A unified linear mixed model for familial relatedness and population structure in genetic association studies. Genet Epidemiol 2021 Apr;45(3):305-315
Date
11/12/2020Pubmed ID
33175443DOI
10.1002/gepi.22371Scopus ID
2-s2.0-85096638635 (requires institutional sign-in at Scopus site) 1 CitationAbstract
Familial relatedness (FR) and population structure (PS) are two major sources for genetic correlation. In the human population, both FR and PS can further break down into additive and dominant components to account for potential additive and dominant genetic effects. In this study, besides the classical additive genomic relationship matrix, a dominant genomic relationship matrix is introduced. A link between the additive/dominant genomic relationship matrices and the coancestry (or kinship)/double coancestry coefficients is also established. In addition, a way to separate the FR and PS correlations based on the estimates of coancestry and double coancestry coefficients from the genomic relationship matrices is proposed. A unified linear mixed model is also developed, which can account for both the additive and dominance effects of FR and PS correlations as well as their possible random interactions. Finally, this unified linear mixed model is applied to analyze two study cohorts from UK Biobank.
Author List
DeVogel N, Auer PL, Manansala R, Rau A, Wang TAuthors
Paul L. Auer PhD Professor in the Institute for Health and Equity department at Medical College of WisconsinTao Wang PhD Associate Professor in the Institute for Health and Equity department at Medical College of Wisconsin
MESH terms used to index this publication - Major topics in bold
Genes, DominantGenetic Association Studies
Genome
Genomics
Humans
Models, Genetic
