Submitted on May 5, 2004
Accepted on February 11, 2005
A meta-clustering analysis indicates distinct pattern alteration between two series of Gene Expression profiles for induced ischemic tolerance in rats
Makoto Kano1*, Shuichi Tsutsumi2, Nobutaka Kawahara3, Yan Wang4, Akitake Mukasa5, Takaaki Kirino3, and Hiroyuki Aburatani2
1 Intelligent Cooperative System, Department of Information Systems, Research Center for Advanced Science and Technology, University of Tokyo, Bunkyo-ku, Tokyo, Japan
2 Genome Science Division, Research Center for Advanced Science and Technology, University of Tokyo, Meguro-ku, Tokyo, Japan
3 Department of Neurosurgery, Faculty of Medicine, University of Tokyo, Bunkyo-ku, Tokyo, Japan; SORST (Solution-Oriented Research for Science and Technology) / JST(Japan Science and Technology), Kawaguchi, Saitama, Japan
4 Department of Neurosurgery, Faculty of Medicine, University of Tokyo, Bunkyo-ku, Tokyo, Japan
5 Genome Science Division, Research Center for Advanced Science and Technology, University of Tokyo, Meguro-ku, Tokyo, Japan; Department of Neurosurgery, Faculty of Medicine, University of Tokyo, Bunkyo-ku, Tokyo, Japan
* To whom correspondence should be addressed. E-mail: mkano{at}cyber.rcast.u-tokyo.ac.jp.
We have developed a visualization methodology, called a Cluster Overlap Distribution Map (CODM), for comparing the clustering results of time-series gene expression profiles generated under two different conditions. Although various clustering algorithms for gene expression data have been proposed, there are few effective methods to compare clustering results for different conditions. Using CODM, the utilization of three-dimensional space and color allows intuitive visualization of changes in cluster set composition, changes in the expression patterns of genes between the two conditions, and relationship with other known gene information, such as transcription factors. We applied CODM to time-series gene expression profiles obtained from Rat 4-vessel occlusion models combined with systemic hypotension and time-matched sham control animals (with sham operation), identifying distinct pattern alteration between the two. Comparison of dynamic changes of time series gene expression levels under different conditions are important in various fields of gene expression profiling analysis, including toxicogenomics and pharmacogenomics. CODM will be valuable for various types of analyses within these fields since it integrates and simultaneously visualizes various types of information across clustering results.
