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Point estimates in phylogenetic reconstructions

Motivation: The construction of statistics for summarizing posterior samples returned by a Bayesian phylogenetic study has so far been hindered by the poor geometric insights available into the space of phylogenetic trees, and ad hoc methods such as the derivation of a consensus tree makeup for the...

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Autores principales: Benner, Philipp, Bačák, Miroslav, Bourguignon, Pierre-Yves
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4147914/
https://www.ncbi.nlm.nih.gov/pubmed/25161244
http://dx.doi.org/10.1093/bioinformatics/btu461
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author Benner, Philipp
Bačák, Miroslav
Bourguignon, Pierre-Yves
author_facet Benner, Philipp
Bačák, Miroslav
Bourguignon, Pierre-Yves
author_sort Benner, Philipp
collection PubMed
description Motivation: The construction of statistics for summarizing posterior samples returned by a Bayesian phylogenetic study has so far been hindered by the poor geometric insights available into the space of phylogenetic trees, and ad hoc methods such as the derivation of a consensus tree makeup for the ill-definition of the usual concepts of posterior mean, while bootstrap methods mitigate the absence of a sound concept of variance. Yielding satisfactory results with sufficiently concentrated posterior distributions, such methods fall short of providing a faithful summary of posterior distributions if the data do not offer compelling evidence for a single topology. Results: Building upon previous work of Billera et al., summary statistics such as sample mean, median and variance are defined as the geometric median, Fréchet mean and variance, respectively. Their computation is enabled by recently published works, and embeds an algorithm for computing shortest paths in the space of trees. Studying the phylogeny of a set of plants, where several tree topologies occur in the posterior sample, the posterior mean balances correctly the contributions from the different topologies, where a consensus tree would be biased. Comparisons of the posterior mean, median and consensus trees with the ground truth using simulated data also reveals the benefits of a sound averaging method when reconstructing phylogenetic trees. Availability and implementation: We provide two independent implementations of the algorithm for computing Fréchet means, geometric medians and variances in the space of phylogenetic trees. TFBayes: https://github.com/pbenner/tfbayes, TrAP: https://github.com/bacak/TrAP. Contact: philipp.benner@mis.mpg.de
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spelling pubmed-41479142014-09-02 Point estimates in phylogenetic reconstructions Benner, Philipp Bačák, Miroslav Bourguignon, Pierre-Yves Bioinformatics Eccb 2014 Proceedings Papers Committee Motivation: The construction of statistics for summarizing posterior samples returned by a Bayesian phylogenetic study has so far been hindered by the poor geometric insights available into the space of phylogenetic trees, and ad hoc methods such as the derivation of a consensus tree makeup for the ill-definition of the usual concepts of posterior mean, while bootstrap methods mitigate the absence of a sound concept of variance. Yielding satisfactory results with sufficiently concentrated posterior distributions, such methods fall short of providing a faithful summary of posterior distributions if the data do not offer compelling evidence for a single topology. Results: Building upon previous work of Billera et al., summary statistics such as sample mean, median and variance are defined as the geometric median, Fréchet mean and variance, respectively. Their computation is enabled by recently published works, and embeds an algorithm for computing shortest paths in the space of trees. Studying the phylogeny of a set of plants, where several tree topologies occur in the posterior sample, the posterior mean balances correctly the contributions from the different topologies, where a consensus tree would be biased. Comparisons of the posterior mean, median and consensus trees with the ground truth using simulated data also reveals the benefits of a sound averaging method when reconstructing phylogenetic trees. Availability and implementation: We provide two independent implementations of the algorithm for computing Fréchet means, geometric medians and variances in the space of phylogenetic trees. TFBayes: https://github.com/pbenner/tfbayes, TrAP: https://github.com/bacak/TrAP. Contact: philipp.benner@mis.mpg.de Oxford University Press 2014-09-01 2014-08-22 /pmc/articles/PMC4147914/ /pubmed/25161244 http://dx.doi.org/10.1093/bioinformatics/btu461 Text en © The Author 2014. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Eccb 2014 Proceedings Papers Committee
Benner, Philipp
Bačák, Miroslav
Bourguignon, Pierre-Yves
Point estimates in phylogenetic reconstructions
title Point estimates in phylogenetic reconstructions
title_full Point estimates in phylogenetic reconstructions
title_fullStr Point estimates in phylogenetic reconstructions
title_full_unstemmed Point estimates in phylogenetic reconstructions
title_short Point estimates in phylogenetic reconstructions
title_sort point estimates in phylogenetic reconstructions
topic Eccb 2014 Proceedings Papers Committee
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4147914/
https://www.ncbi.nlm.nih.gov/pubmed/25161244
http://dx.doi.org/10.1093/bioinformatics/btu461
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