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EPA-ng: Massively Parallel Evolutionary Placement of Genetic Sequences

Barbera, P; Kozlov, A; Czech, L; Morel, B; Darriba, D; Flouris, T; Stamatakis, A; (2019) EPA-ng: Massively Parallel Evolutionary Placement of Genetic Sequences. Systematic Biology , 68 (2) 10.1093/sysbio/syy054. Green open access

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Abstract

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:

Type: Article
Title: EPA-ng: Massively Parallel Evolutionary Placement of Genetic Sequences
Open access status: An open access version is available from UCL Discovery
DOI: 10.1093/sysbio/syy054
Publisher version: https://doi.org/10.1093/sysbio/syy054
Language: English
Additional information: This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contactjournals.permissions@oup.com
Keywords: Metabarcoding, metagenomics, microbiome, phylogenetics, phylogenetic placement
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences > Genetics, Evolution and Environment
URI: https://discovery.ucl.ac.uk/id/eprint/10070099
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