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10 Publications visible to you, out of a total of 10
Metagenomic Analysis Using Phylogenetic Placement—A Review of the First Decade

Abstract

Not specified

Authors: Lucas Czech, Alexandros Stamatakis, Micah Dunthorn, Pierre Barbera

Date Published: 26th May 2022

Publication Type: Journal

Phylogenetic analysis of SARS-CoV-2 data is difficult

Abstract

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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

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

Date Published: 9th Oct 2020

Publication Type: Journal

Petabase-scale sequence alignment catalyses viral discovery

Abstract

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Authors: Robert C. Edgar, Jeff Taylor, Tomer Altman, Pierre Barbera, Dmitry Meleshko, Victor Lin, Dan Lohr, Gherman Novakovsky, Basem Al-Shayeb, Jillian F. Banfield, Anton Korobeynikov, Rayan Chikhi, Artem Babaian

Date Published: 10th Aug 2020

Publication Type: Journal

Genesis and Gappa: Processing, Analyzing and Visualizing Phylogenetic (Placement) Data

Abstract (Expand)

The ever increasing amount of genomic and meta-genomic sequence data has transformed biology into a data-driven and compute-intensive discipline. Hence, there is a need for efficient algorithms and … scalable implementations thereof for analysing such data. We present GENESIS, a library for working with phylogenetic data, and GAPPA, an accompanying command line tool for conducting typical analyses on such data. While our tools primarily target phylogenetic trees and phylogenetic placements, they also offer a plethora of functions for handling genetic sequences, taxonomies, and other relevant data types. The tools aim at improved usability at the production stage (conducting data analyses) as well as the development stage (rapid prototyping): The modular interface of GENESIS simplifies numerous standard high-level tasks and analyses, while allowing for low-level customization at the same time. Our implementation relies on modern, multi-threaded C++11, and is substantially more com-putationally efficient than analogous tools. We already employed the core GENESIS library in several of our tools and publications, thereby proving its flexibility and utility. GENESIS and GAPPA are freely available under GPLv3 at http://github.com/lczech/genesis and http://github.com/lczech/gappa.

Authors: Lucas Czech, Pierre Barbera, Alexandros Stamatakis

Date Published: 28th May 2019

Publication Type: Journal

Long metabarcoding of the eukaryotic rDNA operon to phylogenetically and taxonomically resolve environmental diversity

Abstract (Expand)

High-throughput environmental DNA metabarcoding has revolutionized the analysis of microbial diversity, but this approach is generally restricted to amplicon sizes below 500 base pairs. These short … regions contain limited phylogenetic signal, which makes it impractical to use environmental DNA in full phylogenetic inferences. However, new long-read sequencing technologies such as the Pacific Biosciences platform may provide sufficiently large sequence lengths to overcome the poor phylogenetic resolution of short amplicons. To test this idea, we amplified soil DNA and used PacBio Circular Consensus Sequencing (CCS) to obtain a ~4500 bp region of the eukaryotic rDNA operon spanning most of the small (18S) and large subunit (28S) ribosomal RNA genes. The CCS reads were first treated with a novel curation workflow that generated 650 high-quality OTUs containing the physically linked 18S and 28S regions of the long amplicons. In order to assign taxonomy to these OTUs, we developed a phylogeny-aware approach based on the 18S region that showed greater accuracy and sensitivity than similarity-based and phylogenetic placement-based methods using shorter reads. The taxonomically-annotated OTUs were then combined with available 18S and 28S reference sequences to infer a well-resolved phylogeny spanning all major groups of eukaryotes, allowing to accurately derive the evolutionary origin of environmental diversity. A total of 1019 sequences were included, of which a majority (58%) corresponded to the new long environmental CCS reads. Comparisons to the 18S-only region of our amplicons revealed that the combined 18S-28S genes globally increased the phylogenetic resolution, recovering specific groupings otherwise missing. The long-reads also allowed to directly investigate the relationships among environmental sequences themselves, which represents a key advantage over the placement of short reads on a reference phylogeny. Altogether, our results show that long amplicons can be treated in a full phylogenetic framework to provide greater taxonomic resolution and a robust evolutionary perspective to environmental DNA.

Authors: Mahwash Jamy, Rachel Foster, Pierre Barbera, Lucas Czech, Alexey Kozlov, Alexandros Stamatakis, David Baß, Fabien Burki

Date Published: 5th May 2019

Publication Type: Journal

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

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