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Nucleotide substitution models

Model Reference d.f. Base freq Symmetries code
JC Jukes and Cantor 1969 0 equal AC=AG=AT=CG=CT=GT 000000
F81 Felsenstein, 1981 3 unequal AC=AG=AT=CG=CT=GT 000000
K80 Kimura, 1980 1 equal AC=AT=CG=GT AG=GT 010010
HKY Hasegawa et al., 1985 4 unequal AC=AT=CG=GT AG=GT 010010
TrNef (TN93ef) Tamura and Nei, 1993 2 equal AC=AT=CG=GT AG GT 010020
TrN (TN93) Tamura and Nei, 1993 5 unequal AC=AT=CG=GT AG GT 010020
TPM1 (K81) Kimura, 1981 2 equal AC=GT AG=CT AT=CG 012210
TPM1uf (K81uf) Kimura, 1981 5 unequal AC=GT AG=CT AT=CG 012210
TPM2 2 equal AC=AT CG=GT AG=CT 010212
TPM2uf 5 unequal AC=AT CG=GT AG=CT 010212
TPM3 2 equal AC=AT AG=GT AG=CT 012012
TPM3uf 5 unequal AC=CG AT=GT AG=CT 012012
TIM1 Posada, 2003 3 equal AC=GT AT=CG AG CT 012230
TIM1uf Posada, 2003 6 unequal AC=GT AT=CG AG CT 012230
TIM2 3 equal AC=AT CG=GT AG;CT 010232
TIM2uf 6 unequal AC=AT CG=GT AG;CT 010232
TIM3 3 equal AC=CG AT=GT AG CT 012032
TIM3uf 6 unequal AC=CG AT=GT AG CT 012032
TVMef Posada, 2003 4 equal AC CG AT GT AG=CT 012314
TVM Posada, 2003 7 unequal AC CG AT GT AG=CT 012314
SYM Zharkikh, 1994 5 equal AC CG AT GT AG CT 012345
GTR (REV) Tavaré. 1986 8 unequal AC CG AT GT AG CT 012345

