Rebecca Thiem

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  Integrating Different Data Types in Estimating Phylogenies
  Brandon Cannone, Rebecca Thiem

  Traditionally, behavioral and morphological data have been analyzed with Maximum Parsimony to estimate evolutionary histories by finding the fewest number of required changes in a tree connecting related species. In recent years, Bayesian estimation of molecular phylogenies has been heavily researched, but researchers typically assume a prior distribution that all phylogenies are equally likely. In this project, we integrate these schools of thought and data types by informing the prior distribution with the parsimony scores of the trees with respect to morphology and behavior. We implement this method on sample datasets of corbiculate bees and orb-weaver spiders.