Promises and limitations of local ancestry inference in imputed ancient genomes

Abstract

Recent advances in genome imputation have enabled the application of state-of-the-art statistical methods—originally developed for present-day genomes—to ancient genomes. One class of such methods, known as local ancestry inference (LAI), can model an individual's genome as a mosaic of tracts assigned to different putative ancestral sources, revealing patterns of genetic ancestry across the genome. However, most LAI methods have been designed to study recent admixture events in human history, and they generally assume large panels of present-day genomes. Despite the recent availability of high-quality imputed ancient genomes, it remains unknown to what degree LAI inference is reliable for such datasets. Ancient DNA is often characterized by heterogeneous geographic and temporal sampling, varying degrees of divergence between ancient source proxies and admixing populations, and complex demographic histories. Here, we performed an extensive set of population genetic simulations to evaluate the accuracy of four popular LAI methods—RFMix, FLARE, MOSAIC and simpLAI—under different demographic scenarios, various temporal sampling schemes, sample sizes, and admixture dates. We quantify the accuracy of these methods as a function of different parameters in practically relevant scenarios, and provide general guidelines for future studies utilizing LAI in ancient DNA research.