AI Article Synopsis

  • Researchers created a faster and more memory-efficient version of the transfer bootstrap expectation (TBE) method for phylogenetic analysis, addressing limitations of the original, resource-heavy tool.
  • Their new implementation can be up to 480 times quicker and uses significantly less memory, making it better for large datasets.
  • This optimized TBE method has been integrated into existing tools and is available for public use under an open-source license.

Article 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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7141843PMC
http://dx.doi.org/10.1093/bioinformatics/btz874DOI Listing

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