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Estimating effective population size changes from preferentially sampled genetic sequences

Coalescent theory combined with statistical modeling allows us to estimate effective population size fluctuations from molecular sequences of individuals sampled from a population of interest. When sequences are sampled serially through time and the distribution of the sampling times depends on the...

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Detalles Bibliográficos
Autores principales: Karcher, Michael D., Carvalho, Luiz Max, Suchard, Marc A., Dudas, Gytis, Minin, Vladimir N.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7580988/
https://www.ncbi.nlm.nih.gov/pubmed/33044955
http://dx.doi.org/10.1371/journal.pcbi.1007774
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author Karcher, Michael D.
Carvalho, Luiz Max
Suchard, Marc A.
Dudas, Gytis
Minin, Vladimir N.
author_facet Karcher, Michael D.
Carvalho, Luiz Max
Suchard, Marc A.
Dudas, Gytis
Minin, Vladimir N.
author_sort Karcher, Michael D.
collection PubMed
description Coalescent theory combined with statistical modeling allows us to estimate effective population size fluctuations from molecular sequences of individuals sampled from a population of interest. When sequences are sampled serially through time and the distribution of the sampling times depends on the effective population size, explicit statistical modeling of sampling times improves population size estimation. Previous work assumed that the genealogy relating sampled sequences is known and modeled sampling times as an inhomogeneous Poisson process with log-intensity equal to a linear function of the log-transformed effective population size. We improve this approach in two ways. First, we extend the method to allow for joint Bayesian estimation of the genealogy, effective population size trajectory, and other model parameters. Next, we improve the sampling time model by incorporating additional sources of information in the form of time-varying covariates. We validate our new modeling framework using a simulation study and apply our new methodology to analyses of population dynamics of seasonal influenza and to the recent Ebola virus outbreak in West Africa.
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spelling pubmed-75809882020-10-27 Estimating effective population size changes from preferentially sampled genetic sequences Karcher, Michael D. Carvalho, Luiz Max Suchard, Marc A. Dudas, Gytis Minin, Vladimir N. PLoS Comput Biol Research Article Coalescent theory combined with statistical modeling allows us to estimate effective population size fluctuations from molecular sequences of individuals sampled from a population of interest. When sequences are sampled serially through time and the distribution of the sampling times depends on the effective population size, explicit statistical modeling of sampling times improves population size estimation. Previous work assumed that the genealogy relating sampled sequences is known and modeled sampling times as an inhomogeneous Poisson process with log-intensity equal to a linear function of the log-transformed effective population size. We improve this approach in two ways. First, we extend the method to allow for joint Bayesian estimation of the genealogy, effective population size trajectory, and other model parameters. Next, we improve the sampling time model by incorporating additional sources of information in the form of time-varying covariates. We validate our new modeling framework using a simulation study and apply our new methodology to analyses of population dynamics of seasonal influenza and to the recent Ebola virus outbreak in West Africa. Public Library of Science 2020-10-12 /pmc/articles/PMC7580988/ /pubmed/33044955 http://dx.doi.org/10.1371/journal.pcbi.1007774 Text en © 2020 Karcher et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Karcher, Michael D.
Carvalho, Luiz Max
Suchard, Marc A.
Dudas, Gytis
Minin, Vladimir N.
Estimating effective population size changes from preferentially sampled genetic sequences
title Estimating effective population size changes from preferentially sampled genetic sequences
title_full Estimating effective population size changes from preferentially sampled genetic sequences
title_fullStr Estimating effective population size changes from preferentially sampled genetic sequences
title_full_unstemmed Estimating effective population size changes from preferentially sampled genetic sequences
title_short Estimating effective population size changes from preferentially sampled genetic sequences
title_sort estimating effective population size changes from preferentially sampled genetic sequences
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7580988/
https://www.ncbi.nlm.nih.gov/pubmed/33044955
http://dx.doi.org/10.1371/journal.pcbi.1007774
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