mvBIMBAM

mvBIMBAM performs multivariate Bayesian genetic association analysis to evaluate associations between genotypes and multiple related phenotypes simultaneously.

Key Features:

• Multivariate Analysis: Assesses associations between multiple outcome variables and a single explanatory variable such as genotype at a specific genetic variant.
• Bayesian Framework: Uses Bayesian model comparison and model averaging for multivariate regression models, providing a unified framework that encompasses univariate and multivariate tests.
• Association Testing and Explanation: Integrates testing for association with identification of which outcome variables are associated with genotype rather than relying solely on univariate follow-up tests.
• Computational Efficiency: Is computationally feasible for genome-wide studies involving modest numbers of phenotypes (e.g., 5–10) and can be applied to summary-level data without raw genotype and phenotype datasets.

Scientific Applications:

• Genetic Association Studies: Evaluates associations where the explanatory variable is a genetic variant across multiple phenotypes, suitable for studies of complex traits.
• Genome-wide association of blood lipid traits: Has been applied to GWAS of blood lipid traits to identify genetic associations that were not detected by univariate analyses.

Methodology:

Bayesian model comparison and model averaging applied to multivariate regression models; supports analysis of summary-level data and raw genotype/phenotype data; evaluates associations between multiple outcomes and a single explanatory variable and is computationally feasible for genome-wide scans with ~5–10 phenotypes.