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.
Description
An Integrated Framework for the Inference of Viral Population History From Reconstructed Genealogies -- Pybus et al. 155 (3): 1429 -- Genetics
%0 Journal Article
%1 OliverG._Pybus07012000
%A Pybus, Oliver G.
%A Rambaut, Andrew
%A Harvey, Paul H.
%D 2000
%J Genetics
%K phylogenetics viruses
%N 3
%P 1429-1437
%T An Integrated Framework for the Inference of Viral Population History From Reconstructed Genealogies
%U http://www.genetics.org/cgi/content/abstract/155/3/1429
%V 155
%X 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.
@article{OliverG._Pybus07012000,
abstract = {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.
},
added-at = {2008-07-10T23:03:58.000+0200},
author = {Pybus, Oliver G. and Rambaut, Andrew and Harvey, Paul H.},
biburl = {https://www.bibsonomy.org/bibtex/27ea112761a3b2db1e9de39d8ea166f22/peter.ralph},
description = {An Integrated Framework for the Inference of Viral Population History From Reconstructed Genealogies -- Pybus et al. 155 (3): 1429 -- Genetics},
eprint = {http://www.genetics.org/cgi/reprint/155/3/1429.pdf},
interhash = {62eaed361229e8358b9dbc9e4017bdef},
intrahash = {7ea112761a3b2db1e9de39d8ea166f22},
journal = {Genetics},
keywords = {phylogenetics viruses},
number = 3,
pages = {1429-1437},
timestamp = {2008-07-10T23:03:59.000+0200},
title = {{An Integrated Framework for the Inference of Viral Population History From Reconstructed Genealogies}},
url = {http://www.genetics.org/cgi/content/abstract/155/3/1429},
volume = 155,
year = 2000
}