Most GWAS studies do not employ family-based data; thus, there are inherent challenges in estimating the power of the sample to detect particular effect sizes. However, the implementation of a correlation matrix subdivided by family clusters to control for relatedness among the families pares symptom count analysis to an association test similar to a case-control study, as do the generalized estimating equations (GEE) used to analyze alcohol dependence. Both methods provide similar power estimates based on simulation studies30,31. For this sample, we estimated power using Quanto32. These extended pedigrees have 70% power to detect an effect size of 1.1 for symptom count when the minor allele frequency is between 0.10 and 0.30.
