Continuous ancestry profiles from genomes and genealogies

Using a single population label to represent an individual's ancestry may offer convenience, but ancestry is multidimensional, continuous, and reflects contributions from multiple ancestral sources. Here, we demonstrate empirically that ancestry profiles outperform categorical ancestry labels in capturing this complexity. Relatedness among 28,332 genotyped individuals was measured using haplotype painting and ordination and was regressed on regional ancestry proportions from the deep genealogies available for one-third of the cohort. When tested on participants in a validation set, predicted profiles placed 78% of documented ancestry in the correct region, against 48% for the training set average. Giving each participant a single regional label placed only 32% of their documented ancestry correctly, and a perfect classifier naming each person's largest documented region would reach only 38%, because most individuals carry ancestry from several regions. Thus, the continuous profile captures substantially more ancestry than any classification, providing support for representing ancestry as a continuum rather than a label.