Statistical issues in microarray data analysis

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Microarrays are a new technology for measuring the relative expression levels of thousands of genes simultaneously. They allow medical researchers to take a genome-wide look at which genes are active in a particular tissue type in an organism at a particular time. Many biomedical and biological research groups in Australia have recently untaken microarray experiments for the first time or are planning microarray experiments in the near future. Microarray experiments produce massive amounts of information and the study of how to extract this information is still in a fledgling state. This project will solve a number of fundamental problems in microarray data analysis. The emphasis is not on special methods of down-stream analysis but on basic issues which are common to all microarray experiments. The project will determine how tissue samples from different organisms should be combined in complex experiments. It will develop methods for evaluating the quality of results from microarray experiments. It will make microarray analysis less sensitive to production artifacts. It will make novel use of serial analysis of gene expression (SAGE), a more accurate but more expensive and less available technology, to calibrate the results of microarray experiments. The results will be applied during the lifetime of the project to a number of experiments at the Walter and Eliza Hall Institute and the University of Melbourne on blood cell development, cell growth and proliferation, resistance to malaria and leishmaniasis parasites, and Down syndrome.