Long-branch attraction bias and inconsistency in Bayesian phylogenetics.

ABSTRACT: Bayesian inference (BI) of phylogenetic relationships uses the same probabilistic models of evolution as its precursor maximum likelihood (ML), so BI has generally been assumed to share ML's desirable statistical properties, such as largely unbiased inference of topology given an accurate model and increasingly reliable inferences as the amount of data increases. Here we show that BI, unlike ML, is biased in favor of topologies that group long branches together, even when the true model and prior distributions of evolutionary parameters over a group of phylogenies are known. Using experimental simulation studies and numerical and mathematical analyses, we show that this bias becomes more severe as more data are analyzed, causing BI to infer an incorrect tree as the maximum a posteriori phy

SUBMITTER: Kolaczkowski B 

PROVIDER: S-EPMC2785476 | biostudies-literature | 2009 Dec

REPOSITORIES: biostudies-literature