Estimation of non-additive genetic variance in human complex traits from a large sample of unrelated individuals.

ABSTRACT: Non-additive genetic variance for complex traits is traditionally estimated from data on relatives. It is notoriously difficult to estimate without bias in non-laboratory species, including humans, because of possible confounding with environmental covariance among relatives. In principle, non-additive variance attributable to common DNA variants can be estimated from a random sample of unrelated individuals with genome-wide SNP data. Here, we jointly estimate the proportion of variance explained by additive (h_SNP²), dominance (δ_SNP²) and additive-by-additive (η_SNP²) genetic variance in a single analysis model. We first show by simulations that our model leads to unbiased estimates and provide a new theory to predict standar

SUBMITTER: Hivert V 

PROVIDER: S-EPMC8205999 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature