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Explore advanced statistical methodologies in gene-environment interaction (GxE) meta-analysis specifically applied to coronary artery disease research through this 29-minute conference talk from the Computational Genomics Summer Institute. Discover cutting-edge approaches to analyzing complex genetic and environmental interactions using large-scale biobank data from UK Biobank and All of Us research programs. Learn about the statistical challenges and innovative solutions in conducting meta-analyses that combine genetic variants with environmental factors to better understand coronary artery disease susceptibility. Examine real-world applications of these methodologies through case studies and research findings that demonstrate how GxE interactions can provide deeper insights into cardiovascular disease mechanisms. Gain understanding of the computational and statistical frameworks necessary for handling massive genomic datasets while accounting for population diversity and environmental heterogeneity in coronary artery disease research.
