SNPs with effects on incidence but not on prognosis. To assess lower error rates, we estimated the family-wise type-1 error over the same SNPs, as the proportion of simulations in which at least one SNP had \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$P \, < \, 0.05$$\end{document}P<0.05 after Bonferroni adjustment for the number of such SNPs, that is \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$P \, < \, 10^{ - 5}$$\end{document}P<10-5. Finally, we identified the individual SNP with the highest type-1 error for the unadjusted estimator and compared it to the type-1 error of our adjusted estimator for the same SNP.
