Ancestry Composition
We apply Ancestry Composition, a three-step pipeline that efficiently and accurately identifies the ancestral origin of chromosomal segments in admixed individuals, which is described in Durand et al.33 We apply the method to genotype data that have been phased via a reimplementation of Beagle.46 Ancestry Composition applies a string kernel support vector machines classifier to assign ancestry labels to short local phased genomic regions, which are processed via an autoregressive pair hidden Markov model to simultaneously correct phasing errors and produce reconciled local ancestry estimates and confidence scores based on the initial assignment. Lastly, these confidence estimates are recalibrated by isotonic regression models. This results in both precision and recall estimates that are greater than 0.90 across many populations, and on a continental level, have rates of 0.982–0.994 for precision and recall rates of 0.935–0.993, depending on populations (see Table 1 from Durand et al.33). We note that here, and throughout the manuscript, African ancestry corresponds to sub-Saharan African ancestry (including West African, East African, Central, and South African populations, but excluding North African populations from the reference set). For more details on our ancestry estimation method, see Durand et al.33