| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 3444345 | Annals of Epidemiology | 2012 | 5 Pages |
PurposeMicroarray technology allows for simultaneously screening many genes and determining which gene(s) are differentially expressed in different disease statuses or different cell types. The analysis of variance (ANOVA) (for a K-sample situation with K > 2) can be used in such occasions to gauge statistical significances. However, the test may be underpowered if the diseases under study are heterogeneous.MethodsThe authors propose the “control-only ANOVA” for detecting differentially expressed genes in heterogeneous diseases. Monte-Carlo simulation shows that the test produces quite accurate type I error rates for both normal and non-normal data. The statistical power of the control-only ANOVA is higher than that of the conventional ANOVA when the diseases under study are heterogeneous.ResultsAnalysis of a real data set shows that after Bonferroni correction, the control-only ANOVA detects three differentially expressed genes, whereas the conventional ANOVA can detect only one.ConclusionsThe control-only ANOVA is recommended for use when the diseases under study are heterogeneous.
