David M. Rocke
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Measurement Errors and Data Transformation for Gene Expression Data, Proteomics Data, and Metabolomics Data

David M. Rocke,
Department of Applied Science (College of Engineering), Division of Biostatistics (School of Medicine), and Center for Image Processing and Integrated Computing University of California, Davis

Gene expression microarrays comprise a suite of related technologies for measuring the expression of thousands of genes simultaneously from a single biological sample. There are also numerous other high-throughput biological assays that can measure large numbers of proteins, lipids, and other biologically active compounds. In this talk, I will describe an important statistical challenge in the use of such data. Using raw data, logarithms, or ratios, the variability of the measurements is strongly dependent on the level of expression, causing a failure of the assumptions of most standard methods of statistical analysis. We present a solution to this problem via a specially tuned data transformation.

Graybill Conference
June 18-20, 2003
University Park Holiday Inn
Fort Collins, CO 80526
email: hari@stat.colostate.edu Fax: (970)491-7895 Phone: (970)491-5269
Last Updated: Wednesday, March 12, 2003