ArticlePloS one2014
A phylogeny-based benchmarking test for orthology inference reveals the limitations of function-based validation.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 16 citations in OpenAlex.
- In silico analysis of Ffp1, an ancestral Porphyromonas spp. fimbrillin, shows differences with Fim and Mfa.Access microbiology · 2024Article
- Benchmarking Orthogroup Inference Accuracy: Revisiting Orthobench.Genome biology and evolution · 2020Article
- The Quest for Orthologs benchmark service and consensus calls in 2020.Nucleic acids research · 2020Article
- eggNOG 5.0: a hierarchical, functionally and phylogenetically annotated orthology resource based on 5090 organisms and 2502 viruses.Nucleic acids research · 2019Article
- Multilevel comparative bioinformatics to investigate evolutionary relationships and specificities in gene annotations: an example for tomato and grapevine.BMC bioinformatics · 2018Article
- Knowledge Discovery in Biological Databases for Revealing Candidate Genes Linked to Complex Phenotypes.Journal of integrative bioinformatics · 2017Review
- Functional Annotations of Paralogs: A Blessing and a Curse.Life (Basel, Switzerland) · 2016Article
- eggNOG 4.5: a hierarchical orthology framework with improved functional annotations for eukaryotic, prokaryotic and viral sequences.Nucleic acids research · 2016Article
- Inferring Orthologs: Open Questions and Perspectives.Genomics insights · 2016Review
- Quest for Orthologs Entails Quest for Tree of Life: In Search of the Gene Stream.Genome biology and evolution · 2015Article
- Archaeal Clusters of Orthologous Genes (arCOGs): An Update and Application for Analysis of Shared Features between Thermococcales, Methanococcales, and Methanobacteriales.Life (Basel, Switzerland) · 2015Article
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Authors and funding
7 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Accurate orthology prediction is crucial for many applications in the post-genomic era. The lack of broadly accepted benchmark tests precludes a comprehensive analysis of orthology inference. So far, functional annotation between orthologs serves as a performance proxy. However, this violates the fundamental principle of orthology as an evolutionary definition, while it is often not applicable due to limited experimental evidence for most species. Therefore, we constructed high quality "gold standard" orthologous groups that can serve as a benchmark set for orthology inference in bacterial species. Herein, we used this dataset to demonstrate 1) why a manually curated, phylogeny-based dataset is more appropriate for benchmarking orthology than other popular practices and 2) how it guides database design and parameterization through careful error quantification. More specifically, we illustrate how function-based tests often fail to identify false assignments, misjudging the true performance of orthology inference methods. We also examined how our dataset can instruct the selection of a "core" species repertoire to improve detection accuracy. We conclude that including more genomes at the proper evolutionary distances can influence the overall quality of orthology detection. The curated gene families, called Reference Orthologous Groups, are publicly available at http://eggnog.embl.de/orthobench2.
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