Accounting for Recombination in Infectious Disease Phylodynamics

• Activity Number: 493
• Type: Topic Contributed
• Date/Time: Wednesday, August 6, 2014 : 10:30 AM to 12:20 PM
• Sponsor: Section on Statistics in Epidemiology
• Author(s): Julia Palacios*+ and Sohini Ramachandran and John Wakeley
• Companies: Harvard and Brown University and Harvard
• Keywords: phylodynamics ; Bayesian nonparametric ; Gaussian Processes ; state space models

Abstract

Phylodynamic methods aim to reconstruct past trajectories of population size from genetic variation present in a random sample of the population, and sometimes from a combination of genetic and temporal information relevant to the population of interest. New sophisticated Bayesian inferential tools for phylodynamics have emerged in the last decade. They have been applied to understand several disease dynamics such as human Influenza A virus and Hepatitis C Virus, as well as to understand other population size histories such as Berigian bisons and lizards in Central America. With the rise of new technologies for gathering genomic data, it has become easier to obtain data from multiple individuals at multiple loci and at different times. Current Bayesian phylodynamic methods however, ignore genetic recombination. Recombination is known to play an important role in genetic diversity of some DNA and RNA viruses. Here, we propose to model recombination explicitly from whole genomes. We extend current phylodynamic method to analyze data from multiple individuals at multiple loci. We test our method on simulated and real data.