Determining ancestry proportions in complex admixture scenarios in South Africa using a novel proxy ancestry selection method

Chimusa, Emile R; Daya, Michelle; Möller, Marlo; Ramesar, Raj; Henn, Brenna M; van Helden, Paul D; Mulder, Nicola J; Hoal, Eileen G

Determining ancestry proportions in complex admixture scenarios in South Africa using a novel proxy ancestry selection method

Journal Article

2013

Journal Title

PLoS One

Link to Journal

http://journals.plos.org/plosone

Publisher

Public Library of Science

Publisher

University of Cape Town

Department

Institute of Infectious Disease and Molecular Medicine

Faculty

Faculty of Health Sciences

License

http://creativecommons.org/licenses/by/4.0

Abstract

Admixed populations can make an important contribution to the discovery of disease susceptibility genes if the parental populations exhibit substantial variation in susceptibility. Admixture mapping has been used successfully, but is not designed to cope with populations that have more than two or three ancestral populations. The inference of admixture proportions and local ancestry and the imputation of missing genotypes in admixed populations are crucial in both understanding variation in disease and identifying novel disease loci. These inferences make use of reference populations, and accuracy depends on the choice of ancestral populations. Using an insufficient or inaccurate ancestral panel can result in erroneously inferred ancestry and affect the detection power of GWAS and meta-analysis when using imputation. Current algorithms are inadequate for multi-way admixed populations. To address these challenges we developed PROXYANC, an approach to select the best proxy ancestral populations. From the simulation of a multi-way admixed population we demonstrate the capability and accuracy of PROXYANC and illustrate the importance of the choice of ancestry in both estimating admixture proportions and imputing missing genotypes.