OMA standalone: orthology inference among public and custom genomes and transcriptomes

Adrian M. Altenhoff , Jeremy Levy , Magdalena Zarowiecki , Bartłomiej Tomiczek , Alex Warwick Vesztrocy , Daniel A. Dalquen , Steven Müller , Maximilian J. Telford , Natasha M. Glover , David Dylus , Christophe Dessimoz


Genomes and transcriptomes are now typically sequenced by individual laboratories but analyzing them often remains challenging. One essential step in many analyses lies in identifying orthologs—corresponding genes across multiple species— but this is far from trivial. The Orthologous MAtrix (OMA) database is a leading resource for identifying orthologs among publicly available, complete genomes. Here, we describe the OMA pipeline available as a standalone program for Linux and Mac. When run on a cluster, it has native support for the LSF, SGE, PBS Pro, and Slurm job schedulers and can scale up to thousands of parallel processes. Another key feature ofOMAstandalone is that users can combine their own data with existing public data by exporting genomes and precomputed alignments from the OMA database, which currently contains over 2100 complete genomes. We compare OMA standalone to other methods in the context of phylogenetic tree inference, by inferring a phylogeny of Lophotrochozoa, a challenging clade within the protostomes. We also discuss other potential applications of OMA standalone, including identifying gene families having undergone duplications/ losses in specific clades, and identifying potential drug targets in nonmodel organisms. OMA standalone is available under the permissive open source Mozilla Public License Version 2.0.
Author Adrian M. Altenhoff
Adrian M. Altenhoff,,
, Jeremy Levy
Jeremy Levy,,
, Magdalena Zarowiecki
Magdalena Zarowiecki,,
, Bartłomiej Tomiczek (IFB / M020 / DMCB)
Bartłomiej Tomiczek,,
- Department of Molecular and Cellular Biology
, Alex Warwick Vesztrocy
Alex Warwick Vesztrocy,,
, Daniel A. Dalquen
Daniel A. Dalquen,,
, Steven Müller
Steven Müller,,
, Maximilian J. Telford
Maximilian J. Telford,,
, Natasha M. Glover
Natasha M. Glover,,
, David Dylus
David Dylus,,
et al.`
Journal seriesGenome Research, ISSN 1088-9051, (N/A 200 pkt)
Issue year2019
Publication size in sheets0.55
ASJC Classification2716 Genetics(clinical); 1311 Genetics
Languageen angielski
LicenseOther; published final; Uznanie Autorstwa (CC-BY); with publication
Score (nominal)200
Score sourcejournalList
ScoreMinisterial score = 200.0, 28-01-2020, ArticleFromJournal
Publication indicators Scopus SNIP (Source Normalised Impact per Paper): 2018 = 2.462; WoS Impact Factor: 2018 = 9.944 (2) - 2018=11.638 (5)
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