Our methods are conceptually simple, and provide great power, especially on large datasets. We believe they will prove useful both in medical genetics, where population structure may cause spurious disease associations [1,40–43]; and in population genetics, where our statistical methods provide a strong indication of how many axes of variation are meaningful. A parallel paper [14] explores applications to medical genetics.
