springer, New York.

    Google Scholar 

  124. Posada, D., Buckley, T. R. (2004) Model selection and model averaging in phylogenetics: advantages of akaike information criterion and bayesian approaches over likelihood ratio tests. Syst Biol 53, 793–808.

    PubMed  Google Scholar 

  125. Akaike, H. (1974) A new look at the statistical model identification. IEEE Trans Auto Cont 19, 716–723.

    Google Scholar 

  126. Sugiura, N. (1978) Further analysis of the data by Akaike's information criterion and the finite corrections. Commun Stat A: Theory Methods 7, 13–26.

    Google Scholar 

  127. Schwarz, G. (1978) Estimating the dimension of a model. Ann Stat 6, 461–464.

    Google Scholar 

  128. Suchard, M. A., Weiss, R. E., Sinsheimer, J. S. (2001) Bayesian selection of continuous-time Markov chain evolutionary models. Mol Biol Evol 18, 1001–1013.

    PubMed  CAS  Google Scholar 

  129. Aris-Brosou, S., Yang, Z. (2002) Effects of models of rate evolution on estimation of divergence dates with special reference to the metazoan 18S ribosomal RNA phylogeny. Syst Biol 51, 703–714.

    PubMed  Google Scholar 

  130. Nylander, J. A., Ronquist, F., Huelsenbeck, J. P., et al. (2004) Bayesian phylogenetic analysis of combined data. Syst Biol 53, 47–67.

    PubMed  Google Scholar 

  131. Kass, R. E., Raftery, A. E. (1995) Bayes factors. J Am Stat Assoc 90, 773–795.

    Google Scholar 

  132. Raftery, A. E. (1996) Hypothesis testing and model selection, in (Gilks, W. R., Richardson, S. and Spiegelhalter, D. J., eds.), Markov Chain Monte Carlo in Practice. Chapman & Hall, London.

    Google Scholar 

  133. Minin, V., Abdo, Z., Joyce, P., et al. (2003) Performance-based selection of likelihood models for phylogenetic estimation. Syst Biol 52, 674–683.

    PubMed  Google Scholar 

  134. Posada, D., Crandall, K. A. (2001) Selecting methods of nucleotide substitution: An application to human immunodeficiency virus 1 (HIV-1). Mol Biol Evol 18, 897–906.

    PubMed  CAS  Google Scholar 

  135. Poladian, L., Jermiin, L. S. (2006) Multi-objective evolutionary algorithms and phy-logenetic inference with multiple data sets. Soft Comp 10, 358–368.

    Google Scholar 

  136. Cox, D. R. (1962) Further results on tests of separate families of hypotheses. J Royal Stat Soc B 24, 406–424.

    Google Scholar 

  137. Rambaut, A., Grassly, N. C. (1997) Seq-Gen: An application for the Monte Carlo simulation of DNA sequence evolution along phylogenetic trees. Comp Appl Biosci 13, 235–238.

    PubMed  CAS  Google Scholar 

  138. Felsenstein, J. (2003) Inferring phylogenies. Sinauer Associates, Sunderland, MA.

    Google Scholar 

  139. Rokas, A., Krüger, D., Carroll, S. B. (2005) Animal evolution and the molecular signature of radiations compressed in time. Science 310, 1933–1938.

    PubMed  Google Scholar 

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Acknowledgments

This research was partly funded by Discover y Grants (DP0453173 and DP0556820) from the Australian Research Council. Faisal Ababneh was supported by a postgraduate scholarship from the Al-Hussein Bin Talal University in Jordan. The authors wish to thank J.W.K. Ho, J. Keith, K.W. Lau, G.J.P. Naylor, S. Whelan, and Y. Zhang for their constructive thoughts, ideas, and criticism on this manuscript.

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Authors and Affiliations

  1. School of Biological Sciences, Sydney Bioinformatics and Centre for Mathematical Biology, University of Sydney, Sydney, New South Wales, Australia

    Lars Sommer Jermiin

  2. School of Mathematics and Statistics, Sydney Bioinformatics and Centre for Mathematical Biology, University of Sydney, Sydney, New South Wales, Australia

    Vivek Jayaswal

  3. Department of Mathematics and Statistics, Al-Hussein Bin Talal University, Ma'an, Jordan

    Faisal Ababneh

  4. School of Mathematics and Statistics and Centre for Mathematical Biology, University of Sydney, Sydney, New South Wales, Australia

    John Robinson

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  1. Lars Sommer Jermiin
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  2. Vivek Jayaswal
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  3. Faisal Ababneh
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  4. John Robinson
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Editors and Affiliations

  1. School of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia

    Jonathan M. Keith PhD

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© 2008 Humana Press, a part of Springer Science+Business Media, LLC

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Jermiin, L.S., Jayaswal, V., Ababneh, F., Robinson, J. (2008). Phylogenetic Model Evaluation. In: Keith, J.M. (eds) Bioinformatics. Methods in Molecular Biology™, vol 452. Humana Press. https://doi.org/10.1007/978-1-60327-159-2_16

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  • DOI: https://doi.org/10.1007/978-1-60327-159-2_16

  • Publisher Name: Humana Press

  • Print ISBN: 978-1-58829-707-5

  • Online ISBN: 978-1-60327-159-2

  • eBook Packages: Springer Protocols

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