Orthologous Matrix (OMA) algorithm 2.0: more robust to asymmetric evolutionary rates and more scalable hierarchical orthologous group inference

Détails

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Etat: Public
Version: Final published version
Licence: CC BY-NC 4.0
ID Serval
serval:BIB_7D03376859BC
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Titre
Orthologous Matrix (OMA) algorithm 2.0: more robust to asymmetric evolutionary rates and more scalable hierarchical orthologous group inference
Périodique
Bioinformatics
Auteur(s)
Train C.-M., Glover N.M., Gonnet G.H., Altenhoff A.M., Dessimoz C.
ISSN
1460-2059
ISSN-L
1367-4803
Statut éditorial
Publié
Date de publication
2017
Volume
33
Numéro
14
Pages
i75-i82
Langue
anglais
Résumé
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).

Web of science
Open Access
Oui
Création de la notice
27/07/2017 13:13
Dernière modification de la notice
20/08/2019 15:38
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