In addition to evaluating the loss of genetic signal, we recommend three checks to examine concordance in GWAS coefficients (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta$$\end{document}β), which should preferably be applied to near-independent SNPs (Step 3 explains a standard pruning procedure to find near-independence). If correlated SNPs are included, larger LD blocks will be given more weight. Depending on the power of the full-data GWAS, the checks could be applied only to genome-wide significant hits or could be expanded to a less stringent threshold (say, P < 1 × 10–5). The three checks are to (1) test for sign concordance, (2) inspect for outliers, and (3) run a regression of the down-sampled GWAS coefficients on their full-data counterparts (as absolute values).
