Dataset Information
Quartet inference from SNP data under the coalescent model.
Ontology highlight
ABSTRACT: Motivation
Increasing attention has been devoted to estimation of species-level phylogenetic relationships under the coalescent model. However, existing methods either use summary statistics (gene trees) to carry out estimation, ignoring an important source of variability in the estimates, or involve computationally intensive Bayesian Markov chain Monte Carlo algorithms that do not scale well to whole-genome datasets.Results
We develop a method to infer relationships among quartets of taxa under the coalescent model using techniques from algebraic statistics. Uncertainty in the estimated relationships is quantified using the nonparametric bootstrap. The performance of our method is assessed with simulated data. We then describe how our method could be used for species tree inference in larger taxon samples, and demonstrate its utility using datasets for Sistrurus rattlesnakes and for soybeans.Availability and implementation
The method to infer the phylogenetic relationship among quartets is implemented in the software SVDquartets, available at www.stat.osu.edu/?lkubatko/software/SVDquartets.
SUBMITTER: Chifman J
PROVIDER: S-EPMC4296144 | biostudies-literature | 2014 Dec
REPOSITORIES: biostudies-literature
Publications
Quartet inference from SNP data under the coalescent model.
Bioinformatics (Oxford, England) 20140807 23
<h4>Motivation</h4>Increasing attention has been devoted to estimation of species-level phylogenetic relationships under the coalescent model. However, existing methods either use summary statistics (gene trees) to carry out estimation, ignoring an important source of variability in the estimates, or involve computationally intensive Bayesian Markov chain Monte Carlo algorithms that do not scale well to whole-genome datasets.<h4>Results</h4>We develop a method to infer relationships among quarte ...[more]