The effect of replication on gene expression microarray experiments.
BACKGROUND
We examine the effect of replication on the detection of apparently differentially expressed genes in gene expression microarray experiments. Our analysis is based on a random sampling 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.


RESULTS
While dependent on the data source, our findings suggest that stable results are typically not obtained until at least five biological replicates have been used. 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.
Pavlidis
Paul
P
Columbia Genome Center, Columbia University, 1150 St Nicholas Avenue, New York, NY 10032, USA. pp175@columbia.edu
Li
Qinghong
Q
Noble
William Stafford
WS
D000818:Animals; D004261:DNA Replication / Q000235:genetics; D003627:Data Interpretation, Statistical; D030561:Databases, Nucleic Acid; D020869:Gene Expression Profiling / Q000379:methods*; D006801:Humans; D008957:Models, Genetic; D015233:Models, Statistical; D009369:Neoplasms / Q000235:genetics; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D011786:Quality Control; D015203:Reproducibility of Results; D012107:Research Design; D018401:Sample Size; D012680:Sensitivity and Specificity; D016415:Sequence Alignment / Q000379:methods*; D017422:Sequence Analysis, DNA / Q000379:methods