Naoki Sato1. 1. 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.
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.