pgainsim

pgainsim evaluates modes of inheritance (additive, recessive, and dominant) for quantitative trait loci in genome-wide association studies (GWAS) by simulating study-specific p-gain values to derive empirical quantiles and critical values.

Key Features:

• Model comparison: Compares additive, recessive, and dominant genetic models for quantitative trait loci in GWAS.
• Simulation of p-gain values: Simulates study-specific p-gain values to reflect study parameters.
• Empirical quantile computation: Computes quantiles from the empirical density distribution of simulated p-gain values.
• Critical value determination: Derives critical values by exporting or interpolating empirical quantiles.
• Customizable study parameters: Allows simulations parameterized by minor allele frequencies and study sizes.
• Interpolation for multiple testing: Uses interpolation to determine critical values with a moderate number of random draws in extensive multiple-testing scenarios.
• R-package implementation: Implemented as an R package for integration into R-based analysis workflows.

Scientific Applications:

• Mode of inheritance inference: Identifies the most informative genetic model for a locus to improve GWAS association interpretation.
• Downstream and clinical interpretation: Provides study-specific critical values to inform downstream analyses and clinical interpretation of GWAS findings.

Methodology:

Simulate study-specific p-gain values, compute quantiles from their empirical density distribution, and export or interpolate those quantiles to derive critical values for comparing additive, recessive, and dominant models.