On the sample size requirement in genetic association tests when the proportion of false positives is controlled.
With respect to the multiple-tests problem, recently an increasing amount of attention has been paid to control the false discovery rate (FDR), the positive false discovery rate (pFDR), and the proportion of false positives (PFP). The new approaches are generally believed to be more powerful than the classical Bonferroni one. This article focuses on the PFP approach. It demonstrates via examples in genetic association studies that the Bonferroni procedure can be more powerful than the PFP-control one and also shows the intrinsic connection between controlling the PFP and controlling the overall type I error rate. Since controlling the PFP does not necessarily lead to a desired power level, this article addresses the design issue and recommends the sample sizes that can attain the desired power levels when the PFP is controlled. The results in this article also provide rough guidance for the sample sizes to achieve the desired power levels when the FDR and especially the pFDR are controlled.
Zou
Guohua
G
Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100080, People's Republic of China. zuo@msu.edu
Zuo
Yijun
Y
D000465:Algorithms; D002874:Chromosome Mapping; D005189:False Positive Reactions; D008040:Genetic Linkage; D006801:Humans; D008957:Models, Genetic; D040641:Quantitative Trait Loci; D018401:Sample Size