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Frequentist properties of Bayesian posterior probabilities of phylogenetic trees under simple and complex substitution models
 SYST. BIOL
, 2004
"... What does die posterior probability of a phylogenetic tree mean? This simulation study shows that Bayesian posterior probabilities have the meaning that is typically ascribed to them; the pt>sterkir probability ot'a tree is the probability that the tree is corwct, assuming th>.it the mo ..."
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Cited by 101 (7 self)
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What does die posterior probability of a phylogenetic tree mean? This simulation study shows that Bayesian posterior probabilities have the meaning that is typically ascribed to them; the pt>sterkir probability ot'a tree is the probability that the tree is corwct, assuming th>.it the model is correct. At the same time, the BayLsian method can be sensitive to model misspecification, and the sensitivity of the Bayesian method appears to be greater than the sensitivity ot " the nonparametric bootstrap method (using maximum likelihood to estimate trees). Although the estimatLs of phylogeny obtained by use of the method of maximum likelihood or the Bayesian method are Ukely to be similar, the assessment of the uncertainty of inferred trees via either bootstriipping (t"or maximum likelihood estimates) or petsterior probabilities (for Bayesian estimates) is not likely to be the same. We suggest that the Bayesian method be implemented with the most complex models of those currently avaiiable, as tliis should reduce the chance that the metliod will concentrate too much probability on tuo few trees. [Bayesian estimation; Markov ch^iin Monte Carlo; posterior probability; prior probability.] Quantify ing the uncertainty of a phylogcneticesti mil te is at least as important a goal as obtaining the phylogenetic estimate itself. Measures of phylogenetic reliability not only point out what parts of a tree can be trusted when interpreting the evolution of a group, but can guide
Phylogenomics and the reconstruction of the tree of life
 Nat Rev Genet
, 2005
"... As more complete genomes are sequenced, phylogenetic analysis is entering a new era — that of phylogenomics. One branch of this expanding field aims to reconstruct the evolutionary history of organisms based on the analysis of their genomes. Recent studies have demonstrated the power of this approac ..."
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Cited by 54 (2 self)
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As more complete genomes are sequenced, phylogenetic analysis is entering a new era — that of phylogenomics. One branch of this expanding field aims to reconstruct the evolutionary history of organisms based on the analysis of their genomes. Recent studies have demonstrated the power of this approach, which has the potential to provide answers to a number of fundamental evolutionary questions. However, challenges for the future have also been revealed. The very nature of the evolutionary history of organisms and the limitations of current phylogenetic reconstruction methods mean that part of the tree of life halsde00193293, version 1 3 Dec 2007 may prove difficult, if not impossible, to resolve with confidence. Introductory paragraph Understanding phylogenetic relationships between organisms is a prerequisite of almost any evolutionary study, as contemporary species all share a common history through their ancestry. The notion of phylogeny follows directly from the theory of evolution presented by Charles Darwin in “The Origin of Species ” 1: the only illustration in his famous book is the first representation of evolutionary relationships among species, in the form of a
The identifiability of tree topology for phylogenetic models, including covarion and mixture models
, 2005
"... For a model of molecular evolution to be useful for phylogenetic inference, the topology of evolutionary trees must be identifiable. That is, from a joint distribution the model predicts, it must be possible to recover the tree parameter. We establish tree identifiability for a number of phylogene ..."
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Cited by 42 (12 self)
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For a model of molecular evolution to be useful for phylogenetic inference, the topology of evolutionary trees must be identifiable. That is, from a joint distribution the model predicts, it must be possible to recover the tree parameter. We establish tree identifiability for a number of phylogenetic models, including a covarion model and a variety of mixture models with a limited number of classes. The proof is based on the introduction of a more general model, allowing more states at internal nodes of the tree than at leaves, and the study of the algebraic variety formed by the joint distributions to which it gives rise. Tree identifiability is first established for this general model through the use of certain phylogenetic invariants.
A site and timeheterogeneous model of aminoacid replacement
, 2007
"... 1 We combined the CAT mixture model (Lartillot and Philippe 2004) and the nonstationary BP model (Blanquart and Lartillot 2006) into a new model, CATBP, accounting for variations of the evolutionary process both along the sequence and across lineages. As in CAT, the model implements a mixture of d ..."
