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Bioinformatics Advance Access originally published online on January 24, 2006
Bioinformatics 2006 22(7):779-788; doi:10.1093/bioinformatics/btl009
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Published by Oxford University Press 2006
The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article for non-commercial purposes provided that: the original authorship is properly and fully attributed; the Journal and Oxford University Press are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated. For commercial re-use, please contact journals.permissions@oxfordjournals.org

COCO-CL: hierarchical clustering of homology relations based on evolutionary correlations

Raja Jothi 1,*, Elena Zotenko 1,2, Asba Tasneem 3 and Teresa M. Przytycka 1,*

1National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health Bethesda, MD 20894, USA
2Department of Computer Science, University of Maryland College Park, MD 20742, USA
3Beckman Institute, University of Illinois at Urbana-Champaign Urbana, IL 61801, 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.

Contact: jothi{at}mail.nih.gov, przytyck{at}mail.nih.gov

Supplementary information: Supplementary materials are available at Bioinformatics online.

Received on October 6, 2005; revised on January 13, 2006; accepted on January 14, 2006

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