A simple method for assessing sample sizes in microarray experiments.
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.


CONCLUSIONS
Our method seems to be useful for sample size assessment in microarray experiments.
Tibshirani
Robert
R
Health Research & Policy, Stanford University, Stanford, CA 94305, USA. tibs@stanford.edu
D003198:Computer Simulation; D008957:Models, Genetic; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D018401:Sample Size