GEM

GEM performs large-scale gene–environment interaction (GEI) analysis to identify genetic variants that modify environmental effects and to test joint genetic main and interaction effects in studies of complex traits.

Key Features:

• Scalability: Handles datasets with millions of samples, with performance validated by rigorous simulations.
• Flexibility in GEI analysis: Supports multiple gene–environment interaction terms and allows adjustment for covariates related to those interactions.
• Robust inference and multi-threading: Implements robust inference methods and multi-threading to reduce computation time while maintaining result accuracy.
• Comprehensive testing: Performs GEI tests and joint tests of genetic main effects alongside interaction effects for continuous and binary phenotypes.

Scientific Applications:

• Genetic architecture of complex traits: Identifies genetic variants that modify environmental effects to elucidate gene–environment contributions to disease risk and phenotypic variation.
• Gene–sex interaction analysis (waist–hip ratio): Applied to 352,768 unrelated individuals from the UK Biobank, using joint testing to identify 24 novel loci not reported in combined or sex-specific analyses.

Methodology:

Uses advanced statistical methods tailored for GEI studies, including adjustment for covariates, robust inference, multi-threading, and tests of genetic main and interaction effects, with optimization for large datasets and validation via simulations.