MAGMA is a novel tool for gene and gene-set analysis in genome-wide association studies (GWAS). It addresses several issues common to existing methods, such as the impact of linkage disequilibrium (LD) and the computational burden of permutation-based analyses. MAGMA uses a multiple regression model for gene analysis, which better incorporates LD and multi-marker effects, and a separate layer for gene-set analysis, allowing for flexibility in handling continuous gene properties and multiple gene sets. Simulations and an analysis of Crohn's Disease data demonstrate that MAGMA has significantly higher statistical power compared to other tools while maintaining correct type 1 error rates. Additionally, MAGMA is significantly faster, making it a valuable tool for large-scale GWAS data analysis.MAGMA is a novel tool for gene and gene-set analysis in genome-wide association studies (GWAS). It addresses several issues common to existing methods, such as the impact of linkage disequilibrium (LD) and the computational burden of permutation-based analyses. MAGMA uses a multiple regression model for gene analysis, which better incorporates LD and multi-marker effects, and a separate layer for gene-set analysis, allowing for flexibility in handling continuous gene properties and multiple gene sets. Simulations and an analysis of Crohn's Disease data demonstrate that MAGMA has significantly higher statistical power compared to other tools while maintaining correct type 1 error rates. Additionally, MAGMA is significantly faster, making it a valuable tool for large-scale GWAS data analysis.