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Inferring hierarchical orthologous groups from orthologous gene pairs.

Altenhoff, AM; Gil, M; Gonnet, GH; Dessimoz, C; (2013) Inferring hierarchical orthologous groups from orthologous gene pairs. PLoS One , 8 (1) , Article e53786. 10.1371/journal.pone.0053786. Green open access

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Abstract

Hierarchical orthologous groups are defined as sets of genes that have descended from a single common ancestor within a taxonomic range of interest. Identifying such groups is useful in a wide range of contexts, including inference of gene function, study of gene evolution dynamics and comparative genomics. Hierarchical orthologous groups can be derived from reconciled gene/species trees but, this being a computationally costly procedure, many phylogenomic databases work on the basis of pairwise gene comparisons instead ("graph-based" approach). To our knowledge, there is only one published algorithm for graph-based hierarchical group inference, but both its theoretical justification and performance in practice are as of yet largely uncharacterised. We establish a formal correspondence between the orthology graph and hierarchical orthologous groups. Based on that, we devise GETHOGs ("Graph-based Efficient Technique for Hierarchical Orthologous Groups"), a novel algorithm to infer hierarchical groups directly from the orthology graph, thus without needing gene tree inference nor gene/species tree reconciliation. GETHOGs is shown to correctly reconstruct hierarchical orthologous groups when applied to perfect input, and several extensions with stringency parameters are provided to deal with imperfect input data. We demonstrate its competitiveness using both simulated and empirical data. GETHOGs is implemented as a part of the freely-available OMA standalone package (http://omabrowser.org/standalone). Furthermore, hierarchical groups inferred by GETHOGs ("OMA HOGs") on >1,000 genomes can be interactively queried via the OMA browser (http://omabrowser.org).

Type: Article
Title: Inferring hierarchical orthologous groups from orthologous gene pairs.
Location: United States
Open access status: An open access version is available from UCL Discovery
DOI: 10.1371/journal.pone.0053786
Publisher version: http://dx.doi.org/10.1371/journal.pone.0053786
Language: English
Additional information: © 2013 Altenhoff et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. PMCID: PMC3544860
Keywords: Algorithms, Databases, Genetic, Genomics, Phylogeny, Sequence Homology, Nucleic Acid
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences > Genetics, Evolution and Environment
URI: http://discovery.ucl.ac.uk/id/eprint/1404292
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