ASGSCA

ASGSCA performs joint modeling and testing of associations between multiple genotypes and multiple correlated quantitative traits using Generalized Structured Component Analysis (GSCA) while integrating prior biological knowledge.

Key Features:

• Multi-Genotype and Multi-Trait Association: Performs joint analysis of numerous genetic variants across genes and correlated quantitative traits to improve detection power relative to univariate tests.
• Integration of Prior Biological Knowledge: Represents genes and clinical pathways as latent variables within models to incorporate prior biological knowledge into association analyses.
• Generalized Structured Component Analysis (GSCA): Implements GSCA, an extension of structural equation modeling (SEM), to model complex relationships between genetic variants in candidate genes and correlated traits.
• Single Association Test: Provides a single association test that evaluates multiple genetic variants within a gene against a set of correlated traits while accounting for data from other genes and traits.
• Simulation-Based Evaluation: Assesses performance of the association tests through simulation studies to evaluate robustness and reliability.

Scientific Applications:

• Genetic Association Studies: Models complex trait–genotype interactions to identify genetic variants associated with diseases or quantitative traits.
• Cardiovascular Research: Applied to investigate genetic associations with cardiovascular disease–related traits.
• Large-Scale Genomic Studies: Suited for studies that require joint analysis of multiple genetic factors and phenotypic outcomes.

Methodology:

Modeling is performed using GSCA within a structural equation modeling framework; association-test performance is evaluated via simulation studies; methods have been applied to real datasets including the Quebec Child and Adolescent Health and Social Survey (1999).