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

Uren, Caitlin ; Hoal, Eileen G. ; Moller, Marlo (2020)

CITATION: Uren, C., Hoal, E. G. & Moller, M. 2020. Putting RFMix and ADMIXTURE to the test in a complex admixed population. BMC Genetics, 21:40, doi:10.1186/s12863-020-00845-3.

The original publication is available at https://bmcinfectdis.biomedcentral.com

Publication of this article was funded by the Stellenbosch University Open Access Fund

Article

Background: Global 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. Results: Using 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. Conclusion: This 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 worldwide complex admixture scenarios particularly when including these estimates in association studies.

Please refer to this item in SUNScholar by using the following persistent URL: http://hdl.handle.net/10019.1/108616
This item appears in the following collections: