RegScan

RegScan performs rapid genome-wide association analyses using linear regression to test associations between allele frequencies and continuous and combinatorial traits for scalable analysis of large GWAS and metabolomics datasets.

Key Features:

• Speed and Efficiency: Performs association analyses between allele frequencies and continuous traits up to ten to hundreds of times faster than leading fast methods.
• Combinatorial Trait Analysis: Generates and analyzes combinatorial traits, enabling analysis of complex trait combinations without requiring specification of each trait individually.
• Linear Regression Capabilities: Uses linear regression to estimate marker effects on continuous traits for association testing.
• Scalability and Flexibility: Handles any number of traits simultaneously to support large-scale GWAS and high-dimensional trait spaces.

Scientific Applications:

• Genome-wide association studies (GWAS): Enables GWAS involving large datasets by testing allele frequency associations with continuous traits.
• Metabolomics and high-dimensional trait analysis: Applied to metabolomics and other high-dimensional trait spaces to identify genetic associations underlying complex phenotypes.

Methodology:

Performs association testing between allele frequencies and continuous traits using linear regression models; the algorithm is optimized for speed and generates and analyzes combinatorial trait combinations.