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Lagrange-NG: The next generation of Lagrange

View ORCID ProfileBen Bettisworth, View ORCID ProfileStephen A. Smith, Alexandros Stamatakis
doi: https://doi.org/10.1101/2022.04.19.488734
Ben Bettisworth
1Computational Molecular Evolution Group, Heidelberg Institute for Theoretical Studies, Heidelberg, Germany
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  • For correspondence: ben.bettisworth@h-its.org
Stephen A. Smith
2Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, United States
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Alexandros Stamatakis
1Computational Molecular Evolution Group, Heidelberg Institute for Theoretical Studies, Heidelberg, Germany
3Institute for Theoretical Informatics, Karlsruhe Institute of Technology, Karlsruhe, Germany
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Abstract

Computing ancestral ranges via the Dispersion Extinction and Cladogensis (DEC) model of biogeography is characterized by an exponential number of states relative to the number of regions considered. This is because the DEC model requires computing a large matrix exponential, which typically accounts for up to 80% of overall runtime. Therefore, the kinds of biogeographical analyses that can be conducted under the DEC model are limited by the number of regions under consideration. In this work, we present a completely redesigned efficient version of the popular tool Lagrange which is up to 2.5 times faster, which we call Lagrange-NG (Next Generation). We further reduce time-to-completion by introducing a multi-grained parallelization approach, achieving a total parallel speedup of 8.5 over Lagrange on a machine with 8 cores. In order to validate the correctness of Lagrange-NG, we also introduce a novel metric on range distributions for trees in order to assess the difference between any two range inferences. Finally, Lagrange-NG exhibits substantially higher adherence to coding quality standards. It improves a respective software quality indicator as implemented in the SoftWipe tool from average (5.5; Lagrange) to high (7.8; Lagrange-NG). Lagrange-NG is freely available under GPL2.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
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Posted April 20, 2022.
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Lagrange-NG: The next generation of Lagrange
Ben Bettisworth, Stephen A. Smith, Alexandros Stamatakis
bioRxiv 2022.04.19.488734; doi: https://doi.org/10.1101/2022.04.19.488734
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Lagrange-NG: The next generation of Lagrange
Ben Bettisworth, Stephen A. Smith, Alexandros Stamatakis
bioRxiv 2022.04.19.488734; doi: https://doi.org/10.1101/2022.04.19.488734

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