Improving Bayesian Population Dynamics Inference: A Coalescent-Based Model for Multiple Loci

Effective population size is fundamental in population genetics and characterizes genetic diversity. To infer past population dynamics from molecular sequence data, coalescent-based models have been developed for Bayesian nonparametric estimation of effective population size over time. Among the most successful is a Gaussian Markov random field (GMRF) model for a single gene locus. Here, we present a generalization of the GMRF model that allows for the analysis of multilocus sequence data. Using simulated data, we demonstrate the improved performance of our method to recover true population trajectories and the time to the most recent common ancestor (TMRCA). We analyze a multilocus alignment of HIV-1 CRF02_AG…

• NE
  National Evolutionary Synthesis Center
• EC
  European Commission

  Awards: 278433, 260864, 278433-PREDEMICS, 2007-2013