Skip to main content

Table 1 Controlling for confounding due to admixture in association testing

From: Mapping of disease-associated variants in admixed populations

Generative modela

Regression modeld

βgenotypeb

βlocal ancestryc

Genotype

Genotype and global ancestry

Genotype stratified by local ancestry

0

0

0.048

0.044

0.053

0

1

0.570

0.538

0.052

1

0

0.892

0.892

0.893

1

1

0.599

0.626

0.899

  1. The first two rows demonstrate inflation of the false-positive error rate resulting from confounding due to admixture. The second two rows demonstrate the loss of power resulting from confounding due to admixture. In both cases, confounding is controlled by local ancestry but not by global ancestry. aTwo isolated parental populations were generated with FST = 0.115 (FST is the ratio of the observed variance in allele frequencies among populations to the variance expected if the populations were randomly mating), mimicking the amount of population differentiation between the African and European ancestors of African Americans. A sample of admixed individuals was generated with 80% of the genome inherited from the first parental population, mimicking the amount of African ancestry in African Americans. A dataset consisted of 1,000 unrelated individuals and 1,000 unlinked markers. The generative model for the phenotype was a linear model with the listed fixed effects for the queried marker, no effects for all other markers, and noise equal to a random deviate from the standard normal distribution. bFor each marker and individual, the genotype was coded as 0, 1, or 2 copies of the derived allele. cFor each marker and individual, local ancestry was coded as 0, 1, or 2 copies inherited from the first parental population. dThe rejection rates (false-positive error rates if βgenotype = 0, or power if βgenotype = 1) for testing genotype association at one marker are shown. The significance level was 0.05.