Skip to content

Genome-based Restricted Maximum Likelihood (GREML)

Definition
AI-generated

GREML estimates variance components from genome-wide genotype similarity by fitting a random-effects model with restricted maximum likelihood.

Topics
Post-GWAS
Related
Genome-wide Complex Trait Analysis (GCTA) Genetic Relationship Matrix (GRM) Heritability

Why it matters in GWAS

GREML is a standard way to estimate SNP heritability from individual-level data and to test how much variance is captured by measured variants. It complements summary-statistic methods such as LD score regression and is commonly run in GCTA.

Example usage

"GREML estimated liability-scale SNP heritability after adjusting for age, sex, and the top ancestry PCs."

Genome-wide Complex Trait Analysis (GCTA) Genetic Relationship Matrix (GRM) Heritability LD Score Regression Linear Mixed Model (LMM) Observed Scale SNP Heritability
Related-term network

Click any node to open that term page.

Node order. The current term is first. Next come every page linked from Related terms, in the same top-to-bottom order as that list. Then new terms appear in two-hop layers: for each of those direct neighbors (in that same order), their related terms are appended if not already listed. A third pass does the same for two-hop nodes. The walk stops when a fixed maximum number of nodes is reached.

References

  • Yang J, et al. (2011). GCTA: a tool for genome-wide complex trait analysis. Am J Hum Genet. https://doi.org/10.1016/j.ajhg.2010.11.011
  • Yang J, et al. (2017). Concepts, estimation and interpretation of SNP-based heritability. Nat Genet. https://doi.org/10.1038/ng.3941
  • GWASTutorial: GCTA-GREML.
← Graph Neural Network (GNN) Genotype-Tissue Expression (GTEx) →

Last updated (UTC · Git history)