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87 Publications visible to you, out of a total of 87
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

CellPhy: accurate and fast probabilistic inference of single-cell phylogenies from scDNA-seq data

Abstract

Not specified

Authors: Alexey Kozlov, Joao Alves, Alexandros Stamatakis, David Posada

Date Published: 2nd Aug 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

RootDigger : a root placement program for phylogenetic trees

Abstract

Not specified

Authors: Ben Bettisworth, Alexandros Stamatakis

Date Published: 14th Feb 2020

Publication Type: Journal

Empirical Analysis of Phylogenetic Quasi-Terraces

Abstract (Expand)

Terraces in phylogenetic tree space are, among other things, important for the design of tree space search strategies. While the phenomenon of phylogenetic terraces is already known for unlinked partition … models on partitioned phylogenomic data sets, it has not yet been studied if an analogous structure is present under linked and scaled partition models. To this end, we analyze aspects such as the log-likelihood distributions, likelihood-based significance tests, and nearest neighborhood interchanges on the trees residing on a terrace and compare their distributions among unlinked, linked, and scaled partition models. Our study shows that there exists a terrace-like structure under linked and scaled partition models as well. We denote this phenomenon as quasi-terrace. Therefore quasi-terraces should be taken into account in the design of tree search algorithms as well as when reporting results on ‘the’ final tree topology in empirical phylogenetic studies.

Authors: Paula Breitling, Alexandros Stamatakis, Olga Chernomor, Ben Bettisworth, Lukasz Reszczynski

Date Published: 18th Oct 2019

Publication Type: Journal

Treerecs: an integrated phylogenetic tool, from sequences to reconciliations

Abstract (Expand)

Motivation Gene and species tree reconciliation methods can be used to root gene trees and correct uncertainties that are due to scarcity of signal in multiple sequence alignments. So far, reconciliation … tools have not been integrated in standard phylogenetic software and they either lack of performance on certain functions, or usability for biologists. Results We present Treerecs, a phylogenetic software based on duplication-loss reconciliation. Treerecs is simple to install and to use, fast, versatile, with a graphic output, and can be used along with methods for phylogenetic inference on multiple alignments like PLL and Seaview. Availability Treerecs is open-source. Its source code (C++, AGPLv3) and manuals are available from https://project.inria.fr/treerecs/

Authors: Nicolas Comte, Benoit Morel, Damir Hasic, Laurent Guéguen, Bastien Boussau, Vincent Daubin, Simon Penel, Celine Scornavacca, Manolo Gouy, Alexandros Stamatakis, Eric Tannier, David P. Parsons

Date Published: 11th Oct 2019

Publication Type: Journal

GeneRax: A tool for species tree-aware maximum likelihood based gene tree inference under gene duplication, transfer, and loss

Abstract (Expand)

Inferring gene trees is difficult because alignments are often too short, and thus contain insufficient signal, while substitution models inevitably fail to capture the complexity of the evolutionary … processes. To overcome these challenges species tree-aware methods seek to use information from a putative species tree. However, there are few methods available that implement a full likelihood framework or account for horizontal gene transfers. Furthermore, these methods often require expensive data pre-processing (e.g., computing bootstrap trees), and rely on approximations and heuristics that limit the exploration of tree space. Here we present GeneRax, the first maximum likelihood species tree-aware gene tree inference software. It simultaneously accounts for substitutions at the sequence level and gene level events, such as duplication, transfer and loss and uses established maximum likelihood optimization algorithms. GeneRax can infer rooted gene trees for an arbitrary number of gene families, directly from the per-gene sequence alignments and a rooted, but undated, species tree. We show that compared to competing tools, on simulated data GeneRax infers trees that are the closest to the true tree in 90% of the simulations in terms relative Robinson-Foulds distance. While, on empirical datasets, GeneRax is the fastest among all tested methods when starting from aligned sequences, and that it infers trees with the highest likelihood score, based on our model. GeneRax completed tree inferences and reconciliations for 1099 Cyanobacteria families in eight minutes on 512 CPU cores. Thus, its advanced parallelization scheme enables large-scale analyses. GeneRax is available under GNU GPL at https://github.com/BenoitMorel/GeneRax.

Authors: Benoit Morel, Alexey M. Kozlov, Alexandros Stamatakis, Gergely J. Szöllősi

Date Published: 26th Sep 2019

Publication Type: Journal

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