Detecting differentially expressed genes in heterogeneous diseases using control-only analysis of variance.
OBJECTIVE
Microarray 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.


METHODS
The 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.


RESULTS
Analysis 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.


CONCLUSIONS
The control-only ANOVA is recommended for use when the diseases under study are heterogeneous.
Research Center for Genes, Environment and Human Health, College of Public Health, National Taiwan University, Taiwan.
I-Shiang
IS
Tzeng
Wen-Chung
WC
Lee
D000704:Analysis of Variance; D003198:Computer Simulation; D020869:Gene Expression Profiling / Q000379:methods*; D018740:Genetic Heterogeneity; D005820:Genetic Testing / Q000379:methods*; D006801:Humans; D008957:Models, Genetic; D015233:Models, Statistical; D009010:Monte Carlo Method