References

  • Abdo, Z., Minin, V., Joyce, P., and Sullivan, J. (2005). Accounting for uncertainty in the tree topology has little effect on the decision-theoretic approach to model selection in phylogeny estimation. Molecular Biology and Evolution, 22, 691–703.
  • Akaike, H. (1974). A new look at the statistical model identification. IEEE Transactions on Automatic Control, 19, 716–723.
  • Burnham, K. and Anderson, D. (1998). Model selection and inference: a practical information-theoretic approach. Springer-Verlag, New York, NY.
  • Burnham, K. and Anderson, D. (2003). Model selection and multimodel inference: a practical information-theoretic approach. Springer-Verlag, New York, NY.
  • Felsenstein, J. (1981). Evolutionary trees from dna sequences: A maximum likelihood approach. Journal of Molecular Evolution, 17, 368–376.
  • Felsenstein, J. (1988). Phylogenies from molecular sequences: inference and reliability. Annual Review of Genetics, 22, 521–565.
  • Goldman, N. (1993a). Simple diagnostic statistical test of models of dna substitution. Journal of Molecular Evolution, 37, 650–661.
  • Goldman, N. (1993b). Statistical tests of models of dna substitution. Journal of Molecular Evolution, 36, 182–198.
  • Goldman, N. and Whelan, S. (2000). Statistical tests of gamma-distributed rate heterogeneity in models of sequence evolution in phylogenetics. Molecular Biology and Evolution, 17, 975–978.
  • Hasegawa, M., Kishino, K., and Yano, T. (1985). Dating the human-ape splitting by a molecular clock of mitochondrial dna. Journal of Molecular Evolution, 22, 160–174.
  • Hoeting, J., Madigan, D., and Raftery, A. (1999). Bayesian model averaging: A tutorial. Statistical Science, 14, 382–417.
  • Huelsenbeck, J., Larget, B., and Alfaro, M. (2004). Bayesian phylogenetic model selection using reversible jump markov chain monte carlo. Molecular Biology and Evolution, 21, 1123–1133.
  • Hurvich, C. and Tsai, C. (1989). Regression and time series model selection in small samples. Biometrika, 76, 297–307.
  • Johnson, J. and Omland, K. (2003). Model selection in ecology and evolution. Trends in Ecology and Evolution, 19, 101–108.
  • Jukes, T. and Cantor, C. (1969). Evolution of protein molecules. Academic Press, New York, NY, pages 21–132.
  • Kendall, M. and Stuart, A. (1979). The advanced theory of statistics. Charles Griffin, London.
  • Kimura, M. (1980). A simple method for estimating evolutionary rate of base substitutions through comparative studies of nucleotide sequences. Journal of Molecular Evolution, 16, 111–120.
  • Kimura, M. (1981). Estimation of evolutionary distances between homologous nucleotide sequences. Proceedings of the National Academy of Sciences, U.S.A, 78, 454–458.
  • Madigan, D. and Raftery, A. (1994). Model selection and accounting for model uncertainty in graphical models using occam’s window. Journal of the American Statistical Association, 59, 1335–1346.
  • Minin, V., Abdo, Z., and P. Joyce, J. S. (2003). Performance-based selection of likelihood models for phylogeny estimation. Systematic Biology, 52, 674–683.
  • Ohta, T. (1992). Theoretical study of near neutrality. ii. effect of subdivided population structure with local extinction and recolonization. Genetics, pages 917–923.
  • Posada, D. (2003). Using modeltest and paup to select a model of nucleotide substitution. pages 6.5.1–6.5.14.
  • Posada, D. and Buckley, T. (2004). Model selection and model averaging in phylogenetics: advantages of akaike information criterion and bayesian approaches over likelihood ratio tests. Systematic Biology, 53, 793–808.
  • Posada, D. and Crandall, K. (2001). Selecting the best-fit model of nucleotide substitution. Systematic Biology, 50, 580–601.
  • Raftery, A. (1996). Hypothesis testing and model selection. Markov chain Monte Carlo in practice. Chapman and Hall, London, pages 163–187.
  • S. Kullback, R. L. (1951). On information and sufficiency. Annals of Mathematical Statistics, 22, 79–86.
  • Schwarz, G. (1978). Estimating the dimension of a model. The Annals of Statistics, 6, 461–464.
  • Sugiura, N. (1978). Further analysis of the data by akaike’s information criterion and the finite corrections. Communications in StatisticsTheory and Methods, A7, 13–26.
  • Sullivan, J. and Joyce, P. (2005). Model selection in phylogenetics. Annual Review of Ecology, Evolution and Systematics, 36, 445–466.
  • Tamura, K. and Nei, M. (1993). Estimation of the number of nucleotide substitutions in the control region of mitochondrial dna in humans and chimpanzees. Molecular Biology and Evolution, 10, 512–526.
  • Tavaré, S. (1986). Some probabilistic and statistical problems in the analysis of dna sequences. Some mathematical questions in biology - DNA sequence analysis. Amer. Math. Soc., Providence, RI, pages 57–86.
  • Wasserman, L. (2000). Bayesian model selection and model averaging. Journal of Mathematical Psychology 44:92-107, 44, 92–107.
  • Whelan, S. and Goldman, N. (1999). Distributions of statistics used for the comparison of models of sequence evolution in phylogenetics. Molecular Biology and Evolution, 16, 1292–1299.
  • Yang, Z., Goldman, N., and A.Friday (1995). Maximum likelihood trees from dna sequences: a peculiar statistical estimation problem. Systematic Biology, 44, 384–399.
  • Zharkikh, A. (1994). Estimation of evolutionary distances between nucleotide sequences. Journal of Molecular Evolution, 39, 315–329.

Amino acid replacement models

  1. Dayhoff (Dayhoff et al., 1978)
  2. LG (Le and Gascuel, 2008)
  3. DCMut (Kosiol and Goldman, 2005)
  4. JTT (Jones et al., 1992)
  5. mtREV (Adachi and Hasegawa, 1996)
  6. WAG (Whelan and Goldman, 2001)
  7. RtREV (Dimmic et al., 2002)
  8. CpREV (Adachi and Waddell, 2000)
  9. VT (Muller and Vingron 2000)
  10. Blosum62 (Henikoff and Henikoff, 1992)
  11. MtMam (Cao et al., 1998)
  12. MtArt (Abascal et al., 2007)
  13. MtZoa (Rota-Stabelli et al., 2009)
  14. PMB (Veerassamy, Smith and Tillier, 2003)
  15. HIVb (Nickle et al. 2007)
  16. HIVw (Nickle et al. 2007)
  17. JTT-DCMut (Kosiol and Goldman, 2005)
  18. FLU (Dang et al., 2010)
  19. StmtREV (Liu et al., 2014)

