Meeting Abstract

P1.68  Monday, Jan. 4  A Bayesian approach to testing the independent origin hypothesis MININ, Vladimir N*; OAKLEY, Todd H; SUCHARD, Marc A; University of Washington, Seattle; University of California, Santa Cruz; University of California, Los Angeles vminin@u.washington.edu

Estimating the number of times a discrete evolutionary trait changed its state is one of the fundamental questions in evolutionary developmental biology. Often, researchers are interested in testing a so called independent origin hypothesis that asserts that the number of changes of a certain type exceeds a predefined threshold. Testing such a hypothesis in a formal statistical framework requires a model of trait evolution and a phylogenetic tree along which the evolutionary trait evolves. We use a fairly unrealistic, but mathematically and computationally convenient, Markov model of trait evolution, parameterized in terms of rates at which the trait changes its state. Next, we assume that the phylogenetic tree of organisms under study can be inferred using molecular data. However, such estimation remains imprecise and the resulting phylogenetic uncertainty must be accounted for when testing the independent origin hypothesis. Both, the phylogenetic tree and rates of the Markov evolutionary model are nuisance parameters for our purposes. We propose to test the independent origin hypothesis in a Bayesian framework, because the Bayesian paradigm naturally allows for integration over nuisance parameters. We demonstrate how to construct and to calculate a Bayes factor to perform the desired test. We evaluate our test via simulations and apply the developed method to study evolution of a compound eye in arthropods.