Self-organizing Clustering: Non-hierarchical Clustering for Large Scale DNA Sequence Data

Abstract

Recently, clustering has been recognized as an important and fundamental method that analyzes and classifies large-scale sequence data to provide useful information. We developed a novel clustering method designated as Self-organizing clustering (SOC) that uses oligonucleotide frequencies for large-scale DNA sequence data. We implemented SOC as a command-line program package, and developed a server that provides access to it enabling visualization of the results.SOC effectively and quickly classifies many sequences that have low or no homology to each other. The command-line program is downloadable at http://rgp.nias.affrc.go.jp/programs/. The on-line web site is publicly accessible at http://rgp.nias.affrc.go.jp/SOC/. The common gateway interface (CGI) for the server is also provided within the package.