To address the over-estimation and inaccurate CIs, several methods have been proposed [Garner, 2007; Sun and Bull, 2005; Zollner and Pritchard, 2007; Yu et al., 2007; Zhong and Prentice, 2008]. We recently developed methods to correct the winner's curse and adjust CIs for ORs from GWAS, where SNPs are selected based on extreme P-values, either by a pre-specified threshold or rank-based selection [Zhong and Prentice, 2008]. The correction procedures only use the reported OR estimates and CIs, and do not require the raw individual-level genotype data, and hence can be conveniently applied to published findings from GWAS that have clearly specified selection criteria. In this paper, we applied conditional maximum likelihood estimation and the quantile based CI procedures [Zhong and Prentice, 2008] to estimate bias-corrected ORs and selection-adjusted CIs from several published GWAS on complex human diseases. These studies include GWAS on breast cancer [Easton et al., 2007; Hunter et al., 2007], lung cancer [Amos et al., 2008], prostate cancer [Eeles et al., 2008], colorectal cancer [COGENT Study, 2008], type I diabetes [The WTCCC, 2007] and type II diabetes [Zeggini
