Cluster overlap distribution map: visualization for gene expression analysis using immersive projection technology

Authors:
Makoto Kano;Kunihiro Nishimura;Shuichi Tsutsumi;Hiroyuki Aburatani;Koichi Hirota;Michitaka Hirose
Affiliations:
School of Engineering, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655 Japan;School of Information Science and Technology, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan;Genome Science Division Research, Center for Advanced Science and Technology, University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8904, Japan;Genome Science Division Research, Center for Advanced Science and Technology, University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8904, Japan;Intelligent Cooperative System, Department of Information Systems, Research Center for Advanced Science and Technology, University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8904, Japan;Intelligent Cooperative System, Department of Information Systems, Research Center for Advanced Science and Technology, University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8904, Japan
Venue:
Presence: Teleoperators and Virtual Environments - special issue: IEEE virtual reality 2002 conference
Year:
2003

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Abstract

In this paper, we discuss possible applications of virtual reality technologies, such as immersive projection technology (IPT), in the field of genome science, and propose cluster-oriented visualization that attaches importance to data separation of large gene data sets with multiple variables. Based on these strategies, we developed the cluster overlap distribution map (CDCM), which is a visualization methodology using IPT for pairwise comparison between cluster sets generated from different gene expression data sets. This methodology effectively provides the user with indications of gene clusters that are worth a close examination. In addition, by using the plate window manager system, which enables the user to manipulate existing 2D GUI applications in the virtual 3D space, we developed the virtual environment for the comprehensive analysis from providing the indications to further examination by referring to the database on Web sites. Our system was applied in the comparison between the gene expression data sets of hepatocellular carcinomas and hepatoblastomas, and the effectiveness of the system was confirmed.