Data from: Understanding past population dynamics: Bayesian coalescent-based modeling with covariates

Effective population size characterizes the genetic variability in a population and is a parameter of paramount importance in population genetics and evolutionary biology. Kingman's coalescent process enables inference of past population dynamics directly from molecular sequence data, and resea...

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Main Authors: Gill, Mandev S., Lemey, Philippe, Bennett, Shannon N., Biek, Roman, Suchard, Marc A.
Format: Dataset
Language:English
Published: Dryad 2016
Subjects:
Online Access:https://dx.doi.org/10.5061/dryad.mj0hn
http://datadryad.org/stash/dataset/doi:10.5061/dryad.mj0hn
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spelling ftdatacite:10.5061/dryad.mj0hn 2023-05-15T17:13:37+02:00 Data from: Understanding past population dynamics: Bayesian coalescent-based modeling with covariates Gill, Mandev S. Lemey, Philippe Bennett, Shannon N. Biek, Roman Suchard, Marc A. 2016 https://dx.doi.org/10.5061/dryad.mj0hn http://datadryad.org/stash/dataset/doi:10.5061/dryad.mj0hn en eng Dryad https://dx.doi.org/10.1093/sysbio/syw050 Creative Commons Zero v1.0 Universal https://creativecommons.org/publicdomain/zero/1.0/legalcode cc0-1.0 CC0 population genetics Gaussian Markov Random Fields Bayesian inference Phylodynamics Evolutionary Biology FOS Biological sciences effective population size dataset Dataset 2016 ftdatacite https://doi.org/10.5061/dryad.mj0hn https://doi.org/10.1093/sysbio/syw050 2022-02-08T12:53:43Z Effective population size characterizes the genetic variability in a population and is a parameter of paramount importance in population genetics and evolutionary biology. Kingman's coalescent process enables inference of past population dynamics directly from molecular sequence data, and researchers have developed a number of flexible coalescent-based models for Bayesian nonparametric estimation of the effective population size as a function of time. Major goals of demographic reconstruction include identifying driving factors of effective population size, and understanding the association between the effective population size and such factors. Building upon Bayesian nonparametric coalescent-based approaches, we introduce a flexible framework that incorporates time-varying covariates that exploit Gaussian Markov random fields to achieve temporal smoothing of effective population size trajectories. To approximate the posterior distribution, we adapt efficient Markov chain Monte Carlo algorithms designed for highly structured Gaussian models. Incorporating covariates into the demographic inference framework enables the modeling of associations between the effective population size and covariates while accounting for uncertainty in population histories. Furthermore, it can lead to more precise estimates of population dynamics. We apply our model to four examples. We reconstruct the demographic history of raccoon rabies in North America and find a significant association with the spatiotemporal spread of the outbreak. Next, we examine the effective population size trajectory of the DENV-4 virus in Puerto Rico along with viral isolate count data and find similar cyclic patterns. We compare the population history of the HIV-1 CRF02_AG clade in Cameroon with HIV incidence and prevalence data and find that the effective population size is more reflective of incidence rate. Finally, we explore the hypothesis that the population dynamics of musk ox during the Late Quaternary period were related to climate change. : BEAST XML input files used for the data analysisSkygridXMLs.tar.gz Dataset musk ox DataCite Metadata Store (German National Library of Science and Technology)
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language English
topic population genetics
Gaussian Markov Random Fields
Bayesian inference
Phylodynamics
Evolutionary Biology
FOS Biological sciences
effective population size
spellingShingle population genetics
Gaussian Markov Random Fields
Bayesian inference
Phylodynamics
Evolutionary Biology
FOS Biological sciences
effective population size
Gill, Mandev S.
Lemey, Philippe
Bennett, Shannon N.
Biek, Roman
Suchard, Marc A.
Data from: Understanding past population dynamics: Bayesian coalescent-based modeling with covariates
topic_facet population genetics
Gaussian Markov Random Fields
Bayesian inference
Phylodynamics
Evolutionary Biology
FOS Biological sciences
effective population size
description Effective population size characterizes the genetic variability in a population and is a parameter of paramount importance in population genetics and evolutionary biology. Kingman's coalescent process enables inference of past population dynamics directly from molecular sequence data, and researchers have developed a number of flexible coalescent-based models for Bayesian nonparametric estimation of the effective population size as a function of time. Major goals of demographic reconstruction include identifying driving factors of effective population size, and understanding the association between the effective population size and such factors. Building upon Bayesian nonparametric coalescent-based approaches, we introduce a flexible framework that incorporates time-varying covariates that exploit Gaussian Markov random fields to achieve temporal smoothing of effective population size trajectories. To approximate the posterior distribution, we adapt efficient Markov chain Monte Carlo algorithms designed for highly structured Gaussian models. Incorporating covariates into the demographic inference framework enables the modeling of associations between the effective population size and covariates while accounting for uncertainty in population histories. Furthermore, it can lead to more precise estimates of population dynamics. We apply our model to four examples. We reconstruct the demographic history of raccoon rabies in North America and find a significant association with the spatiotemporal spread of the outbreak. Next, we examine the effective population size trajectory of the DENV-4 virus in Puerto Rico along with viral isolate count data and find similar cyclic patterns. We compare the population history of the HIV-1 CRF02_AG clade in Cameroon with HIV incidence and prevalence data and find that the effective population size is more reflective of incidence rate. Finally, we explore the hypothesis that the population dynamics of musk ox during the Late Quaternary period were related to climate change. : BEAST XML input files used for the data analysisSkygridXMLs.tar.gz
format Dataset
author Gill, Mandev S.
Lemey, Philippe
Bennett, Shannon N.
Biek, Roman
Suchard, Marc A.
author_facet Gill, Mandev S.
Lemey, Philippe
Bennett, Shannon N.
Biek, Roman
Suchard, Marc A.
author_sort Gill, Mandev S.
title Data from: Understanding past population dynamics: Bayesian coalescent-based modeling with covariates
title_short Data from: Understanding past population dynamics: Bayesian coalescent-based modeling with covariates
title_full Data from: Understanding past population dynamics: Bayesian coalescent-based modeling with covariates
title_fullStr Data from: Understanding past population dynamics: Bayesian coalescent-based modeling with covariates
title_full_unstemmed Data from: Understanding past population dynamics: Bayesian coalescent-based modeling with covariates
title_sort data from: understanding past population dynamics: bayesian coalescent-based modeling with covariates
publisher Dryad
publishDate 2016
url https://dx.doi.org/10.5061/dryad.mj0hn
http://datadryad.org/stash/dataset/doi:10.5061/dryad.mj0hn
genre musk ox
genre_facet musk ox
op_relation https://dx.doi.org/10.1093/sysbio/syw050
op_rights Creative Commons Zero v1.0 Universal
https://creativecommons.org/publicdomain/zero/1.0/legalcode
cc0-1.0
op_rightsnorm CC0
op_doi https://doi.org/10.5061/dryad.mj0hn
https://doi.org/10.1093/sysbio/syw050
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