A fast and memory-efficient implementation of the transfer bootstrap

Abstract:

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.

SEEK ID: https://publications.h-its.org/publications/1160

DOI: 10.1093/bioinformatics/btz874

Research Groups: Computational Molecular Evolution

Publication type: Journal

Journal: Bioinformatics

Editors: Russell Schwartz

Citation: Bioinformatics 36(7):2280-2281

Date Published: 1st Apr 2020

Registered Mode: by DOI

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Citation
Lutteropp, S., Kozlov, A. M., & Stamatakis, A. (2019). A fast and memory-efficient implementation of the transfer bootstrap. In R. Schwartz (Ed.), Bioinformatics (Vol. 36, Issue 7, pp. 2280–2281). Oxford University Press (OUP). https://doi.org/10.1093/bioinformatics/btz874
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Created: 18th Dec 2020 at 14:25

Last updated: 5th Mar 2024 at 21:24

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