OMA in a nutshell (Introduction) Web based database interface for orthology prediction

The OMA (“Orthologous MAtrix”) project is a method and database for the inference of orthologs among complete genomes.

The distinctive features of OMA are its:

• Broad scope and size
• High quality of inferences
• Feature-rich web interface
• Availability of data in a wide range of formats and interfaces
• Frequent update schedule of two releases per year

The OMA pipeline can also run on custom genomic/transcriptomic data using the OMA stand-alone software, and it is even possible to combine precomputed data with custom data by exporting parts of the OMA database.

The OMA project was initiated in 2004 at ETH Zurich by Prof. Gaston Gonnet, with the goal of identifying orthologs among all publicly available genomes. At the time, most sequenced genomes were bacteria and only few were eukaryotes. Several PhD students in his group became increasingly involved, in particular Adrian Schneider, Christophe Dessimoz, and Alexander Roth. Over the subsequent 15 years, OMA underwent 24 major releases, steadily increasing the number of genomes under consideration.

The OMA Browser was introduced in 2006. Early releases were developed by Adrian Schneider and Christophe Dessimoz. Adrian Altenhoff joined the team in 2008.

In 2008, the responsibility of “baby-sitting” the all-against-all (i.e. importing and converting genomes, running and verifying computations across hundreds of CPUs) was handed over from Gaston to the two Adrians.

Since 2010, Adrian Altenhoff has been the main baby-sitter of the all-against-all and manager of OMA’s operations. In 2011, Christophe joined Gaston as co-PI of OMA. In 2012, OMA became a SIB-funded bioinformatics resource.

OMA’s inference algorithm consists of three main phases. First, to infer homologous sequences (sequences of common ancestry), all-against-all Smith-Waterman alignments are computed and significant matches are retained. Second, to infer orthologous pairs (the subset of homologs related by speciation events), mutually closest homologs are identified based on evolutionary distances , taking into account distance inference uncertainty and the possibility for differential gene losses (for more details, see Roth et al 2008). Third, these orthologs are clustered in two different ways, which are useful for different purposes:

• We identify cliques of orthologous pairs (“OMA groups” ), which are useful as marker genes for phylogenetic reconstruction and tend to be very specific;
• We identify hierarchical orthologous groups (“HOGs”), groups of genes defined for particular taxonomic ranges and identify all genes that have descended from a common ancestral gene in that taxonomic range.

More details on the algorithm

• How to Identify Orthologs with OMA: A Primer (Zahn-Zabal et al. 2020)
• Inferring HOGs (Altenhoff et al. 2013)
• Updates to the OMA algorithm (Train et al. 2017)
• Initial OMA algorithm (Roth et al. 2008)

For more info on the features of the OMA Browser, please consult the help pages accessible from the navigation bar in the top-right corner.

OMA overview

Adrian M Altenhoff, Clément-Marie Train, Kimberly J Gilbert, Ishita Mediratta, Tarcisio Mendes de Farias, David Moi, Yannis Nevers, Hale-Seda Radoykova, Victor Rossier, Alex Warwick Vesztrocy, Natasha M Glover, Christophe Dessimoz
OMA orthology in 2021: website overhaul, conserved isoforms, ancestral gene order and more
Nucleic Acids Research, gkaa1007 Full text

Adrian M Altenhoff, Natasha M Glover, Clément-Marie Train, Klara Kaleb, Alex Warwick Vesztrocy, David Dylus, Tarcisio Mendes de Farias, Karina Zile, Charles Stevenson, Jiao Long, Henning Redestig, Gaston H Gonnet and Christophe Dessimoz
The OMA orthology database in 2018: retrieving evolutionary relationships among all domains of life through richer web and programmatic interfaces
Nucleic Acids Research, 2018, 46 (D1): D477-D485 Full text

Adrian M. Altenhoff, Nives Škunca, Natasha Glover, Clément-Marie Train, Anna Sueki, Ivana Piližota, Kevin Gori, Bartlomiej Tomiczek, Steven Müller, Henning Redestig, Gaston H Gonnet and Christophe Dessimoz
The OMA orthology database in 2015: function predictions, better plant support, synteny view, and other improvements
Nucleic Acids Research, 2015, 43 (D1): D240-D249 Full text

Adrian M. Altenhoff, Adrian Schneider, Gaston H. Gonnet, Christophe Dessimoz
OMA 2011: Orthology Inference Among 1,000 Complete Genomes
Nucleic Acids Research, 2011, 39 (suppl 1): D289-D294 Full text

