Journal article

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

Valentin Hivert, Julia Sidorenko, Florian Rohart, Michael E Goddard, Jian Yang, Naomi R Wray, Loic Yengo, Peter M Visscher

AMERICAN JOURNAL OF HUMAN GENETICS | CELL PRESS | Published : 2021

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 (hSNP2), dominance (δSNP2) and additive-by-additive (ηSNP2) genetic variance in a single analysis model. We first show by simulations that our model leads to unbiased estimates and provi..

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University of Melbourne Researchers

Grants

Awarded by Australian National Health and Medical Research Council


Awarded by Australian Research Council


Funding Acknowledgements

We acknowledge funding from the Australian National Health and Medical Research Council (1113400, 1173790) and the Australian Research Council (FT180100186 and FL180100072). This research has been conducted using the UK Biobank Resource under Appli-cation Number 12505. We wish to acknowledge The University of Queensland's Research Computing Centre (RCC) for its support in this research. We also thank Allan McRae for technical support, Jian Zeng for fruitful discussions, and two anonymous reviewers for helpful comments.