4.8 Article

Standardized benchmarking in the quest for orthologs

期刊

NATURE METHODS
卷 13, 期 5, 页码 425-+

出版社

NATURE PORTFOLIO
DOI: 10.1038/NMETH.3830

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资金

  1. Swiss National Science Foundation [PP00P3_150654]
  2. UK Biotechnology and Biological Sciences Research Council [BB/L018241/1]
  3. Spanish Ministry of Economy and Competitiveness [BI02012-37161]
  4. Qatar National Research Fund [NPRP 5-298-3-086]
  5. European Research Council [ERC-2012-StG-310325]
  6. National Institutes of Health (NIH) [R24 OD011883, U41 HG002273, U41 HG007822]
  7. Swiss State Secretariat for Education, Research and Innovation (SERI) funding
  8. US National Science Foundation EAGER Award [1355632]
  9. ANR project [BIP-BIP ANR-10-BINF-03-02]
  10. European Molecular Biology Laboratory
  11. Wellcome Trust [WT095908]
  12. Lawrence Berkeley National Laboratory core funds (Office of Basic Energy Sciences and US Department of Energy) [DE-AC02-05CH11231]
  13. Novo Nordisk Foundation [NNF14CC0001]
  14. La Caixa-CRG International Fellowship Program
  15. Biotechnology and Biological Sciences Research Council [BB/L018241/1] Funding Source: researchfish
  16. Novo Nordisk Foundation Center for Protein Research [PI Lars Juhl Jensen] Funding Source: researchfish
  17. Swiss National Science Foundation (SNF) [PP00P3_150654] Funding Source: Swiss National Science Foundation (SNF)
  18. BBSRC [BB/L018241/1] Funding Source: UKRI
  19. ICREA Funding Source: Custom
  20. Div Of Information & Intelligent Systems
  21. Direct For Computer & Info Scie & Enginr [1355632] Funding Source: National Science Foundation

向作者/读者索取更多资源

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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