Adrian Schneider, Christophe Dessimoz, Gaston H. Gonnet
OMA Browser - Exploring orthologous relations across 352 complete genomes
Bioinformatics, 2007, 23:16 (pp. 2180-2182) Project page Full text

OMA algorithm

Natasha M. Glover, Adrian Altenhoff, Christophe Dessimoz
Assigning confidence scores to homoeologs using fuzzy logic PeerJ, 2019, 6, e6231 doi: 10.7717/peerj.6231 Full text

Clément-Marie Train, Natasha M. Glover, Gaston H. Gonnet, Adrian M. Altenhoff, Christophe Dessimoz
Orthologous Matrix (OMA) algorithm 2.0: more robust to asymmetric evolutionary rates and more scalable hierarchical orthologous group inference
Bioinformatics, 2017, 33:14, (pp. i75–i82) Full text

Adrian M. Altenhoff, Manuel Gil, Gaston H. Gonnet, Christophe Dessimoz
Inferring Hierarchical Orthologous Groups From Orthologous Gene Pairs
PLoS One, 2013, 8:1, e53786 Software Full text

Alexander Roth, Gaston H. Gonnet, Christophe Dessimoz
Algorithm of OMA for Large-Scale Orthology Inference
BMC Bioinformatics, 2008, 9:518 Full text (Please note the associated erratum)

Christophe Dessimoz, Brigitte Boeckmann, Alexander Roth, Gaston H. Gonnet
Detecting Non-Orthology in the COGs Database and Other Approaches Grouping Orthologs Using Genome-Specific Best Hits
Nucleic Acids Res, 2006 34:11 (pp. 3309-3316) Full text

Christophe Dessimoz, Gina Cannarozzi, Manuel Gil, Daniel Margadant, Alexander Roth, Adrian Schneider, Gaston H. Gonnet
OMA, a Comprehensive, Automated Project for the Identification of Orthologs from Complete Genome Data: Introduction and First Achievements
RECOMB 2005 Workshop on Comparative Genomics, LNCS 3678 (pp. 61-72) Full text Abstract

Benchmarking

Altenhoff AM, Boeckmann B, Capella-Gutierrez S, Dalquen DA, DeLuca T, Forslund K, Huerta-Cepas J, Linard B, Pereira C, Pryszcz LP, Schreiber F, da Silva AS, Szklarczyk D, Train CM, Bork P, Lecompte O, von Mering C, Xenarios I, Sjölander K, Jensen LJ, Martin MJ, Muffato M; Quest for Orthologs consortium, Gabaldón T, Lewis SE, Thomas PD, Sonnhammer E, Dessimoz C.
Standardized benchmarking in the quest for orthologs
Nat Methods. 2016 May;13(5):425-30. doi: 10.1038/nmeth.3830 Full text

Daniel A. Dalquen, Adrian M. Altenhoff, Gaston H. Gonnet, Christophe Dessimoz
The Impact of Gene Duplication, Insertion, Deletion, Lateral Gene Transfer and Sequencing Error on Orthology Inference: a Simulation Study
PLoS One, 2013, 8:2, e56925 Full text

Brigitte Boeckmann, Marc Robinson-Rechavi, Ioannis Xenarios, Christophe Dessimoz
Conceptual Framework and Pilot Study to Benchmark Phylogenomic Databases Based on Reference Gene Trees
Briefings in Bioinformatics, 2011, 12:5 (pp. 474-484) Full text

Adrian M. Altenhoff and Christophe Dessimoz
Phylogenetic and Functional Assessment of Orthologs Inference Projects and Methods
PLoS Computational Biology, 2009, 5:1, e1000262 Full text

Orthology inference in general

Brigitte Boeckmann, Marc Robinson-Rechavi, Ioannis Xenarios, Christophe Dessimoz
Conceptual Framework and Pilot Study to Benchmark Phylogenomic Databases Based on Reference Gene Trees
Briefings in Bioinformatics, 2011, 12:5 (pp. 474-484) Full text

Adrian M. Altenhoff and Christophe Dessimoz
Phylogenetic and Functional Assessment of Orthologs Inference Projects and Methods
PLoS Computational Biology, 2009, 5:1, e1000262 Full text

Orthology inference in general

Adrian M. Altenhoff and Christophe Dessimoz
Inferring Orthology and Paralogy Evolutionary Genomics: Statistical and Computational methods
(M Anisimova, Editor), Methods in Molecular Biology, 2012, Springer Humana, Vol. 855. Full text Abstract

The OMA Browser is part of the SwissOrthology initiative. SwissOrthology combines a number of Swiss web-resources that are centered around orthology and are funded by SIB.