tetano
Editor, Senior Moderator
Bioinformatics. 2014 Apr 20. [Epub ahead of print]
Efficient Bayesian inference under the structured coalescent.
Vaughan TG1, K?hnert D, Popinga A, Welch D, Drummond AJ.
Author information
Abstract
MOTIVATION:
Population structure significantly affects evolutionary dynamics. Such structure may be due to spatial segregation, but may also reflect any other gene-flow-limiting aspect of a model. In combination with the structured coalescent, this fact can be used to inform phylogenetic tree reconstruction, as well as to infer parameters such as migration rates and sub-population sizes from annotated sequence data. However, conducting Bayesian inference under the structured coalescent is impeded by the difficulty of constructing Markov Chain Monte Carlo sampling algorithms (samplers) capable of efficiently exploring the state space.
RESULTS:
In this paper, we present a new MCMC sampler capable of sampling from posterior distributions over structured trees: timed phylogenetic trees in which lineages are associated with the distinct sub-population in which they lie. The sampler includes a set of MCMC proposal functions which offer significant mixing improvements over a previously published method. Furthermore, its implementation as a BEAST 2 package ensures maximum flexibility with respect to model and prior specification. We demonstrate the usefulness of this new sampler by using it to infer migration rates and effective population sizes of H3N2 influenza between New Zealand, New York and Hong Kong from publicly-available HA sequences under the structured coalescent.
AVAILABILITY:
The sampler has been implemented as a publicly-available BEAST 2 package which is distributed under version 3 of the GNU General Public License (GPL) at http://compevol.github.io/MultiTypeTree.
CONTACT:
tgvaughan@gmail.com.
PMID:
24753484
[PubMed - as supplied by publisher]
http://www.ncbi.nlm.nih.gov/pubmed/24753484
Efficient Bayesian inference under the structured coalescent.
Vaughan TG1, K?hnert D, Popinga A, Welch D, Drummond AJ.
Author information
Abstract
MOTIVATION:
Population structure significantly affects evolutionary dynamics. Such structure may be due to spatial segregation, but may also reflect any other gene-flow-limiting aspect of a model. In combination with the structured coalescent, this fact can be used to inform phylogenetic tree reconstruction, as well as to infer parameters such as migration rates and sub-population sizes from annotated sequence data. However, conducting Bayesian inference under the structured coalescent is impeded by the difficulty of constructing Markov Chain Monte Carlo sampling algorithms (samplers) capable of efficiently exploring the state space.
RESULTS:
In this paper, we present a new MCMC sampler capable of sampling from posterior distributions over structured trees: timed phylogenetic trees in which lineages are associated with the distinct sub-population in which they lie. The sampler includes a set of MCMC proposal functions which offer significant mixing improvements over a previously published method. Furthermore, its implementation as a BEAST 2 package ensures maximum flexibility with respect to model and prior specification. We demonstrate the usefulness of this new sampler by using it to infer migration rates and effective population sizes of H3N2 influenza between New Zealand, New York and Hong Kong from publicly-available HA sequences under the structured coalescent.
AVAILABILITY:
The sampler has been implemented as a publicly-available BEAST 2 package which is distributed under version 3 of the GNU General Public License (GPL) at http://compevol.github.io/MultiTypeTree.
CONTACT:
tgvaughan@gmail.com.
PMID:
24753484
[PubMed - as supplied by publisher]
http://www.ncbi.nlm.nih.gov/pubmed/24753484