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Laudanno, G.

Publications and source records attributed to Laudanno, G..

2 recordsLinked to original sources

Quantifying the importance of an inference model in Bayesian phylogenetics

O_LIPhylogenetic trees are currently routinely reconstructed from an alignment of character sequences (usually nucleotide sequences). Bayesian tools, such as MrBayes, RevBayes and BEAST2, have gained much popularity over the last decade, as they allow joint estimation of the posterior distribution of the phylogenetic trees and the parameters of the underlying inference model. An important ingredient of these Bayesian approaches is the species tree prior. In principle, the Bayesian framework allows for comparing different tree priors, which may elucidate the macroevolutionary processes underlying the species tree. In practice, however, only macroevolutionary models that allow for fast computation of the prior probability are used. The question is how accurate the tree estimation is when the real macroevolutionary processes are substantially different from those assumed in the tree prior. C_LIO_LIHere we present pirouette, a free and open-source R package that assesses the inference error made by Bayesian phylogenetics for a given macroevolutionary diversification model. pirouette makes use of BEAST2, but its philosophy applies to any Bayesian phylogenetic inference tool. C_LIO_LIWe describe pirouettes usage providing full examples in which we interrogate a model for its power to describe another. C_LIO_LILast, we discuss the results obtained by the examples and their interpretation. C_LI

evolutionary biology

Additional analytical support for a new method to compute the likelihood of diversification models

Molecular phylogenies have been increasingly recognized as an important source of information on species diversification. For many models of macro-evolution, analytical likelihood formulas have been derived to infer macro-evolutionary parameters from phylogenies. A few years ago, a general framework to numerically compute such likelihood formulas was proposed, which accommodates models that allow speciation and/or extinction rates to depend on diversity. This framework calculates the likelihood as the probability of the diversification process being consistent with the phylogeny from the root to the tips. However, while some readers found the framework presented in Etienne et al. (2012) convincing, others still questioned it (personal communication), despite numerical evidence that for special cases the framework yields the same (i.e. within double precision) numerical value for the likelihood as analytical formulas do that were independently derived for these special cases. Here we prove analytically that the likelihoods calculated in the new framework are correct for all special cases with known analytical likelihood formula. Our results thus add substantial mathematical support for the overall coherence of the general framework.

evolutionary biology