HAL will be down for maintenance from Friday, June 10 at 4pm through Monday, June 13 at 9am. More information
Skip to Main content Skip to Navigation
Journal articles

Standardized benchmarking in the quest for orthologs

Adrian Altenhoff 1 Brigitte Boeckmann 1 Salvador Capella-Gutiérrez 2 Daniel Dalquen 3 Todd Deluca 4 Kristoffer Forslund 5 Jaime Huerta-Cepas 5 Benjamin Linard 6 Cécile Pereira 7 Leszek Pryszcz 8 Fabian Schreiber 9 Alan Sousa da Silva 9 Damian Szklarczyk 10 Clément-Marie Train 11 Peer Bork 12 Odile Lecompte 13 Christian von Mering 1 Ioannis Xenarios 14 Kimmen Sjölander 15 Lars Juhl Jensen 16 Maria J Martin 9 Matthieu Muffato 9 Toni Gabaldon 8 Suzanna E Lewis 15 Paul D Thomas 17 Erik Sonnhammer 18 Christophe Dessimoz 19
1 SIB - Swiss Institute of Bioinformatics [Lausanne]
2 UPF - Universitat Pompeu Fabra [Barcelona]
3 Department of Genetics, Evolution and Environment
4 HMS - Harvard Medical School [Boston]
5 EMBL - European Molecular Biology Laboratory [Heidelberg]
6 MAB - Méthodes et Algorithmes pour la Bioinformatique
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
7 LRI - Laboratoire de Recherche en Informatique
8 BIST - Barcelona Institute of Science and Technology
9 EMBL-EBI - European Bioinformatics Institute [Hinxton]
10 UZH - Universität Zürich [Zürich] = University of Zurich
11 D-INFK - Department of Computer Science [ETH Zürich]
12 Max Delbrück Centre for Molecular Medicine
13 IGBMC - Institut de Génétique et de Biologie Moléculaire et Cellulaire
14 SIB - Swiss Institute of Bioinformatics [Genève]
15 LBNL - Lawrence Berkeley National Laboratory [Berkeley]
16 CPR - Novo Nordisk Foundation Center for Protein Research
17 SRI International, Evolutionary System Biolology
18 USC - University of Southern California
19 Department of Computer Science
Abstract : Achieving high accuracy in orthology inference is essential for many comparative, evolutionary and functional genomic analyses, yet the true evolutionary history of genes is generally unknown and orthologs are used for very different applications across phyla, requiring different precision–recall trade-offs. As a result, it is difficult to assess the performance of orthology inference methods. Here, we present a community effort to establish standards and an automated web-based service to facilitate orthology benchmarking. Using this service, we characterize 15 well-established inference methods and resources on a battery of 20 different benchmarks. Standardized benchmarking provides a way for users to identify the most effective methods for the problem at hand, sets a minimum requirement for new tools and resources, and guides the development of more accurate orthology inference methods.
Document type :
Journal articles
Complete list of metadata

Cited literature [60 references]  Display  Hide  Download
https://hal.archives-ouvertes.fr/hal-01636892
Contributor : Benjamin Linard Connect in order to contact the contributor
Submitted on : Friday, November 17, 2017 - 10:26:33 AM
Last modification on : Wednesday, January 5, 2022 - 3:02:04 PM
Long-term archiving on: : Sunday, February 18, 2018 - 1:14:43 PM

File

Vignette du document
nature_orthologs.pdf
Publisher files allowed on an open archive

Licence

Distributed under a Creative Commons Attribution - NonCommercial - ShareAlike 4.0 International License

Identifiers

Collections

CNRS | IGBMC | LIRMM | CENTRALESUPELEC | MIPS | UNIV-MONTPELLIER | UMR8623 | UNIV-PARIS-SACLAY | INSERM | MAB | LRI-BIOINFO | SITE-ALSACE | ANR | GS-COMPUTER-SCIENCE

Citation

Adrian Altenhoff, Brigitte Boeckmann, Salvador Capella-Gutiérrez, Daniel Dalquen, Todd Deluca, et al.. Standardized benchmarking in the quest for orthologs. Nature Methods, Nature Publishing Group, 2016, 13 (5), pp.425-430. ⟨10.1038/nMeth.3830⟩. ⟨hal-01636892⟩

Export

BibTeX TEI DC DCterms EndNote Datacite

Share

Metrics

Record views

3531

Files downloads

120