We note that STRUCTURE is a complex program and has numerous options that add power and flexibility, many of which we cannot match with a PCA approach. Perhaps the central goal of STRUCTURE is to classify individuals into discrete populations, but this is not an object of our method. We think that in the future both cluster-based methods such as STRUCTURE and our PCA methods will have a role in discovering population structure on genetic data, so that, for example, our PCA methods offer a good default for the number of clusters to use in STRUCTURE. In complex situations, such as uncovering structure in populations where all individuals are equal mixtures of ancestral populations, it may remain necessary to use statistical software that explicitly models admixture LD, such as [10–13], which allow estimation of local ancestry at arbitrary points of the genome.
