The effect of replication on gene expression microarray experiments
Paul Pavlidis, Qinghong Li and William Stafford Noble
Bioinformatics. 19(13):1620-1627, 2003.
Abstract
We examined the effect of replication on the detection of apparently differentially expressed genes in gene expression microarray experiments. Our analysis is based on a random subsampling approach using real data sets from 16 published studies. We consider both the ability to find genes that meet particular statistical criteria as well as the stability of the results in the face of changing levels of replication. While dependent on the data source, our findings suggest that stable results are typically not obtained until at least 5 replicates have been used, and power is typically low. Conversely, for most studies, 10-15 replicates yield results that are quite stable, and there is less improvement in stability as the number of replicates is further increased. Our methods will be of use in evaluating existing data sets and in helping to design new studies.
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