Next, we sought to examine characteristics of false-positive associations that could be used as predictors of the quality of association signal derived from imputated markers. An analysis of the characteristics of false-positive signals is of paramount importance to guide investigators in appropriately evaluating discovered signals based on imputed markers. Here, discovery entails results crossing a specific α threshold under a frequentist perspective rather than a Bayesian approach. We selected an α = 10-7 for illustrative purposes, an approximation that should work relatively well in typical studies conducted currently in Caucasian populations (CEU HapMap population, for example). Our empirical analysis demonstrated that the magnitude of the odds ratio of false-positive associations lies in the range of effects typically found in the GWA setting: median 1.26 (min = 1.20, max = 1.61); odds ratios were coined to be ≥1 for consistency. However, false-signals from imputed genotypes suggest more commonly protective effects (n = 47) rather than susceptibility effects (n = 26) for the minor allele variant.
