Bayesian Estimation of Ancestral Character States on Phylogenies
Biologists frequently attempt to infer the character states at ancestral nodes of a phylogeny from the distribution of traits observed in contemporary organisms. Because phylogenies are normally inferences from data, it is desirable to account for the uncertainty in estimates of the tree and its bra...
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| Published in | Systematic biology Vol. 53; no. 5; pp. 673 - 684 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
England
Society of Systematic Zoology
01.10.2004
Taylor and Francis Oxford University Press |
| Subjects | |
| Online Access | Get full text |
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| Abstract | Biologists frequently attempt to infer the character states at ancestral nodes of a phylogeny from the distribution of traits observed in contemporary organisms. Because phylogenies are normally inferences from data, it is desirable to account for the uncertainty in estimates of the tree and its branch lengths when making inferences about ancestral states or other comparative parameters. Here we present a general Bayesian approach for testing comparative hypotheses across statistically justified samples of phylogenies, focusing on the specific issue of reconstructing ancestral states. The method uses Markov chain Monte Carlo techniques for sampling phylogenetic trees and for investigating the parameters of a statistical model of trait evolution. We describe how to combine information about the uncertainty of the phylogeny with uncertainty in the estimate of the ancestral state. Our approach does not constrain the sample of trees only to those that contain the ancestral node or nodes of interest, and we show how to reconstruct ancestral states of uncertain nodes using a most-recent-common-ancestor approach. We illustrate the methods with data on ribonuclease evolution in the Artiodactyla. Software implementing the methods (BayesMultiState) is available from the authors. |
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| AbstractList | Biologists frequently attempt to infer the character states at ancestral nodes of a phylogeny from the distribution of traits observed in contemporary organisms. Because phylogenies are normally inferences from data, it is desirable to account for the uncertainty in estimates of the tree and its branch lengths when making inferences about ancestral states or other comparative parameters. Here we present a general Bayesian approach for testing comparative hypotheses across statistically justified samples of phylogenies, focusing on the specific issue of reconstructing ancestral states. The method uses Markov chain Monte Carlo techniques for sampling phylogenetic trees and for investigating the parameters of a statistical model of trait evolution. We describe how to combine information about the uncertainty of the phylogeny with uncertainty in the estimate of the ancestral state. Our approach does not constrain the sample of trees only to those that contain the ancestral node or nodes of interest, and we show how to reconstruct ancestral states of uncertain nodes using a most-recent-common-ancestor approach. We illustrate the methods with data on ribonuclease evolution in the Artiodactyla. Software implementing the methods (BayesMultiState) is available from the authors. Biologists frequently attempt to infer the character states at ancestral nodes of a phylogeny from the distribution of traits observed in contemporary organisms. Because phylogenies are normally inferences from data, it is desirable to account for the uncertainty in estimates of the tree and its branch lengths when making inferences about ancestral states or other comparative parameters. Here we present a general Bayesian approach for testing comparative hypotheses across statistically justified samples of phylogenies, focusing on the specific issue of reconstructing ancestral states. The method uses Markov chain Monte Carlo techniques for sampling phylogenetic trees and for investigating the parameters of a statistical model of trait evolution. We describe how to combine information about the uncertainty of the phylogeny with uncertainty in the estimate of the ancestral state. Our approach does not constrain the