In this paper, we applied bias-adjusted point estimates and confidence interval procedures [Zhong and Prentice, 2008] to published GWAS findings. It is widely recognized that estimates of the genetic effect based on high-dimensional association studies tend to be upwardly biased [Garner, 2007; Zollner and Pritchard, 2007; Yu et al., 2007]. However as demonstrated by several examples here and by extensive simulation studies [Zhong and Prentice, 2008], a simple bias reduction procedure, with careful selection of correction p-value cutoff, allows one to estimate bias-adjusted ORs that have fairly good consistency with the replication based OR estimates. More importantly, the selection adjusted CIs help quantify the uncertainty of the findings from the discovery stage, which provide insights as to whether the significant findings will replicate in independent cohorts. Therefore, this simple bias correction procedure evidently enables one to obtain more reliable OR estimates and CIs from the discovery stage of a GWAS, before embarking on expensive replication studies. When there is not a clearly pre-specified p-value selection threshold, the cutoff can be usefully approximated by the maximum p-value among all the selected
