Transformation of Summary Statistics from Linear Mixed Model Association on All-or-None Traits to Odds Ratio.

ABSTRACT: Genome-wide association studies (GWAS) have identified thousands of loci that are robustly associated with complex diseases. The use of linear mixed model (LMM) methodology for GWAS is becoming more prevalent due to its ability to control for population structure and cryptic relatedness and to increase power. The odds ratio (OR) is a common measure of the association of a disease with an exposure (e.g., a genetic variant) and is readably available from logistic regression. However, when the LMM is applied to all-or-none traits it provides estimates of genetic effects on the observed 0-1 scale, a different scale to that in logistic regression. This limits the comparability of results across studies, for example in a meta-analysis, and makes the interpretation of the magnitude of an e

SUBMITTER: Lloyd-Jones LR 

PROVIDER: S-EPMC5887138 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature