If population stratification exists, it is important to distinguish between subpopulation differences that are due to very recent genetic drift, and those that arose from more ancient population divergence11. In the case of ancient population divergence, dividing association statistics by λGC will provide a sufficient correction for stratification. In the latter case, markers with unusual allele frequency differences that lie outside the expected distribution, which could be caused by natural selection, make stratification a much more severe problem, and dividing association statistics by λGC is likely to be inadequate. In the case of family structure or cryptic relatedness, dividing association statistics by λGC will generally produce the approximate null distribution, though a refinement to the method may be needed when there is uncertainty in the estimate of λGC 12. However, even if the appropriate null distribution is obtained, in general this approach will not maximize power to detect true associations. Other approaches to correcting for stratification, including approaches that also account for family structure and cryptic relatedness, are described below.
