Putting RFMix and ADMIXTURE to the test in a complex admixed population

Caitlin Uren,Marlo Möller,Eileen G Hoal

doi:10.1186/s12863-020-00845-3

Caitlin Uren, Marlo Möller + Show 1 more

Open Access

https://doi.org/10.1186/s12863-020-00845-3

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Abstract

BackgroundGlobal and local ancestry inference in admixed human populations can be performed using computational tools implementing distinct algorithms. The development and resulting accuracy of these tools has been tested largely on populations with relatively straightforward admixture histories but little is known about how well they perform in more complex admixture scenarios.ResultsUsing simulations, we show that RFMix outperforms ADMIXTURE in determining global ancestry proportions even in a complex 5-way admixed population, in addition to assigning local ancestry with an accuracy of 89%. The ability of RFMix to determine global and local ancestry to a high degree of accuracy, particularly in admixed populations provides the opportunity for more accurate association analyses.ConclusionThis study highlights the utility of the extension of computational tools to become more compatible to genetically structured populations, as well as the need to expand the sampling of diverse world-wide populations. This is particularly noteworthy as modern-day societies are becoming increasingly genetically complex and some genetic tools and commonly used ancestral populations are less appropriate. Based on these caveats and the results presented here, we suggest that RFMix be used for both global and local ancestry estimation in world-wide complex admixture scenarios particularly when including these estimates in association studies.

Highlights

Global and local ancestry inference in admixed human populations can be performed using computational tools implementing distinct algorithms
The aim of this study was to determine the accuracy of global and local ancestry inference (GAI and Local ancestry inference (LAI) respectively) in one of the most complex populations world-wide- putting it to the ultimate test
In conclusion, the findings presented here is the first of its kind to detail the accuracy of LAI and Global ancestry inference (GAI) in one of the most complex populations worldwide

Summary

Introduction

Global and local ancestry inference in admixed human populations can be performed using computational tools implementing distinct algorithms. The exchange of genetic material between distinct populations, is a hallmark of modern society - it can occur between closely or distantly related populations [1] This exchange of genetic material leads to population structure; the pattern, timing and extent has been investigated in detail in a number of populations [1,2,3]. Such studies on southern African populations are noteworthy as this area is postulated to be the geographical origin of modern humans [4].

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