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SPART: A versatile and standardized data exchange format for species partition information

Abstract

Not specified

Authors: Aurélien Miralles, Jacques Ducasse, Sophie Brouillet, Tomas Flouri, Tomochika Fujisawa, Paschalia Kapli, L. Lacey Knowles, Sangeeta Kumari, Alexandros Stamatakis, Jeet Sukumaran, Sarah Lutteropp, Miguel Vences, Nicolas Puillandre

Date Published: 2022

Publication Type: Journal

NetRAX: Accurate and Fast Maximum Likelihood Phylogenetic Network Inference ⋆

Abstract

Not specified

Authors: Sarah Lutteropp, Céline Scornavacca, Alexey M. Kozlov, Benoit Morel, Alexandros Stamatakis

Date Published: 31st Aug 2021

Publication Type: Journal

SpeciesRax: A tool for maximum likelihood species tree inference from gene family trees under duplication, transfer, and loss

Abstract

Not specified

Authors: Benoit Morel, Paul Schade, Sarah Lutteropp, Tom A. Williams, Gergely J. Szöllősi, Alexandros Stamatakis

Date Published: 29th Mar 2021

Publication Type: Journal

SPART, a versatile and standardized data exchange format for species partition information

Abstract

Not specified

Authors: Aurélien Miralles, Jacques Ducasse, Sophie Brouillet, Tomas Flouri, Tomochika Fujisawa, Paschalia Kapli, L. Lacey Knowles, Sangeeta Kumari, Alexandros Stamatakis, Jeet Sukumaran, Sarah Lutteropp, Miguel Vences, Nicolas Puillandre

Date Published: 22nd Mar 2021

Publication Type: Journal

Phylogenetic analysis of SARS-CoV-2 data is difficult

Abstract

Not specified

Authors: Benoit Morel, Pierre Barbera, Lucas Czech, Ben Bettisworth, Lukas Hübner, Sarah Lutteropp, Dora Serdari, Evangelia-Georgia Kostaki, Ioannis Mamais, Alexey M Kozlov, Pavlos Pavlidis, Dimitrios Paraskevis, Alexandros Stamatakis

Date Published: 15th Dec 2020

Publication Type: Journal

SCRAPP : A tool to assess the diversity of microbial samples from phylogenetic placements

Abstract

Not specified

Authors: Pierre Barbera, Lucas Czech, Sarah Lutteropp, Alexandros Stamatakis

Date Published: 9th Oct 2020

Publication Type: Journal

A fast and memory-efficient implementation of the transfer bootstrap

Abstract (Expand)

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.

Authors: Sarah Lutteropp, Alexey M Kozlov, Alexandros Stamatakis

Date Published: 1st Apr 2020

Publication Type: Journal

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