Standardized benchmarking in the quest for orthologs
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 tr...
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| Main Authors: | , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
4 April 2016
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| In: |
Nature methods
Year: 2016, Volume: 13, Issue: 5, Pages: 425-430 |
| ISSN: | 1548-7105 |
| DOI: | 10.1038/nmeth.3830 |
| Online Access: | Verlag, Volltext: https://doi.org/10.1038/nmeth.3830 Verlag, Volltext: https://www.nature.com/articles/nmeth.3830 
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| Author Notes: | Adrian M. Altenhoff, Brigitte Boeckmann, Salvador Capella-Gutierrez, Daniel A. Dalquen, Todd DeLuca, Kristoffer Forslund, Jaime Huerta-Cepas, Benjamin Linard, Cécile Pereira, Leszek P. Pryszcz, Fabian Schreiber, Alan Sousa da Silva, Damian Szklarczyk, Clément-Marie Train, Peer Bork, Odile Lecompte, Christian von Mering, Ioannis Xenarios, Kimmen Sjölander, Lars Juhl Jensen, Maria J. Martin, Matthieu Muffato, Quest for Orthologs Consortium, Adrian M. Altenhoff, Brigitte Boeckmann, Salvador Capella-Gutierrez, Todd DeLuca, Kristoffer Forslund, Jaime Huerta-Cepas, Benjamin Linard, Cécile Pereira, Leszek P. Pryszcz, Fabian Schreiber, Alan Sousa da Silva, Damian Szklarczyk, Clément-Marie Train, Odile Lecompte, Ioannis Xenarios, Kimmen Sjölander, Maria J. Martin, Matthieu Muffato, Toni Gabaldón, Suzanna E. Lewis, Paul D. Thomas, Erik Sonnhammer, Christophe Dessimoz, Toni Gabaldón, Suzanna E. Lewis, Paul D. Thomas, Erik Sonnhammer & Christophe Dessimoz |
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| 520 | |a 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. | ||
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