Orthologous Matrix (OMA) algorithm 2.0: more robust to asymmetric evolutionary rates and more scalable hierarchical orthologous group inference
Open accessAbstract
Motivation: Accurate orthology inference is a fundamental step in many phylogenetics and comparative analysis. Many methods have been proposed, including OMA (Orthologous MAtrix). Yet substantial challenges remain, in particular in coping with fragmented genes or genes evolving at different rates after duplication, and in scaling to large datasets. With more and more genomes available, it is necessary to improve the scalability and robustness of orthology inference methods. Results: We present improvements in the OMA algorithm: (i) refining the pairwise orthology inference step to account for same-species paralogs evolving at different rates, and (ii) minimizing errors in the pairwise orthology verification step by testing the consistency of pairwise distance estimates, which can be problematic in the presence of fragmentary sequences. In addition we introduce a more scalable procedure for hierarchical orthologous group (HOG) clustering, which are several orders of magnitude faster on large datasets. Using the Quest for Orthologs consortium orthology benchmark service, we show that these changes translate into substantial improvement on multiple empirical datasets. Availability and Implementation: This new OMA 2.0 algorithm is used in the OMA database (http://omabrowser.org) from the March 2017 release onwards, and can be run on custom genomes using OMA standalone version 2.0 and above (http://omabrowser.org/standalone).
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Graph-based methods cluster genes into pairs or groups of orthologs based on pairwise sequence similarity such as reciprocal best alignment hits.
“Graph-based methods cluster genes into pairs or groups of orthologs based on pairwise sequence similarity such as (reciprocal) best alignment hits (8–12).”
From Integrating gene annotation with orthology inference at scale (2023) · cites this paper as [9]
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Integrating gene annotation with orthology inference at scale
Kirilenko, B. M., Munegowda, C., Osipova, E., Jebb, D., Sharma, V., Blumer, M., Morales, A. E., Ahmed, A.-W., Kontopoulos, D.-G., Hilgers, L., et al. (2023) · Science · doi:10.1126/science.abn3107 · Cited by 209 · see citing works
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Self-citationAdvances and Applications in the Quest for Orthologs
Glover, N., Dessimoz, C., Ebersberger, I., Forslund, S. K., Gabaldón, T., Huerta-Cepas, J., Martin, M.-J., Muffato, M., Patricio, M., Pereira, C., et al. (2019) · Molecular Biology and Evolution · doi:10.1093/molbev/msz150 · Cited by 94 · see citing works
Self-citation
- Authors
- Train, C.-M., Glover, N. M., Gonnet, G. H., Altenhoff, A. M., & Dessimoz, C.
- Affiliations
- SIB Swiss Institute of Bioinformatics (CH)
- Department of Computer Science, ETH Zurich, Zurich, Switzerland
- Corresponding author
- Altenhoff, Adrian M
- Dessimoz, Christophe
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2017-07-12
- Volume
- 33
- Issue
- 14
- Pages
- i75-i82
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- PMC
- PMC5870696
- OpenAlex
- W2734735318
- Cited by
- 96
- References
- 2
- Citations by year
- 2026: 3 · 2025: 5 · 2024: 8 · 2023: 7 · 2022: 16 · 2021: 11 · 2020: 14 · 2019: 18 · 2018: 13 · 2017: 1
- FWCI
- 5.01
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Bioinformatics (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- SERVAL (Université de Lausanne) (publishedVersion, cc-by-nc)
- Repository for Publications and Research Data (ETH Zurich) (publishedVersion, cc-by-nc)
- RERO DOC (Universität Bern) (submittedVersion)
- IRIS (submittedVersion, cc-by-nc)
- UCL Discovery (University College London) (submittedVersion)
- ETH Zürich Research Collection
- Funders
- National Science Foundation
- University College London
- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (150654, BB/M015009/1)
- Swiss Institute of Bioinformatics
- Biotechnology and Biological Sciences Research Council (BB/M015009/1)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Agricultural and Biological Sciences › Plant Science › Chromosomal and Genetic Variations
- Keywords
- orthology inference, paralogs, gene duplication
- MeSH terms
- Algorithms, Animals, Humans, Mammals, Phylogeny, Software, Evolution, Molecular, Genomics, Mutation Rate
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