References

  • Abascal, F., Posada, D., and Zardoya, R. 2007. MtArt: a new model of amino acid replacement for Arthropoda. Mol Biol Evol 24: 1-5.
  • Adachi, J., and Hasegawa, M. 1996. Model of amino acid substitution in proteins encoded by mitochondrial DNA. J. Mol. Evol. 42: 459-468.
  • Adachi, J., Waddell, P.J., Martin, W., and Hasegawa, M. 2000. Plastid genome phylogeny and a model of amino acid substitution for proteins encoded by chloroplast DNA. J Mol Evol 50: 348-358.
  • Cao, Y., Janke, A., Waddell, P.J., Westerman, M., Takenaka, O., Murata, S., Okada, N., Paabo, S., and Hasegawa, M. 1998. Conflict among individual mitochondrial proteins in resolving the phylogeny of eutherian orders. J Mol Evol 47: 307-322.
  • Dang, CC, Le, Q.S., Gascuel, O and Le, V. S. 2010. FLU, an amino acid substitution model for influenza proteins. BMC Evolutionary Biology 2010, 10:99.
  • Dayhoff, M.O., Schwartz, R.M., and Orcutt, B.C. 1978. A model of evolutionary change in proteins. In Atlas of Protein Sequence and Structure. (ed. M.O. Dayhoff), pp. 345-352. National Biomedical Research Foundation, Washington, DC.
  • Dimmic, M.W., Rest, J.S., Mindell, D.P., and Goldstein, R.A. 2002. rtREV: an amino acid substitution matrix for inference of retrovirus and reverse transcriptase phylogeny. J Mol Evol 55: 65-73.
  • Henikoff, S., and Henikoff, J.G. 1992. Amino acid substitution matrices from protein blocks. Proc Natl Acad Sci U S A 89: 10915-10919.
  • Jones, D.T., Taylor, W.R., and Thornton, J.M. 1992. The rapid generation of mutation data matrices from protein sequences. Comp. Appl. Biosci. 8: 275-282.
  • Kosiol, C., and Goldman, N.2005. Different Versions of the Dayhoff Rate Matrix. Mol. Biol. Evol. 22:193-199.
  • Le, S.Q., and Gascuel, O. 2008. An improved general amino acid replacement matrix. Mol Biol Evol 25: 1307-1320.
  • Liu, Y., Cox, C. J., Wang, W., & Goffinet, B. 2014. Mitochondrial phylogenomics of early land plants: Mitigating the effects of saturation, compositional heterogeneity, and codon-usage bias. Systematic biology, 63(6), 862-878.
  • Muller, T., and Vingron, M. 2000. Modeling amino acid replacement. J Comput Biol 7: 761-776.
  • Nickle, D.C., Heath, L., Jensen, M.A., Gilbert, P.B., Mullins, J.I., and Kosakovsky Pond, S.L. 2007. HIV-specific probabilistic models of protein evolution. PLoS ONE 2: e503.
  • Rota-Stabelli, O., Yang, Z., & Telford, M. J. 2009. MtZoa: a general mitochondrial amino acid substitutions model for animal evolutionary studies. Molecular phylogenetics and evolution, 52(1), 268-272.
  • Thorne, J.L., and Goldman, N. 2003. Probabilistic models for the study of protein evolution. In Handbook of Statistical Genetics. (ed. M.B. D.J. Balding, and C. Cannings), pp. 209-226. John Wiley & Sons, Ltd., Chichester, England.
  • Veerassamy, S., Smith, A., & Tillier, E. R. 2003. A transition probability model for amino acid substitutions from blocks. Journal of Computational Biology, 10(6), 997-1010.
  • Whelan, S., & Goldman, N. 2001. A general empirical model of protein evolution derived from multiple protein families using a maximum-likelihood approach. Molecular biology and evolution, 18(5), 691-699.
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