Inference on the genetic basis of eye and skin color in an admixed population via Bayesian linear mixed models

L.R. Lloyd-Jones, M.R. Robinson, G. Moser, J. Zeng, S. Beleza, G.S. Barsh, H. Tang, P.M. Visscher, Genetics 206 (2017) 1113–1126.

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Journal Article | Published | English
Author
Lloyd-Jones, Luke R.; Robinson, Matthew RichardIST Austria ; Moser, Gerhard; Zeng, Jian; Beleza, Sandra; Barsh, Gregory S.; Tang, Hua; Visscher, Peter M.
Abstract
Genetic association studies in admixed populations are underrepresented in the genomics literature, with a key concern for researchers being the adequate control of spurious associations due to population structure. Linear mixed models (LMMs) are well suited for genome-wide association studies (GWAS) because they account for both population stratification and cryptic relatedness and achieve increased statistical power by jointly modeling all genotyped markers. Additionally, Bayesian LMMs allow for more flexible assumptions about the underlying distribution of genetic effects, and can concurrently estimate the proportion of phenotypic variance explained by genetic markers. Using three recently published Bayesian LMMs, Bayes R, BSLMM, and BOLT-LMM, we investigate an existing data set on eye (n = 625) and skin (n = 684) color from Cape Verde, an island nation off West Africa that is home to individuals with a broad range of phenotypic values for eye and skin color due to the mix of West African and European ancestry. We use simulations to demonstrate the utility of Bayesian LMMs for mapping loci and studying the genetic architecture of quantitative traits in admixed populations. The Bayesian LMMs provide evidence for two new pigmentation loci: one for eye color (AHRR) and one for skin color (DDB1).
Publishing Year
Date Published
2017-06-01
Journal Title
Genetics
Volume
206
Issue
2
Page
1113-1126
IST-REx-ID

Cite this

Lloyd-Jones LR, Robinson MR, Moser G, et al. Inference on the genetic basis of eye and skin color in an admixed population via Bayesian linear mixed models. Genetics. 2017;206(2):1113-1126. doi:10.1534/genetics.116.193383
Lloyd-Jones, L. R., Robinson, M. R., Moser, G., Zeng, J., Beleza, S., Barsh, G. S., … Visscher, P. M. (2017). Inference on the genetic basis of eye and skin color in an admixed population via Bayesian linear mixed models. Genetics, 206(2), 1113–1126. https://doi.org/10.1534/genetics.116.193383
Lloyd-Jones, Luke R., Matthew Richard Robinson, Gerhard Moser, Jian Zeng, Sandra Beleza, Gregory S. Barsh, Hua Tang, and Peter M. Visscher. “Inference on the Genetic Basis of Eye and Skin Color in an Admixed Population via Bayesian Linear Mixed Models.” Genetics 206, no. 2 (2017): 1113–26. https://doi.org/10.1534/genetics.116.193383.
L. R. Lloyd-Jones et al., “Inference on the genetic basis of eye and skin color in an admixed population via Bayesian linear mixed models,” Genetics, vol. 206, no. 2, pp. 1113–1126, 2017.
Lloyd-Jones LR, Robinson MR, Moser G, Zeng J, Beleza S, Barsh GS, Tang H, Visscher PM. 2017. Inference on the genetic basis of eye and skin color in an admixed population via Bayesian linear mixed models. Genetics. 206(2), 1113–1126.
Lloyd-Jones, Luke R., et al. “Inference on the Genetic Basis of Eye and Skin Color in an Admixed Population via Bayesian Linear Mixed Models.” Genetics, vol. 206, no. 2, Genetics Society of America, 2017, pp. 1113–26, doi:10.1534/genetics.116.193383.

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