Background: In this short article, we discuss a simple method for assessing sample size requirements in microarray experiments.
Results: Our method starts with the output from a permutation-based analysis for a set of pilot data, e.g. from the SAM package. Then for a given hypothesized mean difference and various samples sizes, we estimate the false discovery rate and false negative rate of a list of genes; these are also interpretable as per gene power and type I error. We also discuss application of our method to other kinds of response variables, for example survival outcomes.
Conclusion: Our method seems to be useful for sample size assessment in microarray experiments.