Online Bayesian Phylodynamic Inference in BEAST with Application to Epidemic Reconstruction.

ABSTRACT: Reconstructing pathogen dynamics from genetic data as they become available during an outbreak or epidemic represents an important statistical scenario in which observations arrive sequentially in time and one is interested in performing inference in an "online" fashion. Widely used Bayesian phylogenetic inference packages are not set up for this purpose, generally requiring one to recompute trees and evolutionary model parameters de novo when new data arrive. To accommodate increasing data flow in a Bayesian phylogenetic framework, we introduce a methodology to efficiently update the posterior distribution with newly available genetic data. Our procedure is implemented in the BEAST 1.10 software package, and relies on a distance-based measure to insert new taxa into the current estimate o

SUBMITTER: Gill MS 

PROVIDER: S-EPMC7253210 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature