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Swapping Birth and Death: Symmetries and Transformations in Phylodynamic Models

Stochastic birth–death models provide the foundation for studying and simulating evolutionary trees in phylodynamics. A curious feature of such models is that they exhibit fundamental symmetries when the birth and death rates are interchanged. In this article, we first provide intuitive reasons for...

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Detalles Bibliográficos
Autores principales: Stadler, Tanja, Steel, Mike
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6701459/
https://www.ncbi.nlm.nih.gov/pubmed/31135030
http://dx.doi.org/10.1093/sysbio/syz039
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author Stadler, Tanja
Steel, Mike
author_facet Stadler, Tanja
Steel, Mike
author_sort Stadler, Tanja
collection PubMed
description Stochastic birth–death models provide the foundation for studying and simulating evolutionary trees in phylodynamics. A curious feature of such models is that they exhibit fundamental symmetries when the birth and death rates are interchanged. In this article, we first provide intuitive reasons for these known transformational symmetries. We then show that these transformational symmetries (encoded in algebraic identities) are preserved even when individuals at the present are sampled with some probability. However, these extended symmetries require the death rate parameter to sometimes take a negative value. In the last part of this article, we describe the relevance of these transformations and their application to computational phylodynamics, particularly to maximum likelihood and Bayesian inference methods, as well as to model selection.
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spelling pubmed-67014592019-08-23 Swapping Birth and Death: Symmetries and Transformations in Phylodynamic Models Stadler, Tanja Steel, Mike Syst Biol Points of View Stochastic birth–death models provide the foundation for studying and simulating evolutionary trees in phylodynamics. A curious feature of such models is that they exhibit fundamental symmetries when the birth and death rates are interchanged. In this article, we first provide intuitive reasons for these known transformational symmetries. We then show that these transformational symmetries (encoded in algebraic identities) are preserved even when individuals at the present are sampled with some probability. However, these extended symmetries require the death rate parameter to sometimes take a negative value. In the last part of this article, we describe the relevance of these transformations and their application to computational phylodynamics, particularly to maximum likelihood and Bayesian inference methods, as well as to model selection. Oxford University Press 2019-09 2019-05-28 /pmc/articles/PMC6701459/ /pubmed/31135030 http://dx.doi.org/10.1093/sysbio/syz039 Text en © The Author(s) 2019. Published by Oxford University Press on behalf of the Society of Systematic Biologists. 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 reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Points of View
Stadler, Tanja
Steel, Mike
Swapping Birth and Death: Symmetries and Transformations in Phylodynamic Models
title Swapping Birth and Death: Symmetries and Transformations in Phylodynamic Models
title_full Swapping Birth and Death: Symmetries and Transformations in Phylodynamic Models
title_fullStr Swapping Birth and Death: Symmetries and Transformations in Phylodynamic Models
title_full_unstemmed Swapping Birth and Death: Symmetries and Transformations in Phylodynamic Models
title_short Swapping Birth and Death: Symmetries and Transformations in Phylodynamic Models
title_sort swapping birth and death: symmetries and transformations in phylodynamic models
topic Points of View
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6701459/
https://www.ncbi.nlm.nih.gov/pubmed/31135030
http://dx.doi.org/10.1093/sysbio/syz039
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