CORE GREML for estimating covariance between random effects in linear mixed models for complex trait analyses - Xuan Zhou (Nature Portfolio, 2020)
Linear mixed models have bias due to the assumed independence between random effects. Here, the authors describe a genome-based restricted maximum likelihood, CORE GREML, which estimates covariance between random effects. Application to UK Biobank data highlights this as an important parameter for multi-omics analyses of phenotypic variance.