sample of trees only to those that contain the ancestral node or nodes of interest, and we show how to reconstruct ancestral states of uncertain nodes using a most-recent-common-ancestor approach. We illustrate the methods with data on ribonuclease evolution in the Artiodactyla. Software implementing the methods (BayesMultiState) is available from the authors. [Ancestral states; comparative methods; maximum likelihood; MCMC; phylogeny.] [PUBLICATION ABSTRACT] Biologists frequently attempt to infer the character states at ancestral nodes of a phylogeny from the distribution of traits observed in contemporary organisms. Because phylogenies are normally inferences from data, it is desirable to account for the uncertainty in estimates of the tree and its branch lengths when making inferences about ancestral states or other comparative parameters. Here we present a general Bayesian approach for testing comparative hypotheses across statistically justified samples of phylogenies, focusing on the specific issue of reconstructing ancestral states. The method uses Markov chain Monte Carlo techniques for sampling phylogenetic trees and for investigating the parameters of a statistical model of trait evolution. We describe how to combine information about the uncertainty of the phylogeny with uncertainty in the estimate of the ancestral state. Our approach does not constrain the sample of trees only to those that contain the ancestral node or nodes of interest, and we show how to reconstruct ancestral states of uncertain nodes using a most-recent-common-ancestor approach. We illustrate the methods with data on ribonuclease evolution in the Artiodactyla. Software implementing the methods (BayesMultiState) is available from the authors.Biologists frequently attempt to infer the character states at ancestral nodes of a phylogeny from the distribution of traits observed in contemporary organisms. Because phylogenies are normally inferences from data, it is desirable to account for the uncertainty in estimates of the tree and its branch lengths when making inferences about ancestral states or other comparative parameters. Here we present a general Bayesian approach for testing comparative hypotheses across statistically justified samples of phylogenies, focusing on the specific issue of reconstructing ancestral states. The method uses Markov chain Monte Carlo techniques for sampling phylogenetic trees and for investigating the parameters of a statistical model of trait evolution. We describe how to combine information about the uncertainty of the phylogeny with uncertainty in the estimate of the ancestral state. Our approach does not constrain the sample of trees only to those that contain the ancestral node or nodes of interest, and we show how to reconstruct ancestral states of uncertain nodes using a most-recent-common-ancestor approach. We illustrate the methods with data on ribonuclease evolution in the Artiodactyla. Software implementing the methods (BayesMultiState) is available from the authors. Abstract Biologists frequently attempt to infer the character states at ancestral nodes of a phylogeny from the distribution of traits observed in contemporary organisms. Because phylogenies are normally inferences from data, it is desirable to account for the uncertainty in estimates of the tree and its branch lengths when making inferences about ancestral states or other comparative parameters. Here we present a general Bayesian approach for testing comparative hypotheses across statistically justified samples of phylogenies, focusing on the specific issue of reconstructing ancestral states. The method uses Markov chain Monte Carlo techniques for sampling phylogenetic trees and for investigating the parameters of a statistical model of trait evolution. We describe how to combine information about the uncertainty of the phylogeny with uncertainty in the estimate of the ancestral state. Our approach does not constrain the sample of trees only to those that contain the ancestral node or nodes of interest, and we show how to reconstruct ancestral states of uncertain nodes using a most-recent-common-ancestor approach. We illustrate the methods with data on ribonuclease evolution in the Artiodactyla. Software implementing the methods (BayesMultiState) is available from the authors. |
| Author | Barker, Daniel Meade, Andrew Pagel, Mark |
| Author_xml | – sequence: 1 givenname: Mark surname: Pagel fullname: Pagel, Mark email: School of Animal and Microbial Sciences, University of Reading, Whiteknights Reading RG6 6AJ England; m.pagel@rdg.ac.uk (M.P.), m.pagel@rdg.ac.uk organization: School of Animal and Microbial Sciences, University of Reading, Whiteknights Reading RG6 6AJ England; E-mail: m.pagel@rdg.ac.uk (M.P.) – sequence: 2 givenname: Andrew surname: Meade fullname: Meade, Andrew email: School of Animal and Microbial Sciences, University of Reading, Whiteknights Reading RG6 6AJ England; m.pagel@rdg.ac.uk (M.P.), m.pagel@rdg.ac.uk organization: School of Animal and Microbial Sciences, University of Reading, Whiteknights Reading RG6 6AJ England; E-mail: m.pagel@rdg.ac.uk (M.P.) – sequence: 3 givenname: Daniel surname: Barker fullname: Barker, Daniel email: School of Animal and Microbial Sciences, University of Reading, Whiteknights Reading RG6 6AJ England; m.pagel@rdg.ac.uk (M.P.), m.pagel@rdg.ac.uk organization: School of Animal and Microbial Sciences, University of Reading, Whiteknights Reading RG6 6AJ England; E-mail: m.pagel@rdg.ac.uk (M.P.) – sequence: 4 givenname: Jeffrey surname: Thorne fullname: Thorne, Jeffrey email: m.pagel@rdg.ac.uk organization: School of Animal and Microbial Sciences, University of Reading, Whiteknights, Reading RG6 6AJ England |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/15545248$$D View this record in MEDLINE/PubMed |
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| Cites_doi | 10.1111/j.1558-5646.1997.tb05095.x 10.1080/106351599260184 10.1038/377108a0 10.1080/10635150490468675 10.1080/106351599260238 10.1093/sysbio/42.2.193 10.1080/10635150390192726 10.1093/genetics/150.1.499 10.1038/374057a0 10.1093/nar/25.24.4876 10.1098/rspb.1994.0006 10.1038/35082053 10.1007/BF00160154 10.1080/106351599260193 10.1080/10635150119871 10.1111/j.1463-6409.1997.tb00423.x 10.1098/rspb.2002.1955 10.1038/44766 10.1126/science.283.5399.220 10.1093/biomet/57.1.97 10.1063/1.1699114 10.1080/106351501753462876 10.1080/10635150290102393 10.1093/biomet/83.2.315 10.1007/BF02338839 10.1214/ss/1177011137 10.1038/35035065 10.1093/oxfordjournals.molbev.a026160 10.1111/j.0006-341X.1999.00001.x 10.1126/science.1065889 10.1007/3-540-45692-9_8 10.1073/pnas.93.23.13429 |
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| References | Pagel ( key 20180228053108_b30) Felsenstein ( key 20180228053108_b4) 1993; 42 Metropolis ( key 20180228053108_b19) 1953; 21 Schluter ( key 20180228053108_b33) 1997; 51 Geyer ( key 20180228053108_b6) 1992; 7 Pagel ( key 20180228053108_b28) 2002 Huelsenbeck ( key 20180228053108_b12) 2001; 50 Swofford ( key 20180228053108_b34) 1996 Gilks ( key 20180228053108_b7) 1996 Galtier ( key 20180228053108_b5) 1999; 283 Schluter ( key 20180228053108_b32) 1995; 377 Yang ( key 20180228053108_b37) 1994; 39 Holden ( key 20180228053108_b11) 2002; 269 Mau ( key 20180228053108_b18) 1999; 55 Pagel ( key 20180228053108_b25) 1997; 26 Rannala ( key 20180228053108_b31) 1996; 43 Efron ( key 20180228053108_b3) 1996; 93 Hastings ( key 20180228053108_b9) 1970; 57 Edwards ( key 20180228053108_b2) 1972 Lewis ( key 20180228053108_b16) 2001; 50 Hibbett ( key 20180228053108_b10) 2000; 407 Larget ( key 20180228053108_b15) 1999; 16 Pagel ( key 20180228053108_b24) 1994; 255 Newton ( key 20180228053108_b21) 1996; 83 Newton ( key 20180228053108_b22) 1999 Wilson ( key 20180228053108_b36) 1998; 150 Nielsen ( key 20180228053108_b23) 2002; 51 Huelsenbeck ( key 20180228053108_b13) 2001; 294 Mooers ( key 20180228053108_b20) 1999; 48 Hassanin ( key 20180228053108_b8) 2003; 52 Pagel ( key 20180228053108_b29) 2004; 53 Pagel ( key 20180228053108_b27) 1999; 48 Jermann ( key 20180228053108_b14) 1995; 374 Cunningham ( key 20180228053108_b1) 1999; 48 Thompson ( key 20180228053108_b35) 1997; 25 Lutzoni ( key 20180228053108_b17) 2001; 411 Pagel ( key 20180228053108_b26) 1999; 401 |
