Sample size calculation with dependence adjustment for FDR-control in microarray studies.

DNA microarrays have been widely used for the purpose of simultaneously monitoring a large number of gene expression levels to identify differentially expressed genes. Statistical methods for the adjustment of multiple testing have been discussed extensively in the literature. An important further challenge is the existence of dependence among test statistics due to reasons such as gene co-regulation. To plan large-scale genomic studies, sample size determination with appropriate adjustment for both multiple testing and potential dependency among test statistics is crucial to avoid an abundance of false-positive results and/or serious lack of power. We introduce a general approach for calculating sample sizes for two-way multiple comparisons in the presence of dependence among test statistics to ensure adequate overall power when the false discovery rates are controlled. The usefulness of the proposed method is demonstrated via numerical studies using both simulated data and real data from a well-known study of leukaemia.