Local ancestry deconvolution made simpler (?)

I’ve been waiting for a local ancestry deconvolution method to come out of Simon Myers’ group for a few years. Well, I think we’re there, Fine-scale Inference of Ancestry Segments without Prior Knowledge of Admixing Groups. Here’s the abstract:

We present an algorithm for inferring ancestry segments and characterizing admixture events, which involve an arbitrary number of genetically differentiated groups coming together. This allows inference of the demographic history of the species, properties of admixing groups, identification of signatures of natural selection, and may aid disease gene mapping. The algorithm employs nested hidden Markov models to obtain local ancestry estimation along the genome for each admixed individual. In a range of simulations, the accuracy of these estimates equals or exceeds leading existing methods that return local ancestry. Moreover, and unlike these approaches, we do not require any prior knowledge of the relationship between sub-groups of donor reference haplotypes and the unseen mixing ancestral populations. Instead, our approach infers these in terms of conditional “copying probabilities”. In application to the Human Genome Diversity Panel we corroborate many previously inferred admixture events (e.g. an ancient admixture event in the Kalash). We further identify novel events such as complex 4-way admixture in San-Khomani individuals, and show that Eastern European populations possess 1-5% ancestry from a group resembling modern-day central Asians. We also identify evidence of recent natural selection favouring sub-Saharan ancestry at the HLA region, across North African individuals. We make available an R and C ++ software library, which we term MOSAIC (which stands for MOSAIC Organises Segments of Ancestry In Chromosomes).

The truth is I’ve only done a quick skim of the preprint and not run the method myself to see how it works. But to be honest I can’t see where the part about Eastern Europeans is in the manuscript (I checked the supporting text)? That being said, if you run a PCA many Northern and most Eastern Europeans are clearly shifted toward East Asians compared to Southern Europeans. So I accept it.

In any case, always remember, all models are wrong. But some of them have insight.