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Estimating the probability of continuous character transitions on trees
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| PI(s): |
Andrew L. Hipp (The Morton Arboretum) |
| Start Date: |
22-Feb-2008 |
| End Date: |
27-Mar-2008 |
| Keywords: |
phylogenetics, comparative methods, computational modeling |
Estimating the evolutionary history of species traits is a basic problem in evolutionary biology and an issue of practical concern for ecologists, developmental biologists, and others testing biological hypotheses using phylogenetic data. This project adapts and evaluates a Bayesian method of association mapping to the problem of estimating when in phylogenetic time evolutionary shifts in quantitative traits occurred. Existing phylogenetic comparative methods are well-suited to estimating trait values of putative ancestors, testing specific evolutionary hypotheses, and mapping transitions in discrete traits. The method to be developed will directly estimate the probability and magnitude of quantitative trait change on all branches of a phylogeny simultaneously under explicitly formulated evolutionary models.
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- AUTHORS: Hipp, Andrew L. and Alexander Platt
DATE: Monday, July 28th, 2008
TITLE: Estimating the probability of continuous character transitions on phylogenetic trees
MEETING: Botany 2008
LOCATION: UBC, Vancouver
ABSTRACT:
Inferring the evolutionary history of species traits is a basic problem in evolutionary biology and an issue of practical concern for ecologists, developmental biologists, and others testing biological hypotheses using phylogenetic data. Methods of analyzing categorical data in a phylogenetic context have addressed the problem of localizing character transitions to branches. Locating transitions in continuous characters have received less focus, in part because many methods are based on a constant variance (Brownian motion) model, in which the rate of character evolution is modeled as shifting gradually on the tree if at all. Evaluation of Ornstein-Uhlenbeck models that allow shifts in character equilibria or Brownian motion models on subtrees are straightforward methods of modeling transitions in continuous characters. Assessed in an information theoretic framework, these models are useful means of estimating the probability that continuous trait change on a selected phylogenetic branch violates the expectations of a constant variance model. We contrast these methods with a Bayesian association mapping method that directly estimates the probability and magnitude of quantitative trait change on all branches of a phylogeny. In combination, these techniques provide a useful complement to existing methods for investigating the evolution of continuous characters.
