Chunk #91 — 7.0 Recommendations to Advance Endophenotype Genetics — 7.3 Adequate power to detect individual effects is crucial but almost never attained in existing endophenotype genetic association studies — 7.3.1. Power and sampling schemes in GWAS
be required for 80% power to detect a single genome-wide effect. Next, we estimated the sample size required if one were to maximize the variance of X (VX) or to reduce measurement error from 50% to 25%. We assume that the predictor X is a biallelic SNP, its variance is determined by the variance of the binomial distribution, or 2*MAF(1-MAF), which is maximized when MAF =.5. To reduce measurement error we simply assumed that the variance in the phenotype was produced in accord with classical test theory: var(P) = var(T) + var(E), where P is the phenotypic score, T is the true score, and E is the measurement error. We conservatively assumed that measurement error accounted for half the variance in the phenotype, and that one could then reduce measurement error by half. As Table 3 indicates, even under the most unrealistically optimistic of circumstances, when one assumes the effect is as large as the largest effect reported for the nicotine metabolite cotinine, error in measuring the phenotype is reduced by half, and MAF for the variant is maximized at 50%, 1,465 participants are still required to have 80% power to detect a single genome-wide effect. The worst-case scenario is
