Genetic association analysis using weighted false discovery rate approach on Genetic Analysis Workshop 18 data.

Area of Science:

• Genetics
• Statistical Genetics
• Cardiovascular Disease Research

Background:

• Genome-wide association studies (GWAS) test numerous genetic markers for disease associations.
• Controlling the false discovery rate (FDR) is crucial for accurate results in high-throughput genetic data analysis.
• Family-based association tests are valuable for quantitative traits.

Purpose of the Study:

• To apply a novel FDR control method with p-value weighting to family-based association tests.
• To detect significant single nucleotide polymorphisms (SNPs) associated with mean arterial pressure (MAP).
• To leverage Genetic Analysis Workshop 18 (GAW18) data for genetic discovery.

Main Methods:

• Utilized the FDR control method incorporating p-value weighting.
• Performed family-based association tests on quantitative traits.
• Analyzed genetic and phenotype data from chromosome 3 of GAW18.

Main Results:

• Identified one SNP within the CACNA2D3 gene showing a significant association with MAP.
• The p-value weighting method enhanced statistical power for detecting associations.
• Successfully applied the FDR control strategy to complex genetic data.

Conclusions:

• The p-value weighting approach is effective for FDR control in GWAS.
• A significant genetic marker (SNP in CACNA2D3) associated with MAP was discovered.
• This method offers improved statistical power by integrating relevant biological information.