title: Bayesian long branch attraction bias and corrections.
abstract: Previous work on the star-tree paradox has shown that Bayesian methods suffer from a long branch attraction bias. That work is extended to settings involving more taxa and partially resolved trees. The long branch attraction bias is confirmed to arise more broadly and an additional source of bias is found. A by-product of the analysis is methods that correct for biases toward particular topologies. The corrections can be easily calculated using existing Bayesian software. Posterior support for a set of two or more trees can thus be supplemented with corrected versions to cross-check or replace results. Simulations show the corrections to be highly effective.
authors.affiliation: Department of Mathematics and Statistics, Dalhousie University, Halifax, Nova Scotia, canada B3H, 4R2 edward.susko@gmail.com.
authors.forename: Edward
authors.initials: E
authors.lastname: Susko
mesh_terms: D001499:Bayes Theorem; D015982:Bias; D003198:Computer Simulation; D015233:Models, Statistical; D010802:Phylogeny; D012984:Software / Q000592:standards*
keywords: Bayesian methods; bias; long branch attraction; posterior probability; star tree