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1 School of Engineering, University of Tokyo, Bunkyo-ku, Tokyo, Japan
2 School of Information Science and Technology, University of Tokyo, Bunkyo-ku, Tokyo, Japan
3 Genome Science Division, Research Center for Advanced Science and Technology, University of Tokyo, Meguro-ku, Tokyo, Japan
4 Intelligent Cooperative System, Department of Information Systems, Research Center for Advanced Science and Technology, University of Tokyo, Meguro-ku, Tokyo, Japan
* To whom correspondence should be addressed. E-mail: mkano{at}cyber.rcast.u-tokyo.ac.jp.
We describe the development of a new visualization method, called the Expression Imbalance Map (EIM), for detecting mRNA expression imbalance regions, reflecting genomic losses and gains at a much higher resolution than conventional technologies such as comparative genomic hybridization (CGH). Simple spatial mapping of the microarray expression profiles on chromosomal location provides little information about genomic structure, because mRNA expression levels do not completely reflect genomic copy number and some microarray probes would be of low quality. The EIM, which does not employ arbitrary selection of thresholds in conjunction with hypergeometric distribution-based algorithm, has a high tolerance of these complex factors. The EIM could detect regionally under- or over-expressed genes (called, here, an expression imbalance region) in lung cancer specimens from their gene expression data of oligonucleotide microarray. Many known as well as potential loci with frequent genomic losses or gains were detected as expression imbalance regions by the EIM. Therefore, the EIM should provide the user with further insight into genomic structure through mRNA expression.
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