Fast simulation of reconstructed phylogenies under global time-dependent birth-death processes

Bioinformatics

Volumn 29, Issue 11, 2013, Pages 1367-1374

  Höhna, Sebastian ^a  

^a STOCKHOLM UNIVERSITY   (Sweden)

Author keywords

[No Author keywords available]

Indexed keywords

AVES;

ALGORITHM; ARTICLE; BIOLOGICAL MODEL; COMPUTER SIMULATION; EVOLUTION; GENETIC VARIABILITY; PHYLOGENY; SPECIES DIFFERENTIATION; SPECIES EXTINCTION;

ALGORITHMS; BIOLOGICAL EVOLUTION; COMPUTER SIMULATION; EXTINCTION, BIOLOGICAL; GENETIC SPECIATION; GENETIC VARIATION; MODELS, BIOLOGICAL; PHYLOGENY;

EID: 84878315827     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/btt153     Document Type: Article

References (40)

1. Aldous, D. and Popovic, L. (2005) A critical branching process model for biodiversity. Adv. Appl. Probab., 37, 1094-1115.
2. Alfaro, M.E. et al. (2009) Nine exceptional radiations plus high turnover explain species diversity in jawed vertebrates. Proc. Natl Acad. Sci., 106, 13410-13414.
3. Astro? m P. et al. (2011) Non-monophyly intricate morphological evolution within the avian family Cettiidae revealed by multilocus analysis of a Taxonomically Densely Sampled Dataset. BMC Evol. Biol. 11 352
4. Beaumont, M.A. et al. (2002) Approximate Bayesian computation in population genetics. Genetics, 162, 2045-2035.
5. Bokma, F. (2008) Bayesian estimation of speciation and extinction probabilities from (in) complete phylogenies. Evolution, 62, 2441-2445.
6. Bollback, J.P. (2002) Bayesian model adequacy and choice in phylogenetics. Mol. Biol. Evol., 19, 1171-1180.
7. Etienne, R. et al. (2012) Diversity-dependence brings molecular phylogenies closer to agreement with the fossil record. Proc. Natl Acad. Sci., 279, 1300-1309.
8. Etienne, R.S. and Rosindell, J. (2012) Prolonging the past counteracts the pull of the present: protracted speciation can explain observed slowdowns in diversification. Syst. Biol., 61, 204-213.
9. Felsenstein, J. (2004) Distance Matrix Methods. Inferring Phylogenies. Sinauer Associates, Sunderland, MA, USA.
10. FitzJohn, R. et al. (2009) Estimating trait-dependent speciation and extinction rates from incompletely resolved phylogenies., Syst. Biol., 58, 595-611.
11. Gelman, A. et al. (2003) Model checking and improvement. In: Bayesian Data analysis, 2nd edn. Chapman & Hall/CRC, New York.
12. Geweke, J. (1991) Evaluating the Accuracy of Sampling-Based Approaches to the Calculation of Posterior Moments. Federal Reserve Bank of Minneapolis, Research Department.
13. Harmon, L.J. et al. (2008) GEIGER: investigating evolutionary radiations. Bioinformatics, 24, 129-131.
14. Hartmann, K. et al. (2010) Sampling trees from evolutionary models., Syst. Biol., 59, 465-476.
15. Hastings, W.K. (1970) Monte carlo sampling methods using Markov chains and their applications. Biometrika, 57, 97-109.
16. Ho?hna, S. et al. (2011) Inferring speciation and extinction rates under different species sampling schemes. Mol. Biol. Evol., 28, 2577-2589.
17. Kendall, D.G. (1948) On the generalized ''Birth-and-Death'' process. Ann. Math. Statist., 19, 1-15.
18. Liow, L.H. et al. (2010) When can decreasing diversification rates be detected with molecular phylogenies and the fossil record? Syst. Biol., 59, 646-659.
19. Maddison, W. et al. (2007) Estimating a binary character's effect on speciation and extinction. Syst. Biol., 56, 701.
20. Metropolis, N. et al. (1953) Equation of state calculations by fast computing machines. J. Chem. Phys., 21, 1087-1092.
21. Morlon, H. et al. (2011) Reconciling molecular phylogenies with the fossil record. Proc. Natl Acad. Sci., 108, 16327-16332.
22. Nee, S. (2006) Birth-death models in macroevolution. Ann. Rev. Ecol. Evol. Syst., 37, 1-17.
23. Nee, S. et al. (1994a) Extinction rates can be estimated from molecular phylogenies. Philos. Trans. R. Soc. Lond. B. Biol. Sci., 344, 77-82.
24. Nee, S. et al. (1994b) The reconstructed evolutionary process. Philos. Trans. R. Soc. Lond. B. Biol. Sci., 344, 305-311.
25. O'Meara, B.C. (2012) Evolutionary Inferences from phylogenies: a review of methods. Annu. Rev. Ecol. Syst., 43, 267-285.
26. Paradis, E. et al. (2004) APE: analyses of phylogenetics and evolution in R language. Bioinformatics, 20, 289-290.
27. Phillimore, A.B. and Price, T.D. (2008) Density-dependent cladogenesis in birds. Plos Biol., 6, e71.
28. Pybus, O.G. and Harvey, P.H. (2000) Testing macro-evolutionary models using incomplete molecular phylogenies. Proc. R. Soc. Lond. B Biol. Sci., 267, 2267-2272.
29. Quental, T.B. and Marshall, C.R. (2009) Extinction during evolutionary radiations: reconciling the fossil record with molecular phylogenies. Evolution, 63, 3158-3167.
30. Rabosky, D. (2006) Likelihood methods for detecting temporal shifts in diversification rates. Evolution, 60, 1152-1164.
31. Rabosky, D.L. (2009) Heritability of extinction rates links diversification patterns in molecular phylogenies and fossils. Syst. Biol., 58, 629-640.
32. Rabosky, D. and Lovette, I. (2008) Explosive evolutionary radiations: decreasing speciation or increasing extinction through time? Evolution, 62, 1866-1875.
33. R Core Team. (2012) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. htpp://www.R-project.org (18 April 2013, date last accessed).
34. Ricklefs, R. (2007) Estimating diversification rates from phylogenetic information. Trends Ecol. Evol., 22, 601-610.
35. Robert, C.P. et al. (2011) Lack of confidence in approximate Bayesian computation model choice. Proc. Natl Acad. Sci., 108, 15112-15117.
36. Soetaert, K. et al. (2010) Solving differential equations in R: Package deSolve. J. Stat. Softw., 33, 1-25.
37. Sokal, R. and Michener, C. (1958) A statistical method for evaluating systems relationships. Univ. of Kans. Sci. Bull., 38, 1409-1438.
38. Stadler, T. (2011) Simulating trees with a fixed number of extant species. Syst. Biol., 60, 676-684.
39. Thompson, E. (1975) The Likelihood Approach. Human Evolutionary Trees. Cambridge University Press, Cambridge.
40. Yang, Z. and Rannala, B. (1997) Bayesian phylogenetic inference using DNA sequences: a Markov Chain Monte Carlo method. Mol. Biol. Evol., 14, 717-724.