rqt

rqt performs gene-level association analysis and meta-analysis by aggregating single nucleotide polymorphism (SNP) data to identify genetic associations with complex diseases.

Key Features:

• Gene-Level Aggregation: Combines SNP-level signals into gene-level effect sizes and p-values to capture cumulative genetic effects.
• Meta-Analysis Across Datasets: Integrates gene-level results from multiple studies to increase statistical power and robustness.

Scientific Applications:

• Genetic Epidemiology of Complex Diseases: Identifies gene-level associations in multi-cohort studies, including analyses of Alzheimer’s disease datasets such as CHS, FHS, and LOADFS.

Methodology:

rqt applies statistical aggregation methods to compute gene-level effect sizes and p-values from SNP data and performs cross-study meta-analysis to detect significant gene–disease associations.