Efficient Bayesian species tree inference under the multi-species coalescent
A method was developed for Bayesian inference of species phylogeny using the multi-species coalescent model. To improve the mixing properties of the Markov chain Monte Carlo (MCMC) algorithm that traverses the space of species trees, we implement two efficient MCMC proposals: the first is based on the Subtree Pruning and Regrafting (SPR) algorithm and the second is based on a novel node-slider algorithm. Like the Nearest-Neighbor Interchange (NNI) algorithm we implemented previously, both algorithms propose changes to the species tree, while simultaneously altering the gene trees at multiple genetic loci to automatically avoid conflicts with the newly-proposed species tree. The method integrates over gene trees, naturally taking account of the uncertainty of gene tree topology and branch lengths given the sequence data. A simulation study was performed to examine the statistical properties of the new method. We found that it has excellent statistical performance, inferring the correct species tree with near certainty when analyzing 10 loci. The prior on species trees has some impact, particularly for small numbers of loci. An empirical dataset (for rattlesnakes) was reanalyzed. While the 18 nuclear loci and one mitochondrial locus support largely consistent species trees under the multi-species coalescent model estimates of parameters suggest drastically different evolutionary dynamics between the nuclear and mitochondrial loci.
Code (0)
등록된 구현이 없습니다.
Tasks
Bayesian InferenceSimilar Papers 제목 키워드 기반
Split probabilities and species tree inference under the multispecies coalescent model
Using topological summaries of gene trees as a basis for species tree inference is a promising approach to obtain acceptable speed on genomic-scale datasets, and to avoid some undesirable modeling assumptions. Here we st…
Bayesian inference of species trees using diffusion models
We describe a new and computationally efficient Bayesian methodology for inferring species trees and demographics from unlinked binary markers. Likelihood calculations are carried out using diffusion models of allele fre…
Bayesian InferenceThe Tree of Blobs of a Species Network: Identifiability under the Coalescent
Inference of species networks from genomic data under the Network Multispecies Coalescent Model is currently severely limited by heavy computational demands. It also remains unclear how complicated networks can be for co…
Species tree inference from genomic sequences using the log-det distance
The log-det distance between two aligned DNA sequences was introduced as a tool for statistically consistent inference of a gene tree under simple non-mixture models of sequence evolution. Here we prove that the log-det …
There are no caterpillars in a wicked forest
Species trees represent the historical divergences of populations or species, while gene trees trace the ancestry of individual gene copies sampled within those populations. In cases involving rapid speciation, gene tree…