Demonstrates quantile regression's effectiveness in correcting population stratification in height studies, suggesting improved analysis in genetic research.
Subtle population structure remains a significant concern in genome-wide association studies. Using human height as an example, we show how quantile regression, a natural extension of linear regression, can better correct for subtle population structure due to its inherent ability to adjust for quantile-specific effects of covariates such as principal components. We utilize data from the UK Biobank and the SardiNIA/ProgeNIA project for demonstration.
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Wang et al. (2025) studied this question.
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