PrioriTree: a utility for improving phylodynamic analyses in BEAST

Abstract

SummaryPhylodynamic 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 ImplementationPrioriTree 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/. Contactjsigao@ucdavis.edu