OMA 2011: orthology inference among 1000 complete genomes

By Adrian M. Altenhoff, Adrian Schneider, Gaston H. Gonnet, Christophe Dessimoz. 2010

228 citations recorded by the source corpus.

OMA (Orthologous MAtrix) is a database that identifies orthologs among publicly available, complete genomes. Initiated in 2004, the project is at its 11th release. It now includes 1000 genomes, making it one of the largest resources of its kind. Here, we describe recent developments in terms of species covered; the algorithmic pipeline—in particular regarding the treatment of alternative splicing, and new features of the web (OMA Browser) and programming interface (SOAP API). In the second part, we review the various representations provided by OMA and their typical applications. The database is publicly accessible at http://omabrowser.org.

Subfields: Artificial Intelligence, Molecular Biology

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Citations in the corpus

OrthoFinder: solving fundamental biases in whole genome comparisons dramatically improves orthogroup inference accuracy (2015, methodology): “5 1 F ra ct io n A OrthoMCL 2 3 B OrthoMCL (normalised scores) 2 3 C OrthoFinder Recall PrecisionF-score 0.0 0.2 0.4 0.6 0.8 1.0 F ra ct io n D F-score E Recall F Precision T TreeFam OrthoFinder eggNOG OrthoMCL OrthoDB OMA F ra ct io n F ra ct io n 4 10 log (length) 4 10 log (length) 4 10 Fig.”
eggNOG v4.0: nested orthology inference across 3686 organisms (2013, background): “Certain orthology resources are, as a result, specialized in identifying and reconstructing such families of single-copy orthologs (59,60).”
Ensembl comparative genomics resources (2016, background): “For instance, OMA offers orthology predictions for a much broader set of species (1850 in the 18th release) (21).”
The OMA orthology database in 2015: function predictions, better plant support, synteny view and other improvements (2014, methodology): “If multiple splicing variants are possible, the best one in terms of matches with other genomes is selected, which is not necessarily the longest one (15).”
Orthology Inference in Nonmodel Organisms Using Transcriptomes and Low-Coverage Genomes: Improving Accuracy and Matrix Occupancy for Phylogenomics (2014, background): “A number of other alternative orthology inference pipelines also suffer from using similarity measurements as approximations to directly infer orthology (Li et al. 2003; Roure et al. 2007; Schreiber et al. 2009; Altenhoff et al. 2011, 2013).”
OrthoDB: a hierarchical catalog of animal, fungal and bacterial orthologs (2012, background): “(7,8) have embraced this concept and now provide orthology classifications at several major radiations across the tree of life.”
The OMA orthology database in 2018: retrieving evolutionary relationships among all domains of life through richer web and programmatic interfaces (2017, unknown): “OMA (‘Orthologous Matrix’) distinguishes itself through high-quality orthology inferences, a broad coverage of all three domains of life, feature-rich web interface, availability of data in a wide range of formats and interfaces, and a frequent update schedule of two releases per year (14,17).”
GET_HOMOLOGUES, a Versatile Software Package for Scalable and Robust Microbial Pangenome Analysis (2013, background): “of OMA (Orthologous Matrix), a database that identifies orthologues among publicly available, complete genomes (10).”
Genenames.org: the HGNC resources in 2015 (2014, methodology): “HCOP currently collates orthology assertions from eggNOG (34), Ensembl Compara (2), HGNC, HomoloGene (31), InParanoid (35), OMA (36), OrthoDB (37), OrthoMCL (38), PANTHER (39), PhylomeDB (40), Treefam (41) and ZFIN (18) into a single tool, enabling comparison of these data to identify a consensus or”
Ensembl comparative genomics resources (2016, background): “It also offers OMA stand-alone, which is designed for the analysis on any set of genomes in a local environment.”