SUMMARY: Phylodynamic methods are central to studies of the geographic and demographic history of disease outbreaks. Inference under discrete-geographic phylodynamic models-which involve many parameters that must be inferred from minimal information-is inherently sensitive to our prior beliefs about the model parameters. We present an interactive utility, PrioriTree, to help researchers identify and accommodate prior sensitivity in discrete-geographic inferences. Specifically, PrioriTree provides a suite of functions to generate input files for-and summarize output from-BEAST analyses for performing robust Bayesian inference, data-cloning analyses and assessing the relative and absolute fit of candidate discrete-geographic (prior) models to empirical datasets. AVAILABILITY AND IMPLEMENTATION: PrioriTree is distributed as an R package available at https://github.com/jsigao/prioritree, with a comprehensive user manual provided at https://bookdown.org/jsigao/prioritree_manual/.

SUMMARY: The program DMLE+ allows Bayesian inference of the location of a gene carrying a mutation influencing a discrete trait (such as a disease) and/or other parameters of interest (such as mutation age) based on the observed linkage disequilibrium at multiple genetic markers. DMLE+ uses either individual marker genotypes, or haplotypes, integrates over uncertain population allele frequencies, and can incorporate prior information about gene location from an annotated human genome sequence. AVAILABILITY: DMLE+ is available in both Windows GUI and portable UNIX command line versions at http://dmle.org.