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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:...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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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. |
format | Online Article Text |
id | pubmed-7141843 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
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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