Journal
BIOINFORMATICS
Volume 30, Issue 23, Pages 3317-3324Publisher
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btu530
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Funding
- National Science Foundation [DMS-1106706]
- NIH Cancer Biology Training [T32-CA079448]
- Division Of Mathematical Sciences
- Direct For Mathematical & Physical Scien [1106706] Funding Source: National Science Foundation
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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.
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