title: Correlating viral phenotypes with phylogeny: accounting for phylogenetic uncertainty.
abstract: Many recent studies have sought to quantify the degree to which viral phenotypic characters (such as epidemiological risk group, geographic location, cell tropism, drug resistance state, etc.) are correlated with shared ancestry, as represented by a viral phylogenetic tree. Here, we present a new Bayesian Markov-Chain Monte Carlo approach to the investigation of such phylogeny-trait correlations. This method accounts for uncertainty arising from phylogenetic error and provides a statistical significance test of the null hypothesis that traits are associated randomly with phylogeny tips. We perform extensive simulations to explore and compare the behaviour of three statistics of phylogeny-trait correlation. Finally, we re-analyse two existing published data sets as case studies. Our framework aims to provide an improvement over existing methods for this problem.
authors.affiliation: Department of Zoology, University of Oxford, South Parks Road, Oxford OX1 3PS, United Kingdom. joe.parker@zoo.ox.ac.uk
authors.forename: Joe
authors.initials: J
authors.lastname: Parker
authors.forename: Andrew
authors.initials: A
authors.lastname: Rambaut
authors.forename: Oliver G
authors.initials: OG
authors.lastname: Pybus
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D036262:Empirical Research; D010641:Phenotype; D010802:Phylogeny; D035501:Uncertainty; D018406:Virus Physiological Phenomena; D014780:Viruses / Q000235:genetics*