Estimating heritability explained by local ancestry and evaluating stratification bias in admixture mapping from summary statistics.

ABSTRACT: The heritability explained by local ancestry markers in an admixed population hγ2 provides crucial insight into the genetic architecture of a complex disease or trait. Estimation of hγ2 can be susceptible to biases due to population structure in ancestral populations. Here, we present a novel approach, Heritability estimation from Admixture Mapping Summary STAtistics (HAMSTA), which uses summary statistics from admixture mapping to infer heritability explained by local ancestry while adjusting for biases due to ancestral stratification. Through extensive simulations, we demonstrate that HAMSTA hγ2 estimates are approximately unbiased and are robust to ancestral stratification compared to existing approaches. In the presence of ancestral stratification, we show a HAMSTA-derived sampling sch

SUBMITTER: Chan TF 

PROVIDER: S-EPMC10153181 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature