SVDquartets

David Swofford
Duke University

Laura Kubatko
The Ohio State University

Increasing attention has been devoted to the estimation of species-level phylogenetic relationships under the multispecies 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 MCMC algorithms that do not scale well to whole-genome datasets.

We describe SVDQuartets, a recently developed method for inferring relationships under the coalescent model using techniques from algebraic statistics. The method operates on quartets of taxa, then assembles the quartet information into a full tree via quartet amalgamation algorithms. Uncertainty in the estimated relationships is quantified using the nonparametric bootstrap. The method has high accuracy in simulation studies; we also describe results from empirical examples where it seems to perform well.

SVDQuartets is currently implemented as a module in the PAUP* program.