Bioinformatics Advance Access published online on January 24, 2006
Bioinformatics, doi:10.1093/bioinformatics/btl009
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1 National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA
* To whom correspondence should be addressed.
Motivation: Determining orthology relations among genes across multiple genomes is an important problem in the post-genomic era. Identifying orthologous genes can not only help predict functional annotations for newly sequenced or poorly characterized genomes, but can also help predict new protein-protein interactions. Unfortunately, determining orthology relation through computational methods is not straightforward due to the presence of paralogs. Traditional approaches have relied on pairwise sequence comparisons to construct graphs, which were then partitioned into putative clusters of orthologous groups. These methods do not attempt to preserve the non-transitivity and hierarchic nature of the orthology relation. Results: We propose a new method, COCO-CL, for hierarchical clustering of homology relations, and identification of orthologous groups of genes. Unlike previous approaches, which are based on pairwise sequence comparisons, our method explores the correlation of evolutionary histories of individual genes in a more global context. COCO-CL can be used as a semi-independent method to delineate the orthology/paralogy relation for a refined set of homologous proteins obtained using a less-conservative clustering approach, or as a refiner that removes putative out-paralogs from clusters computed using a more inclusive approach. We analyze our clustering results manually, with support from literature and functional annotations. Since our orthology determination procedure does not employ a species tree to infer duplication events, it can be used in situations when the species tree is unknown or uncertain. Supplementary information: Supplementary materials are available at Bioinformatics online.
Received October 6, 2005
Revised January 13, 2006
Accepted January 14, 2006
Article
COCO-CL: hierarchical clustering of homology relations based on evolutionary correlations
Raja Jothi 1 *,
Elena Zotenko 2,
Asba Tasneem 3,
and
Teresa M. Przytycka 1
2 National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA; Department of Computer Science, University of Maryland, College Park, MD 20742, USA
3 Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
Raja Jothi, E-mail: jothi{at}mail.nih.gov
Abstract
Associate Editor: Martin Bishop
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