Cargando…
Scalable Bayesian phylogenetics
Recent advances in Bayesian phylogenetics offer substantial computational savings to accommodate increased genomic sampling that challenges traditional inference methods. In this review, we begin with a brief summary of the Bayesian phylogenetic framework, and then conceptualize a variety of methods...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9393558/ https://www.ncbi.nlm.nih.gov/pubmed/35989603 http://dx.doi.org/10.1098/rstb.2021.0242 |
_version_ | 1784771295560335360 |
---|---|
author | Fisher, Alexander A. Hassler, Gabriel W. Ji, Xiang Baele, Guy Suchard, Marc A. Lemey, Philippe |
author_facet | Fisher, Alexander A. Hassler, Gabriel W. Ji, Xiang Baele, Guy Suchard, Marc A. Lemey, Philippe |
author_sort | Fisher, Alexander A. |
collection | PubMed |
description | Recent advances in Bayesian phylogenetics offer substantial computational savings to accommodate increased genomic sampling that challenges traditional inference methods. In this review, we begin with a brief summary of the Bayesian phylogenetic framework, and then conceptualize a variety of methods to improve posterior approximations via Markov chain Monte Carlo (MCMC) sampling. Specifically, we discuss methods to improve the speed of likelihood calculations, reduce MCMC burn-in, and generate better MCMC proposals. We apply several of these techniques to study the evolution of HIV virulence along a 1536-tip phylogeny and estimate the internal node heights of a 1000-tip SARS-CoV-2 phylogenetic tree in order to illustrate the speed-up of such analyses using current state-of-the-art approaches. We conclude our review with a discussion of promising alternatives to MCMC that approximate the phylogenetic posterior. This article is part of a discussion meeting issue ‘Genomic population structures of microbial pathogens’. |
format | Online Article Text |
id | pubmed-9393558 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | The Royal Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-93935582022-08-30 Scalable Bayesian phylogenetics Fisher, Alexander A. Hassler, Gabriel W. Ji, Xiang Baele, Guy Suchard, Marc A. Lemey, Philippe Philos Trans R Soc Lond B Biol Sci Articles Recent advances in Bayesian phylogenetics offer substantial computational savings to accommodate increased genomic sampling that challenges traditional inference methods. In this review, we begin with a brief summary of the Bayesian phylogenetic framework, and then conceptualize a variety of methods to improve posterior approximations via Markov chain Monte Carlo (MCMC) sampling. Specifically, we discuss methods to improve the speed of likelihood calculations, reduce MCMC burn-in, and generate better MCMC proposals. We apply several of these techniques to study the evolution of HIV virulence along a 1536-tip phylogeny and estimate the internal node heights of a 1000-tip SARS-CoV-2 phylogenetic tree in order to illustrate the speed-up of such analyses using current state-of-the-art approaches. We conclude our review with a discussion of promising alternatives to MCMC that approximate the phylogenetic posterior. This article is part of a discussion meeting issue ‘Genomic population structures of microbial pathogens’. The Royal Society 2022-10-10 2022-08-22 /pmc/articles/PMC9393558/ /pubmed/35989603 http://dx.doi.org/10.1098/rstb.2021.0242 Text en © 2022 The Authors. https://creativecommons.org/licenses/by/4.0/Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, provided the original author and source are credited. |
spellingShingle | Articles Fisher, Alexander A. Hassler, Gabriel W. Ji, Xiang Baele, Guy Suchard, Marc A. Lemey, Philippe Scalable Bayesian phylogenetics |
title | Scalable Bayesian phylogenetics |
title_full | Scalable Bayesian phylogenetics |
title_fullStr | Scalable Bayesian phylogenetics |
title_full_unstemmed | Scalable Bayesian phylogenetics |
title_short | Scalable Bayesian phylogenetics |
title_sort | scalable bayesian phylogenetics |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9393558/ https://www.ncbi.nlm.nih.gov/pubmed/35989603 http://dx.doi.org/10.1098/rstb.2021.0242 |
work_keys_str_mv | AT fisheralexandera scalablebayesianphylogenetics AT hasslergabrielw scalablebayesianphylogenetics AT jixiang scalablebayesianphylogenetics AT baeleguy scalablebayesianphylogenetics AT suchardmarca scalablebayesianphylogenetics AT lemeyphilippe scalablebayesianphylogenetics |