PolarMorphism

PolarMorphism identifies pleiotropic single nucleotide polymorphisms (SNPs) across multiple traits by transforming GWAS summary statistic effect sizes into polar coordinates to quantify overall effect (r) and sharedness (θ).

Key Features:

• Pleiotropic SNP detection: Identifies SNPs associated with multiple traits using GWAS summary statistics.
• Input data: Operates on genome-wide association study (GWAS) summary statistics.
• Coordinate transformation: Represents trait-specific SNP effect sizes as Cartesian coordinates and transforms them to polar coordinates.
• Polar parameters (r and θ): Uses r to represent overall effect size across traits and θ to indicate the degree of SNP sharedness among traits.
• P-value calculation: Computes a P-value for each SNP to assess significance of shared effects.
• Multi-trait analysis: Applicable to more than two traits or entire trait domains for simultaneous analysis.
• Pleiotropy network construction: Enables construction of networks that illustrate how traits share SNPs using publicly available GWAS summary statistics.
• Pathway analysis compatibility: Supports downstream pathway analysis of pleiotropic SNPs to evaluate biological relevance.
• Comparative performance: Offers reported efficiency and statistical power advantages relative to previously published methods.
• Biological relevance vs pairwise analyses: Yields more biologically relevant discoveries when analyzing multiple traits simultaneously compared to pairwise or genetic-correlation-only approaches.

Scientific Applications:

• Pleiotropy discovery: Detection of SNPs that influence multiple traits to study shared genetic architecture.
• Pleiotropy network analysis: Construction of networks showing SNP sharing between traits to explore trait interrelationships.
• Cross-trait genetic relationship exploration: Quantification of shared effects to investigate relationships among complex traits and trait domains.
• Pathway-level interpretation: Enabling pathway analysis of pleiotropic SNPs to infer underlying biological processes.

Methodology:

PolarMorphism transforms trait-specific SNP effect sizes from Cartesian to polar coordinates (r and θ) using GWAS summary statistics and computes a P-value per SNP to assess sharedness across more than two traits.