The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
Phylogeography Takes a Relaxed Random Walk in Continuous Space and Time
Open accessAbstract
Research aimed at understanding the geographic context of evolutionary histories is burgeoning across biological disciplines. Recent endeavors attempt to interpret contemporaneous genetic variation in the light of increasingly detailed geographical and environmental observations. Such interest has promoted the development of phylogeographic inference techniques that explicitly aim to integrate such heterogeneous data. One promising development involves reconstructing phylogeographic history on a continuous landscape. Here, we present a Bayesian statistical approach to infer continuous phylogeographic diffusion using random walk models while simultaneously reconstructing the evolutionary history in time from molecular sequence data. Moreover, by accommodating branch-specific variation in dispersal rates, we relax the most restrictive assumption of the standard Brownian diffusion process and demonstrate increased statistical efficiency in spatial reconstructions of overdispersed random walks by analyzing both simulated and real viral genetic data. We further illustrate how drawing inference about summary statistics from a fully specified stochastic process over both sequence evolution and spatial movement reveals important characteristics of a rabies epidemic. Together with recent advances in discrete phylogeographic inference, the continuous model developments furnish a flexible statistical framework for biogeographical reconstructions that is easily expanded upon to accommodate various landscape genetic features.
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Citations
Cites
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Self-citation
Cited by
BEAST 2: a software platform for Bayesian evolutionary analysis
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Self-citationBEAST 2.5: An advanced software platform for Bayesian evolutionary analysis
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Self-citationDetection of a SARS-CoV-2 variant of concern in South Africa
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Emergence of SARS-CoV-2 Omicron lineages BA.4 and BA.5 in South Africa
Tegally, H., Moir, M., Everatt, J., Giovanetti, M., Scheepers, C., Wilkinson, E., Subramoney, K., Makatini, Z., Moyo, S., Amoako, D. G., et al. (2022) · Nature Medicine · doi:10.1038/s41591-022-01911-2 · Cited by 707
Self-citationEvolution and epidemic spread of SARS-CoV-2 in Brazil
Candido, D. S., Claro, I. M., de Jesus, J. G., Souza, W. M., Moreira, F. R. R., Dellicour, S., Mellan, T. A., du Plessis, L., Pereira, R. H. M., Sales, F. C. S., et al. (2020) · Science · doi:10.1126/science.abd2161 · Cited by 573
Self-citationSixteen novel lineages of SARS-CoV-2 in South Africa
Tegally, H., Wilkinson, E., Lessells, R. J., Giandhari, J., Pillay, S., Msomi, N., Mlisana, K., Bhiman, J. N., von Gottberg, A., Walaza, S., et al. (2021) · Nature Medicine · doi:10.1038/s41591-021-01255-3 · Cited by 349
Genomic characterization of a novel SARS-CoV-2 lineage from Rio de Janeiro, Brazil
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A biologist’s guide to Bayesian phylogenetic analysis
Nascimento, F. F., Reis, M. D., & Yang, Z. (2017) · Nature Ecology & Evolution · doi:10.1038/s41559-017-0280-x · Cited by 212
Genomic characterization of a novel SARS-CoV-2 lineage from Rio de Janeiro, Brazil
Voloch, C. M., Silva F, R. D., de Almeida, L. G. P., Cardoso, C. C., Brustolini, O. J., Gerber, A. L., Guimarães, A. P. D. C., Mariani, D., Costa, R. M. D., Ferreira, O. C., et al. (2020) · doi:10.1101/2020.12.23.20248598 · Cited by 372
Metadata
- Authors
- Lemey, P., Rambaut, A., Welch, J. J., & Suchard, M. A.
- Venue
- Molecular Biology and Evolution
- Publisher
- Oxford University Press (OUP)
- Published
- 2010-03-04
- Volume
- 27
- Issue
- 8
- Pages
- 1877-1885
- ISSN
- 0737-4038 (ISSN-L)
- 1537-1719
- OpenAlex
- W2139166200
- Cited by
- 685
- References
- 8
- FWCI
- 15.59
- Type
- journal article
- Language
- en
- Open access
- green
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