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Cited by 42 (6 self)
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1 We combined the CAT mixture model (Lartillot and Philippe 2004) and the nonstationary BP model (Blanquart and Lartillot 2006) into a new model, CATBP, accounting for variations of the evolutionary process both along the sequence and across lineages. As in CAT, the model implements a mixture of distinct Markovian processes of substitution distributed among sites, thus accommodating sitespecific selective constraints induced by protein structure and function. Furthermore, as in BP, these processes are nonstationary, and their equilibrium frequencies are allowed to change along lineages in a correlated way, through discrete shifts in global amino acid composition distributed along the phylogenetic tree. We implemented the CATBP model in a Bayesian Markov Chain Monte Carlo framework, and compared its predictions with those of three simpler models, BP, CAT, and the site and timehomogeneous GTR model, on a concatenation of four mitochondrial proteins of 20 arthropod species. In contrast to GTR, BP and CAT, which all display a phylogenetic reconstruction artefact positioning the bees Apis m. and Melipona b. among chelicerates, the CATBP model
Detecting individual sites subject to episodic diversifying selection. PLoS Genet 8(7): e1002764
, 2012
"... The imprint of natural selection on protein coding genes is often difficult to identify because selection is frequently transient or episodic, i.e. it affects only a subset of lineages. Existing computational techniques, which are designed to identify sites subject to pervasive selection, may fail t ..."
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Cited by 39 (1 self)
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The imprint of natural selection on protein coding genes is often difficult to identify because selection is frequently transient or episodic, i.e. it affects only a subset of lineages. Existing computational techniques, which are designed to identify sites subject to pervasive selection, may fail to recognize sites where selection is episodic: a large proportion of positively selected sites. We present a mixed effects model of evolution (MEME) that is capable of identifying instances of both episodic and pervasive positive selection at the level of an individual site. Using empirical and simulated data, we demonstrate the superior performance of MEME over older models under a broad range of scenarios. We find that episodic selection is widespread and conclude that the number of sites experiencing positive selection may have been vastly underestimated.
Exploring amongsite 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
, 2001
"... Abstract.—We have investigated the effects of different amongsite rate variation models on the estimation of substitution model parameters, branch lengths, topology, and bootstrap proportions under minimum evolution (ME) and maximum likelihood (ML). Speci�cally, we examined equal rates, invariable ..."
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Cited by 36 (4 self)
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Abstract.—We have investigated the effects of different amongsite rate variation models on the estimation of substitution model parameters, branch lengths, topology, and bootstrap proportions under minimum evolution (ME) and maximum likelihood (ML). Speci�cally, we examined equal rates, invariable sites, gammadistributed rates, and sitespeci�c rates (SSR) models, using mitochondrial DNA sequence data from three proteincoding genes and one tRNA gene from species of the New Zealand cicada genus Maoricicada. Estimates of topology were relatively insensitive to the substitution model used; however, estimates of bootstrap support, branch lengths, and Rmatrices (underlying relative substitution rate matrix) were strongly in�uenced by the assumptions of the substitution model. We identi�ed one situation where ME and ML tree building became inaccurate when implemented with an inappropriate amongsite rate variation model. Despite the fact the SSR models often have a better �t to the data than do invariable sites and gamma rates models, SSR models have some serious weaknesses. First, SSR rate parameters are not comparable across data sets, unlike the proportion of invariable sites or the alpha shape parameter of the gamma distribution. Second, the extreme amongsite rate variation within codon positions is problematic for SSR models, which explicitly assume rate homogeneity within each rate class. Third, the SSR models appear to give severe underestimates of
Stochastic mapping of morphological characters
 Syst. Biol
, 2003
"... Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at. ..."
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Cited by 36 (3 self)
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Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at.
Accurate branch length estimation in partitioned Bayesian analyses requires accommodation of amongpartition rate variation and attention to branch length priors. Syst Biol
, 2006
"... Molecular phylogenetic studies are making increasing use of partitioned Bayesian analyses via software tools like MrBayes, version 3 (Ronquist and Huelsenbeck, 2003). Data partitioning is important because, as long as the same topology/history underlies all of the partitions, it addresses some of t ..."
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Cited by 33 (0 self)
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Molecular phylogenetic studies are making increasing use of partitioned Bayesian analyses via software tools like MrBayes, version 3 (Ronquist and Huelsenbeck, 2003). Data partitioning is important because, as long as the same topology/history underlies all of the partitions, it addresses some of the problems associated with the combination of data sets with heterogeneous rates (Bull et al., 1993) and eliminates the need to argue the validity of tests that have been used to judge data combinability (e.g., Huelsenbeck et al., 1994; Huelsenbeck
Bootstrapping phylogenetic trees: theory and methods
 Statist. Sci
, 2003
"... Abstract. This is a survey of the use of the bootstrap in the area of systematic and evolutionary biology. I present the current usage by biologists of the bootstrap as a tool both for making inferences and for evaluating robustness, and propose a framework for thinking about these problems in terms ..."
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Cited by 26 (3 self)
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Abstract. This is a survey of the use of the bootstrap in the area of systematic and evolutionary biology. I present the current usage by biologists of the bootstrap as a tool both for making inferences and for evaluating robustness, and propose a framework for thinking about these problems in terms of mathematical statistics. Key words and phrases: Bootstrap, phylogenetic trees, confidence regions, nonpositive curvature. 1. AN INTRODUCTION TO SYSTEMATICS The objects of study in systematics are binary rooted semilabeled trees that link species or families by their coancestral relationships. For example, Figure 1 shows a tree with seven strains of HIV.