An integrated framework for the inference of viral population history from reconstructed genealogies.
We describe a unified set of methods for the inference of demographic history using genealogies reconstructed from gene sequence data. We introduce the skyline plot, a graphical, nonparametric estimate of demographic history. We discuss both maximum-likelihood parameter estimation and demographic hypothesis testing. Simulations are carried out to investigate the statistical properties of maximum-likelihood estimates of demographic parameters. The simulations reveal that (i) the performance of exponential growth model estimates is determined by a simple function of the true parameter values and (ii) under some conditions, estimates from reconstructed trees perform as well as estimates from perfect trees. We apply our methods to HIV-1 sequence data and find strong evidence that subtypes A and B have different demographic histories. We also provide the first (albeit tentative) genetic evidence for a recent decrease in the growth rate of subtype B.
Pybus
O G
OG
Department of Zoology, University of Oxford, Oxford OX1 3PS, United Kingdom. oliver.pybus@zoo.ox.ac.uk
Rambaut
A
A
Harvey
P H
PH
D017954:Africa South of the Sahara / Q000453:epidemiology; D003198:Computer Simulation; D004196:Disease Outbreaks / Q000145:classification / Q000706:statistics & numerical data; D005060:Europe / Q000453:epidemiology; D015752:Genes, env / Q000235:genetics; D015750:Genes, gag / Q000235:genetics; D014644:Genetic Variation; D005828:Genetics, Population; D015658:HIV Infections / Q000453:epidemiology / Q000235:genetics / Q000635:transmission; D015497:HIV-1 / Q000235:genetics*; D006801:Humans; D016013:Likelihood Functions; D016015:Logistic Models; D008957:Models, Genetic; D010375:Pedigree; D010802:Phylogeny; D011237:Predictive Value of Tests; D016008:Statistical Distributions