PGMRA

PGMRA identifies genotype-phenotype relationships by integrating phenomics and SNP-set structures to address missing heritability in genome-wide association studies (GWAS).

Key Features:

• Missing heritability focus: Analyzes contributions of numerous loci with marginal effects to explain genetic variation not captured by single SNP associations in GWAS.
• Phenomics integration: Incorporates comprehensive sets of phenotype features (phenomics) into genotype-phenotype analysis.
• SNP-set detection: Detects SNP-set structures within existing GWAS data to reveal multi-locus architectures.
• Latent intermediate phenotypes: Identifies latent intermediate phenotypes that mediate genotype-phenotype relationships.
• Agnostic relationship discovery: Uncovers causally cohesive genotype-phenotype relationships without requiring prior knowledge of subject disease status.
• Post hoc risk-surface construction: Incorporates subject status after relation discovery to construct disease risk surfaces.
• Complementary analysis: Provides a framework that complements standard GWAS approaches for exploring complex interactions between genotypes and phenotypes.
• Interpretation and organization: Enables unbiased organization and interpretation of genotype-phenotype relationships informed by multi-locus and phenomic structure.

Scientific Applications:

• Missing heritability analysis: Quantifies genetic contributions beyond single nucleotide polymorphism (SNP) associations in GWAS.
• Intermediate phenotype discovery: Identifies latent phenotypes that link genotypes to complex traits.
• Disease risk mapping: Constructs risk surfaces by mapping genotype-phenotype relations to subject disease status.
• Exploration of complex interactions: Organizes and interprets multi-locus and phenomic interactions underlying complex traits.

Methodology:

Integrates phenomics into GWAS data, detects SNP-set structures to identify latent intermediate phenotypes, uncovers causally cohesive genotype-phenotype relationships without prior disease-status information, and incorporates subject status post hoc to construct risk surfaces.