| References_xml | – volume: 51 start-page: 1699 year: 1997 ident: key 20180228053108_b33 article-title: Likelihood of ancestor states in adaptive radiation publication-title: Evolution doi: 10.1111/j.1558-5646.1997.tb05095.x – volume: 48 start-page: 612 year: 1999 ident: key 20180228053108_b27 article-title: The maximum likelihood approach to reconstructing ancestral character states on phylogenies publication-title: Syst. Biol. doi: 10.1080/106351599260184 – volume: 377 start-page: 108 year: 1995 ident: key 20180228053108_b32 article-title: Uncertainty in ancient phylogenies publication-title: Nature doi: 10.1038/377108a0 – start-page: 407 volume-title: Molecular systematics, 2nd edition year: 1996 ident: key 20180228053108_b34 article-title: Phylogenetic inference – volume: 53 start-page: 571 year: 2004 ident: key 20180228053108_b29 article-title: A phylogenetic mixture model for detecting pattern-heterogeneity in gene sequence or character-state data publication-title: Syst. Biol. doi: 10.1080/10635150490468675 – volume: 48 start-page: 665 year: 1999 ident: key 20180228053108_b1 article-title: Some limitations of ancestral character-state reconstruction when testing evolutionary hypotheses publication-title: Syst. Biol. doi: 10.1080/106351599260238 – volume: 42 start-page: 193 year: 1993 ident: key 20180228053108_b4 article-title: Is there something wrong with the bootstrap? A reply to Hillis and Bull publication-title: Syst. Biol. doi: 10.1093/sysbio/42.2.193 – volume: 52 start-page: 206 year: 2003 ident: key 20180228053108_b8 article-title: Molecular and morphological phylogenies of Ruminantia, and the alternative position of the Moschidae publication-title: Syst. Biol. doi: 10.1080/10635150390192726 – volume: 150 start-page: 499 year: 1998 ident: key 20180228053108_b36 article-title: Genealogical inference from microsatellite data publication-title: Genetics doi: 10.1093/genetics/150.1.499 – volume: 374 start-page: 57 year: 1995 ident: key 20180228053108_b14 article-title: Reconstructing the evolutionary history of the artiodactyl ribonulcease superfamily publication-title: Nature doi: 10.1038/374057a0 – volume: 25 start-page: 4876 year: 1997 ident: key 20180228053108_b35 article-title: The CLUSTAL X windows interface: Flexible strategies for multiple sequence alignment aided by quality analysis tools publication-title: Nucleic Acids Res. doi: 10.1093/nar/25.24.4876 – volume: 255 start-page: 37 year: 1994 ident: key 20180228053108_b24 article-title: Detecting correlated evolution on phylogenies: A general method for the comparative analysis of discrete characters publication-title: Proc. R. Soc. B doi: 10.1098/rspb.1994.0006 – start-page: 1 volume-title: Markov Chain Monte Carlo in Practice year: 1996 ident: key 20180228053108_b7 article-title: Introducing Markov chain Monte Carlo – volume: 411 start-page: 937 year: 2001 ident: key 20180228053108_b17 article-title: Major fungal lineages derived from lichen-symbiotic ancestors publication-title: Nature doi: 10.1038/35082053 – volume: 39 start-page: 306 year: 1994 ident: key 20180228053108_b37 article-title: Maximum likelihood phylogenetic estimation from DNA sequences with variable rates over sites: approximate methods publication-title: J. Mol. Evol. doi: 10.1007/BF00160154 – volume: 48 start-page: 623 year: 1999 ident: key 20180228053108_b20 article-title: Support for one and two rate models of discrete trait evolution publication-title: Syst. Biol. doi: 10.1080/106351599260193 – volume-title: The evolution of cultural diversity: A phylogenetic approach ident: key 20180228053108_b30 article-title: Bayesian estimation of correlated evolution across cultures: A case study of marriage systems and wealth transfer at marriage. To appear – year: 1972 ident: key 20180228053108_b2 article-title: Likelihood – volume: 50 start-page: 351 year: 2001 ident: key 20180228053108_b12 article-title: Empirical and hierarchical Bayesian estimation of ancestral states publication-title: Syst. Biol. doi: 10.1080/10635150119871 – volume: 26 start-page: 331 year: 1997 ident: key 20180228053108_b25 article-title: Inferring evolutionary processes from phylogenies publication-title: Zool. Scripta doi: 10.1111/j.1463-6409.1997.tb00423.x – volume: 269 start-page: 793 year: 2002 ident: key 20180228053108_b11 article-title: Bantu language trees reflect the spread of farming across sub-Saharan Africa: A maximum-parsimony analysis publication-title: Proc. R. Soc. Lond. B doi: 10.1098/rspb.2002.1955 – volume: 401 start-page: 877 year: 1999 ident: key 20180228053108_b26 article-title: Inferring the historical patterns of biological evolution publication-title: Nature doi: 10.1038/44766 – volume: 283 start-page: 220 year: 1999 ident: key 20180228053108_b5 article-title: A nonhyperthermophilic common ancestor to extant life forms publication-title: Science doi: 10.1126/science.283.5399.220 – volume: 57 start-page: 97 year: 1970 ident: key 20180228053108_b9 article-title: Monte Carlo sampling methods using Markov chains and their applications publication-title: Biometrika doi: 10.1093/biomet/57.1.97 – volume: 21 start-page: 1087 year: 1953 ident: key 20180228053108_b19 article-title: Equation of state calculations by fast computing machines publication-title: J. Chem. Phys. doi: 10.1063/1.1699114 – volume: 50 start-page: 913 year: 2001 ident: key 20180228053108_b16 article-title: A likelihood approach to estimating phylogeny from discrete morphological character data publication-title: Syst. Biol. doi: 10.1080/106351501753462876 – volume: 51 start-page: 729 year: 2002 ident: key 20180228053108_b23 article-title: Mapping mutations on phylogenies publication-title: Syst. Biol. doi: 10.1080/10635150290102393 – volume: 83 start-page: 315 year: 1996 ident: key 20180228053108_b21 article-title: Bootstrapping phylogenies: Large deviations and dispersion effects publication-title: Biometrika doi: 10.1093/biomet/83.2.315 – volume: 43 start-page: 304 year: 1996 ident: key 20180228053108_b31 article-title: Probability distributions of molecular evolutionary trees: A new method of phylogenetic inference publication-title: J. Mol. Evol. doi: 10.1007/BF02338839 – volume: 7 start-page: 473 year: 1992 ident: key 20180228053108_b6 article-title: Practical Markov chain Monte Carlo publication-title: Stat. Sci. doi: 10.1214/ss/1177011137 – volume: 407 start-page: 506 year: 2000 ident: key 20180228053108_b10 article-title: Evolutionary instability of ectomycorrhizal symbioses in basidiomycetes publication-title: Nature doi: 10.1038/35035065 – volume: 16 start-page: 750 year: 1999 ident: key 20180228053108_b15 article-title: Markov chain monte carlo algorithms for the Bayesian analysis of phylogenetic trees publication-title: Mol. Biol. Evol. doi: 10.1093/oxfordjournals.molbev.a026160 – volume: 55 start-page: 1 year: 1999 ident: key 20180228053108_b18 article-title: Bayesian phylogenetic inference via Markov chain Monte Carlo methods publication-title: Biometrics doi: 10.1111/j.0006-341X.1999.00001.x – volume: 294 start-page: 2310 year: 2001 ident: key 20180228053108_b13 article-title: Bayesian inference of phylogeny and its impact on evolutionary biology publication-title: Science doi: 10.1126/science.1065889 – start-page: 148 volume-title: Biological evolution and statistical physics year: 2002 ident: key 20180228053108_b28 article-title: Accounting for phylogenetic uncertainty in comparative studies of evolution and adaptation doi: 10.1007/3-540-45692-9_8 – volume: 93 start-page: 13429 year: 1996 ident: key 20180228053108_b3 article-title: Bootstrap confidence levels for phylogenetic trees publication-title: Proc. Natl. Acad. Sci. USA doi: 10.1073/pnas.93.23.13429 – start-page: 143 volume-title: Statistics in molecular biology year: 1999 ident: key 20180228053108_b22 article-title: Markov chain Monte Carlo for the Bayesian analysis of evolutionary trees from aligned molecular sequences |
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| Snippet | Biologists frequently attempt to infer the character states at ancestral nodes of a phylogeny from the distribution of traits observed in contemporary... Abstract Biologists frequently attempt to infer the character states at ancestral nodes of a phylogeny from the distribution of traits observed in contemporary... |
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| SubjectTerms | Ancestral states Animals Artiodactyla - genetics Bayes Theorem Bayesian analysis Biological diversity Biological taxonomies Classification - methods Coefficients comparative methods Comparative studies Decision trees Evolution Evolution, Molecular Evolutionary biology Markov Chains maximum likelihood MCMC Models, Biological Monte Carlo Method Monte Carlo simulation Parametric models Phenotypic traits Phylogenetics Phylogeny Probability distributions Ribonucleases - genetics Statistical models |
| Title | Bayesian Estimation of Ancestral Character States on Phylogenies |
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