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This is the preliminary program for the 2007 Joint Statistical Meetings in Salt Lake City, Utah.

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Activity Number: 285
Type: Contributed
Date/Time: Tuesday, July 31, 2007 : 10:30 AM to 12:20 PM
Sponsor: Biopharmaceutical Section
Abstract - #309387
Title: Microarray Experiments for Pharmacogenomics
Author(s): Youlan Rao*+ and Yoonkyung Lee and Jane Chang and Tao Wang and Jason C. Hsu
Companies: The Ohio State University and The Ohio State University and Bowling Green State University and University of South Florida and The Ohio State University
Address: 1958 Neil Avenue, Columbus, OH, 43210,
Keywords: Microarrays ; prognostics ; mixed linear model ; multiple testing ; classification ; sample size
Abstract:

The development of a microarray for clinical prognosis is envisioned as a two-stage process. The first stage is to find marker genes and train a prognostic algorithm based on data with known disease outcomes. The second stage is to validation the prediction algorithm using arrays with marker genes only. In this talk, we show that if a microarray experiment is designed according to statistical principles to avoid bias and allow the variance components of subject, sample, and noise to be estimated separately, then sample sizes of subject, samples within subject, and replication of probes can conceptually be computed to meet prespecified sensitivity and specificity requirements of the device.

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Revised September, 2007