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

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Version: Final published version
License: CC BY-NC 4.0
Serval ID
serval:BIB_7D03376859BC
Type
Article: article from journal or magazin.
Collection
Publications
Title
Orthologous Matrix (OMA) algorithm 2.0: more robust to asymmetric evolutionary rates and more scalable hierarchical orthologous group inference
Journal
Bioinformatics
Author(s)
Train C.-M., Glover N.M., Gonnet G.H., Altenhoff A.M., Dessimoz C.
ISSN
1460-2059
ISSN-L
1367-4803
Publication state
Published
Issued date
2017
Volume
33
Number
14
Pages
i75-i82
Language
english
Abstract
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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Open Access
Yes
Create date
27/07/2017 13:13
Last modification date
29/05/2019 7:09
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