PheGWAS

PheGWAS visualizes phenome-wide pleiotropy by integrating GWAS and PheWAS summary statistics into a 3D landscape to reveal relationships between genetic variants and multiple phenotypes.

Key Features:

• 3D landscape visualization: Generates 3D landscapes that combine Manhattan plots from GWAS with PheWAS data to represent associations across phenotypes.
• Sectional views: Plots sectional views of sub-surface GWAS significance strata at user-defined levels to explore subtle pleiotropic effects.
• Chromosomal sectioning: Confines analyses to a single chromosomal section to reduce complexity in interpretation.
• Genomic and phenomic coordinates: Displays detailed genomic and phenomic coordinates for associated signals.
• Locus identification in GLGC data: Demonstrated on Global Lipids Genetics Consortium summary statistics, highlighting 88 loci for single traits and 69 loci for multiple traits.
• Genetic correlation and causality insight: Identifies independent signals and provides insight into local genetic correlations (verified using HESS) and regions sharing causal variants (verified using colocalization tests).
• Gene and SNP reporting: Facilitates identification of genes and single nucleotide polymorphisms reported in GWAS consortia.

Scientific Applications:

• Pleiotropy mapping: Map pleiotropic relationships between genetic variants and multiple phenotypes across the phenome.
• Locus discovery and prioritization: Identify and prioritize genetic loci associated with single and multiple traits, as demonstrated for lipid traits.
• Local genetic correlation analysis: Investigate local genetic correlations using HESS to assess shared genetic architecture.
• Colocalization assessment: Test for colocalization to evaluate regions that may share causal variants across phenotypes.
• Interpretation of genetic architecture: Aid interpretation of the genetic architecture underlying complex traits and implicated biological pathways.

Methodology:

Integrates GWAS and PheWAS summary statistics into a 3D landscape combining Manhattan plots with PheWAS data; supports sectional plotting of GWAS significance strata for single chromosomal sections; identifies genes and SNPs reported in GWAS consortia; assesses local genetic correlation using HESS and evaluates colocalization using colocalization tests, demonstrated on Global Lipids Genetics Consortium summary data.