The prevailing paradigm in recent years has been to use Genomic Control to measure the extent of inflation due to population stratification or other confounders, and to correct for stratification (if necessary) using methods that infer genetic ancestry, such as Structured Association or Principal Components Analysis. A limitation of this strategy is that it fails to account for other types of sample structure, such as family structure or cryptic relatedness5–6. Modeling family structure is a necessity in studies with family-based sample ascertainment, and there is increasing evidence that cryptic relatedness may occur in a wide range of data sets (see below). Family-Based Association Tests offer one potential solution for dealing with family structure. More recently, approaches using Mixed Models that incorporate the full covariance structure across individuals have been proposed.
