Practical FDR-based sample size calculations in microarray experiments

Motivation: Owing to the experimental cost and difficulty inobtaining biological materials, it is essential to considerappropriate sample sizes in microarray studies. With the growinguse of the False Discovery Rate (FDR) in microarray analysis,an FDR-based sample size calculation is essential. Method: We describe an approach to explicitly connect the samplesize to the FDR and the number of differentially expressed genesto be detected. The method fits parametric models for degreeof differential expression using the Expectation–Maximizationalgorithm. Results: The applicability of the method is illustrated withsimulations and studies of a lung microarray dataset. We proposeto use a small training set or published data from relevantbiological settings to calculate the sample size of an experiment. Availability: Code to implement the method in the statisticalpackage R is available from the authors. Contact: jhu{at}mdanderson.org