Filter and export

Publications

What is a Publication?
18 Publications visible to you, out of a total of 18
Photoreceptor diversification accompanies the evolution of Anthozoa

Abstract

Not specified

Authors: Sebastian G Gornik, B Gideon Bergheim, Benoit Morel, Alexandros Stamatakis, Nicholas S Foulkes, Annika Guse

Date Published: 23rd Nov 2020

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

ModelTest-NG: A New and Scalable Tool for the Selection of DNA and Protein Evolutionary Models

Abstract (Expand)

ModelTest-NG is a reimplementation from scratch of jModelTest and ProtTest, two popular tools for selecting the best-fit nucleotide and amino acid substitution models, respectively. ModelTest-NG is one … to two orders of magnitude faster than jModelTest and ProtTest but equally accurate and introduces several new features, such as ascertainment bias correction, mixture, and free-rate models, or the automatic processing of single partitions. ModelTest-NG is available under a GNU GPL3 license at https://github.com/ddarriba/modeltest , last accessed September 2, 2019.

Authors: Diego Darriba, David Posada, Alexey M Kozlov, Alexandros Stamatakis, Benoit Morel, Tomas Flouri

Date Published: 21st Aug 2019

Publication Type: Journal

Data Distribution for Phylogenetic Inference with Site Repeats via Judicious Hypergraph Partitioning

Abstract

Not specified

Authors: Ivo Baar, Lukas Hubner, Peter Oettig, Adrian Zapletal, Sebastian Schlag, Alexandros Stamatakis, Benoit Morel

Date Published: 1st May 2019

Publication Type: Proceedings

EPA-ng: Massively Parallel Evolutionary Placement of Genetic Sequences

Abstract (Expand)

Next generation sequencing (NGS) technologies have led to a ubiquity of molecular sequence data. This data avalanche is particularly challenging in metagenetics, which focuses on taxonomic identification … of sequences obtained from diverse microbial environments. Phylogenetic placement methods determine how these sequences fit into an evolutionary context. Previous implementations of phylogenetic placement algorithms, such as the evolutionary placement algorithm (EPA) included in RAxML, or PPLACER, are being increasingly used for this purpose. However, due to the steady progress in NGS technologies, the current implementations face substantial scalability limitations. Herein, we present EPA-NG, a complete reimplementation of the EPA that is substantially faster, offers a distributed memory parallelization, and integrates concepts from both, RAxML-EPA and PPLACER. EPA-NG can be executed on standard shared memory, as well as on distributed memory systems (e.g., computing clusters). To demonstrate the scalability of EPA-NG, we placed 1 billion metagenetic reads from the Tara Oceans Project onto a reference tree with 3748 taxa in just under 7 h, using 2048 cores. Our performance assessment shows that EPA-NG outperforms RAxML-EPA and PPLACER by up to a factor of 30 in sequential execution mode, while attaining comparable parallel efficiency on shared memory systems. We further show that the distributed memory parallelization of EPA-NG scales well up to 2048 cores. EPA-NG is available under the AGPLv3 license: https://github.com/Pbdas/epa-ng.

Authors: Pierre Barbera, Alexey M Kozlov, Lucas Czech, Benoit Morel, Diego Darriba, Tomáš Flouri, Alexandros Stamatakis

Date Published: 2018

Publication Type: Journal

ParGenes: a tool for massively parallel model selection and phylogenetic tree inference on thousands of genes.

Abstract

Not specified

Authors: Benoit Morel, Alexey M Kozlov, Alexandros Stamatakis

Date Published: 2018

Publication Type: Journal

Powered by
 (v.1.14.2)
About HITS Publication SEEK | About HITS-Publication-SEEK | Funding and Programmes | Credits
Copyright © 2008 - 2023 The University of Manchester and HITS gGmbH