EmpPrior: using outside empirical data to inform branch-length priors for Bayesian phylogenetics.

Background: Branch-length parameters are a central component of phylogenetic models and of intrinsic biological interest. Default branch-length priors in some Bayesian phylogenetic software can be unintentionally informative and lead to branch- and tree-length estimates that are unreasonable. Alternatively, priors may be uninformative, but lead to diffuse posterior estimates.

Deflating trees: improving Bayesian branch-length estimates using informed priors.

Prior distributions can have a strong effect on the results of Bayesian analyses. However, no general consensus exists for how priors should be set in all circumstances. Branch-length priors are of particular interest for phylogenetics, because they affect many parameters and biologically relevant inferences have been shown to be sensitive to the chosen prior distribution.

Untangling the influences of unmodeled evolutionary processes on phylogenetic signal in a forensically important HIV-1 transmission cluster.

Stochastic models of sequence evolution have been developed to reflect many biologically important processes, allowing for accurate phylogenetic reconstruction when an appropriate model is selected. However, commonly used models do not incorporate several potentially important biological processes. Spurious phylogenetic inference may result if these processes play an important role in the evolution of a dataset yet are not incorporated into assumed models.

Populations at risk: conservation genetics of kangaroo mice (Microdipodops) of the Great Basin Desert.

The Great Basin Desert of western North America has experienced frequent habitat alterations due to a complex biogeographic history and recent anthropogenic impacts, with the more recent alterations likely resulting in the decline of native fauna and flora. Dark (Microdipodops megacephalus) and pallid (M. pallidus) kangaroo mice are ecological specialists found within the Great Basin Desert and are potentially ideal organisms for assessing ecosystem health and inferring the biogeographic history of this vulnerable region.