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The multifurcating skyline plot

A variety of methods based on coalescent theory have been developed to infer demographic history from gene sequences sampled from natural populations. The ‘skyline plot’ and related approaches are commonly employed as flexible prior distributions for phylogenetic trees in the Bayesian analysis of pa...

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Detalles Bibliográficos
Autores principales: Hoscheit, Patrick, Pybus, Oliver G
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6736156/
https://www.ncbi.nlm.nih.gov/pubmed/31528357
http://dx.doi.org/10.1093/ve/vez031
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author Hoscheit, Patrick
Pybus, Oliver G
author_facet Hoscheit, Patrick
Pybus, Oliver G
author_sort Hoscheit, Patrick
collection PubMed
description A variety of methods based on coalescent theory have been developed to infer demographic history from gene sequences sampled from natural populations. The ‘skyline plot’ and related approaches are commonly employed as flexible prior distributions for phylogenetic trees in the Bayesian analysis of pathogen gene sequences. In this work we extend the classic and generalized skyline plot methods to phylogenies that contain one or more multifurcations (i.e. hard polytomies). We use the theory of Λ-coalescents (specifically, [Formula: see text]-coalescents) to develop the ‘multifurcating skyline plot’, which estimates a piecewise constant function of effective population size through time, conditional on a time-scaled multifurcating phylogeny. We implement a smoothing procedure and extend the method to serially sampled (heterochronous) data, but we do not address here the problem of estimating trees with multifurcations from gene sequence alignments. We validate our estimator on simulated data using maximum likelihood and find that parameters of the [Formula: see text] -coalescent process can be estimated accurately. Furthermore, we apply the multifurcating skyline plot to simulated trees generated by tracking transmissions in an individual-based model of epidemic superspreading. We find that high levels of superspreading are consistent with the high-variance assumptions underlying Λ-coalescents and that the estimated parameters of the Λ-coalescent model contain information about the degree of superspreading.
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spelling pubmed-67361562019-09-16 The multifurcating skyline plot Hoscheit, Patrick Pybus, Oliver G Virus Evol Research Article A variety of methods based on coalescent theory have been developed to infer demographic history from gene sequences sampled from natural populations. The ‘skyline plot’ and related approaches are commonly employed as flexible prior distributions for phylogenetic trees in the Bayesian analysis of pathogen gene sequences. In this work we extend the classic and generalized skyline plot methods to phylogenies that contain one or more multifurcations (i.e. hard polytomies). We use the theory of Λ-coalescents (specifically, [Formula: see text]-coalescents) to develop the ‘multifurcating skyline plot’, which estimates a piecewise constant function of effective population size through time, conditional on a time-scaled multifurcating phylogeny. We implement a smoothing procedure and extend the method to serially sampled (heterochronous) data, but we do not address here the problem of estimating trees with multifurcations from gene sequence alignments. We validate our estimator on simulated data using maximum likelihood and find that parameters of the [Formula: see text] -coalescent process can be estimated accurately. Furthermore, we apply the multifurcating skyline plot to simulated trees generated by tracking transmissions in an individual-based model of epidemic superspreading. We find that high levels of superspreading are consistent with the high-variance assumptions underlying Λ-coalescents and that the estimated parameters of the Λ-coalescent model contain information about the degree of superspreading. Oxford University Press 2019-08-29 /pmc/articles/PMC6736156/ /pubmed/31528357 http://dx.doi.org/10.1093/ve/vez031 Text en © The Author(s) 2019. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Research Article
Hoscheit, Patrick
Pybus, Oliver G
The multifurcating skyline plot
title The multifurcating skyline plot
title_full The multifurcating skyline plot
title_fullStr The multifurcating skyline plot
title_full_unstemmed The multifurcating skyline plot
title_short The multifurcating skyline plot
title_sort multifurcating skyline plot
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6736156/
https://www.ncbi.nlm.nih.gov/pubmed/31528357
http://dx.doi.org/10.1093/ve/vez031
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