Orthologous Matrix (OMA) algorithm 2.0: more robust to asymmetric evolutionary rates and more scalable hierarchical orthologous group inference. 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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References in zbMATH (referenced in 2 articles )
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- Geiß, Manuela; Stadler, Peter F.; Hellmuth, Marc: Reciprocal best match graphs (2020)
- Geiß, Manuela; Chávez, Edgar; González Laffitte, Marcos; López Sánchez, Alitzel; Stadler, Bärbel M. R.; Valdivia, Dulce I.; Hellmuth, Marc; Hernández Rosales, Maribel; Stadler, Peter F.: Best match graphs (2019)