How many replicates of arrays are required to detect gene expression changes in microarray experiments? A mixture model approach.
BACKGROUND
It has been recognized that replicates of arrays (or spots) may be necessary for reliably detecting differentially expressed genes in microarray experiments. However, the often-asked question of how many replicates are required has barely been addressed in the literature. In general, the answer depends on several factors: a given magnitude of expression change, a desired statistical power (that is, probability) to detect it, a specified Type I error rate, and the statistical method being used to detect the change. Here, we discuss how to calculate the number of replicates in the context of applying a nonparametric statistical method, the normal mixture model approach, to detect changes in gene expression.


RESULTS
The methodology is applied to a data set containing expression levels of 1,176 genes in rats with and without pneumococcal middle-ear infection. We illustrate how to calculate the power functions for 2, 4, 6 and 8 replicates.


CONCLUSIONS
The proposed method is potentially useful in designing microarray experiments to discover differentially expressed genes. The same idea can be applied to other statistical methods.
Pan
Wei
W
Division of Biostatistics, School of Public Health, University of Minnesota, 420 Delaware Street, Minneapolis, MN 55455-0378, USA. weip@biostat.umn.edu
Lin
Jizhen
J
Le
Chap T
CT
D000818:Animals; D020869:Gene Expression Profiling / Q000379:methods* / Q000592:standards / Q000706:statistics & numerical data*; D005786:Gene Expression Regulation / Q000235:genetics; D008957:Models, Genetic; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods* / Q000592:standards / Q000706:statistics & numerical data*; D010033:Otitis Media / Q000276:immunology / Q000382:microbiology; D011008:Pneumococcal Infections / Q000235:genetics / Q000276:immunology; D051381:Rats; D013296:Streptococcus pneumoniae / Q000276:immunology