Phylodynamic Model Adequacy Using Posterior Predictive Simulations. (25th June 2018)

• Record Type: Journal Article
• Authors: Duchene, Sebastian; Bouckaert, Remco; Duchene, David A; Stadler, Tanja; Drummond, Alexei J
• Editors: Townsend, Jeffry
• Is Part Of: Systematic biology. Volume 68:Number 2(2019)
• Page Start: 358
• Page End: 364
• Publication Date: 2018-06-25
• Subjects: Bayesian phylogenetics -- BEAST2 -- model adequacy -- phylodynamics -- posterior predictive simulation -- viral evolution; Biology -- Classification -- Periodicals; Biology -- Periodicals; Biologie -- Classification -- Périodiques; Biologie -- Périodiques; 578.012
• DOI: 10.1093/sysbio/syy048
• Languages: English
• ISSNs: 1063-5157

Abstract

Abstract: Rapidly evolving pathogens, such as viruses and bacteria, accumulate genetic change at a similar timescale over which their epidemiological processes occur, such that, it is possible to make inferences about their infectious spread using phylogenetic time-trees. For this purpose it is necessary to choose a phylodynamic model. However, the resulting inferences are contingent on whether the model adequately describes key features of the data. Model adequacy methods allow formal rejection of a model if it cannot generate the main features of the data. We present TreeModelAdequacy, a package for the popular BEAST2 software that allows assessing the adequacy of phylodynamic models. We illustrate its utility by analyzing phylogenetic trees from two viral outbreaks of Ebola and H1N1 influenza. The main features of the Ebola data were adequately described by the coalescent exponential-growth model, whereas the H1N1 influenza data were best described by the birth–death susceptible-infected-recovered model.