GEWIST

GEWIST optimizes SNP prioritization to increase statistical power for detecting gene-environment interactions by applying variance prioritization (VP) and the Gene Environment Wide Interaction Search Threshold (GEWIST) algorithm.

Key Features:

• Variance Prioritization (VP): Identifies SNPs with significant heterogeneity in quantitative trait variance per genotype.
• SNP-specific P-value thresholds: Dynamically determines an optimal P-value threshold for each SNP rather than using a uniform threshold across all SNPs.
• GEWIST algorithm: Implements a fast Gene Environment Wide Interaction Search Threshold algorithm that efficiently computes optimal prioritization thresholds for large numbers of SNPs.
• Integration over interaction effect sizes: Integrates over possible interaction effect sizes to optimize SNP prioritization when the nature of interactions is unknown.
• Multiple testing mitigation: Addresses the multiple hypothesis problem and the conservativeness of Bonferroni correction to improve detection power.
• Scalability for genome-wide studies: Applies methods suitable for genome-wide scans involving vast numbers of SNPs.

Scientific Applications:

• Gene-environment interaction discovery: Improves detection of gene-environment interactions in quantitative trait analyses.
• Genome-wide interaction scans: Prioritizes SNPs in genome-wide searches to reduce multiple testing burden and enhance power.
• Genetic epidemiology: Supports genetic epidemiology studies seeking interaction effects between genetic variants and environmental factors.

Methodology:

Computational methods explicitly include variance prioritization (VP), per-SNP optimal P-value thresholding, the GEWIST algorithm for fast threshold computation, and integration over possible interaction effect sizes to address multiple hypothesis testing relative to Bonferroni correction.