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A fast and memory-efficient implementation of the transfer bootstrap

MOTIVATION: Recently, Lemoine et al. suggested the transfer bootstrap expectation (TBE) branch support metric as an alternative to classical phylogenetic bootstrap support for taxon-rich datasets. However, the original TBE implementation in the booster tool is compute- and memory-intensive. RESULTS:...

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Detalles Bibliográficos
Autores principales: Lutteropp, Sarah, Kozlov, Alexey M, Stamatakis, Alexandros
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7141843/
https://www.ncbi.nlm.nih.gov/pubmed/31755898
http://dx.doi.org/10.1093/bioinformatics/btz874
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author Lutteropp, Sarah
Kozlov, Alexey M
Stamatakis, Alexandros
author_facet Lutteropp, Sarah
Kozlov, Alexey M
Stamatakis, Alexandros
author_sort Lutteropp, Sarah
collection PubMed
description MOTIVATION: Recently, Lemoine et al. suggested the transfer bootstrap expectation (TBE) branch support metric as an alternative to classical phylogenetic bootstrap support for taxon-rich datasets. However, the original TBE implementation in the booster tool is compute- and memory-intensive. RESULTS: We developed a fast and memory-efficient TBE implementation. We improve upon the original algorithm by Lemoine et al. via several algorithmic and technical optimizations. On empirical as well as on random tree sets with varying taxon counts, our implementation is up to 480 times faster than booster. Furthermore, it only requires memory that is linear in the number of taxa, which leads to 10× to 40× memory savings compared with booster. AVAILABILITY AND IMPLEMENTATION: Our implementation has been partially integrated into pll-modules and RAxML-NG and is available under the GNU Affero General Public License v3.0 at https://github.com/ddarriba/pll-modules and https://github.com/amkozlov/raxml-ng. The parallel version that also computes additional TBE-related statistics is available at: https://github.com/lutteropp/raxml-ng/tree/tbe. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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spelling pubmed-71418432020-04-13 A fast and memory-efficient implementation of the transfer bootstrap Lutteropp, Sarah Kozlov, Alexey M Stamatakis, Alexandros Bioinformatics Applications Notes MOTIVATION: Recently, Lemoine et al. suggested the transfer bootstrap expectation (TBE) branch support metric as an alternative to classical phylogenetic bootstrap support for taxon-rich datasets. However, the original TBE implementation in the booster tool is compute- and memory-intensive. RESULTS: We developed a fast and memory-efficient TBE implementation. We improve upon the original algorithm by Lemoine et al. via several algorithmic and technical optimizations. On empirical as well as on random tree sets with varying taxon counts, our implementation is up to 480 times faster than booster. Furthermore, it only requires memory that is linear in the number of taxa, which leads to 10× to 40× memory savings compared with booster. AVAILABILITY AND IMPLEMENTATION: Our implementation has been partially integrated into pll-modules and RAxML-NG and is available under the GNU Affero General Public License v3.0 at https://github.com/ddarriba/pll-modules and https://github.com/amkozlov/raxml-ng. The parallel version that also computes additional TBE-related statistics is available at: https://github.com/lutteropp/raxml-ng/tree/tbe. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2020-04-01 2019-11-22 /pmc/articles/PMC7141843/ /pubmed/31755898 http://dx.doi.org/10.1093/bioinformatics/btz874 Text en © The Author(s) 2019. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), 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 Applications Notes
Lutteropp, Sarah
Kozlov, Alexey M
Stamatakis, Alexandros
A fast and memory-efficient implementation of the transfer bootstrap
title A fast and memory-efficient implementation of the transfer bootstrap
title_full A fast and memory-efficient implementation of the transfer bootstrap
title_fullStr A fast and memory-efficient implementation of the transfer bootstrap
title_full_unstemmed A fast and memory-efficient implementation of the transfer bootstrap
title_short A fast and memory-efficient implementation of the transfer bootstrap
title_sort fast and memory-efficient implementation of the transfer bootstrap
topic Applications Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7141843/
https://www.ncbi.nlm.nih.gov/pubmed/31755898
http://dx.doi.org/10.1093/bioinformatics/btz874
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