Bioinformatics. 2009 Mar 1;25(5):599-605. Epub 2009 Jan 21.

Gclust: trans-kingdom classification of proteins using automatic individual threshold setting.

Source

Department of Life Sciences, Graduate School of Arts and Sciences, University of Tokyo, Komaba, Meguro-ku, Tokyo, 153-8902, Japan. naokisat@bio.c.u-tokyo.ac.jp

Abstract

MOTIVATION:

Trans-kingdom protein clustering remained difficult because of large sequence divergence between eukaryotes and prokaryotes and the presence of a transit sequence in organellar proteins. A large-scale protein clustering including such divergent organisms needs a heuristic to efficiently select similar proteins by setting a proper threshold for homologs of each protein. Here a method is described using two similarity measures and organism count.

RESULTS:

The Gclust software constructs minimal homolog groups using all-against-all BLASTP results by single-linkage clustering. Major points include (i) estimation of domain structure of proteins; (ii) exclusion of multi-domain proteins; (iii) explicit consideration of transit peptides; and (iv) heuristic estimation of a similarity threshold for homologs of each protein by entropy-optimized organism count method. The resultant clusters were evaluated in the light of power law. The software was used to construct protein clusters for up to 95 organisms.

AVAILABILITY:

Software and data are available at http://gclust.c.u-tokyo.ac.jp/Gclust_Download.html.

PMID:: 19158159; [PubMed - indexed for MEDLINE]

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Research Support, Non-U.S. Gov't

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Proteins

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