期刊
NATURE METHODS
卷 13, 期 5, 页码 425-+出版社
NATURE PORTFOLIO
DOI: 10.1038/NMETH.3830
关键词
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资金
- Swiss National Science Foundation [PP00P3_150654]
- UK Biotechnology and Biological Sciences Research Council [BB/L018241/1]
- Spanish Ministry of Economy and Competitiveness [BI02012-37161]
- Qatar National Research Fund [NPRP 5-298-3-086]
- European Research Council [ERC-2012-StG-310325]
- National Institutes of Health (NIH) [R24 OD011883, U41 HG002273, U41 HG007822]
- Swiss State Secretariat for Education, Research and Innovation (SERI) funding
- US National Science Foundation EAGER Award [1355632]
- ANR project [BIP-BIP ANR-10-BINF-03-02]
- European Molecular Biology Laboratory
- Wellcome Trust [WT095908]
- Lawrence Berkeley National Laboratory core funds (Office of Basic Energy Sciences and US Department of Energy) [DE-AC02-05CH11231]
- Novo Nordisk Foundation [NNF14CC0001]
- La Caixa-CRG International Fellowship Program
- Biotechnology and Biological Sciences Research Council [BB/L018241/1] Funding Source: researchfish
- Novo Nordisk Foundation Center for Protein Research [PI Lars Juhl Jensen] Funding Source: researchfish
- Swiss National Science Foundation (SNF) [PP00P3_150654] Funding Source: Swiss National Science Foundation (SNF)
- BBSRC [BB/L018241/1] Funding Source: UKRI
- ICREA Funding Source: Custom
- Div Of Information & Intelligent Systems
- Direct For Computer & Info Scie & Enginr [1355632] Funding Source: National Science Foundation
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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