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Modeling the velocity of evolving lineages and predicting dispersal patterns.
Bastide, Paul; Rocu, Pauline; Wirtz, Johannes; Hassler, Gabriel W; Chevenet, François; Fargette, Denis; Suchard, Marc A; Dellicour, Simon; Lemey, Philippe; Guindon, Stéphane.
Afiliação
  • Bastide P; IMAG, Université de Montpellier, CNRS, Montpellier, France.
  • Rocu P; Laboratoire d'Informatique, de Robotique et de Microélectronique de Montpellier. CNRS - UMR 5506. Montpellier, France.
  • Wirtz J; CEFE, Université de Montpellier, CNRS, EPHE, IRD, Montpellier, France.
  • Hassler GW; Department of Economics, Sociology, and Statistics, RAND, Santa Monica, CA, USA.
  • Chevenet F; MIVEGEC, IRD, CNRS, Université de Montpellier, Montpellier, France.
  • Fargette D; PHIM, IRD, INRAE, CIRAD, Université de Montpellier, Montpellier, France.
  • Suchard MA; Department of Biostatistics, Jonathan and Karin Fielding School of Public Health, University of California, Los Angeles, CA, USA.
  • Dellicour S; Department of Human Genetics, David Geffen School of Medicine at UCLA, University of California, Los Angeles, CA, USA.
  • Lemey P; Department of Computational Medicine, David Geffen School of Medicine at UCLA, University of California, Los Angeles, CA, USA.
  • Guindon S; Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, Brussels, Belgium.
bioRxiv ; 2024 Jun 06.
Article em En | MEDLINE | ID: mdl-38895258
ABSTRACT
Accurate estimation of the dispersal velocity or speed of evolving organisms is no mean feat. In fact, existing probabilistic models in phylogeography or spatial population genetics generally do not provide an adequate framework to define velocity in a relevant manner. For instance, the very concept of instantaneous speed simply does not exist under one of the most popular approaches that models the evolution of spatial coordinates as Brownian trajectories running along a phylogeny [30]. Here, we introduce a new family of models - the so-called "Phylogenetic Integrated Velocity" (PIV) models - that use Gaussian processes to explicitly model the velocity of evolving lineages instead of focusing on the fluctuation of spatial coordinates over time. We describe the properties of these models and show an increased accuracy of velocity estimates compared to previous approaches. Analyses of West Nile virus data in the U.S.A. indicate that PIV models provide sensible predictions of the dispersal of evolving pathogens at a one-year time horizon. These results demonstrate the feasibility and relevance of predictive phylogeography in monitoring epidemics in time and space.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article