Mar 15, 2011

Estimating species trees using approximate Bayesian computation

Molecular Phylogenetics and Evolution
Helen Hang Fan, Laura S Kubatko

Abstract

Development of methods for estimating species trees from multilocus data is a current challenge in evolutionary biology. We propose a method for estimating the species tree topology and branch lengths using approximate Bayesian computation (ABC). The method takes as data a sample of observed rooted gene tree topologies, and then iterates through the following sequence of steps: First, a randomly selected species tree is used to compute the distribution of rooted gene tree topologies. This distribution is then compared to the observed gene topology frequencies, and if the fit between the observed and the predicted distributions is close enough, the proposed species tree is retained. Repeating this many times leads to a collection of retained species trees that are then used to form the estimate of the overall species tree. We test the performance of the method, which we call ST-ABC, using both simulated and empirical data. The simulation study examines both symmetric and asymmetric species trees over a range of branch lengths and sample sizes. The results from the simulation study show that the model performs very well, giving accurate estimates for both the topology and the branch lengths across the conditions studied, and that...Continue Reading

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References

Mentioned in this Paper

Saccharomyces bayanus
In Silico
Candida albicans
Genome
Saccharomyces cerevisiae allergenic extract
Yeasts
Gorilla <Eastern Gorilla>
Phylogeny
Pan troglodytes
Saccharomyces kudriavzevii

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