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Standardized benchmarking in the quest for orthologs


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.

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.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Molecular Life Sciences
08 University Research Priority Programs > Evolution in Action: From Genomes to Ecosystems
Dewey Decimal Classification:570 Life sciences; biology
Language:English
Date:May 2016
Deposited On:11 Jan 2017 16:35
Last Modified:06 Aug 2017 01:25
Publisher:Nature Publishing Group
ISSN:1548-7091
Free access at:PubMed ID. An embargo period may apply.
Publisher DOI:https://doi.org/10.1038/nmeth.3830
PubMed ID:27043882

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Licence: Creative Commons: Attribution 3.0 Unported (CC BY 3.0)