CAFEH

CAFEH performs joint Bayesian fine-mapping and colocalization of genetic association data across multiple phenotypes to identify causal variants and assess tissue-specific effects while accounting for linkage disequilibrium and allelic heterogeneity.

Key Features:

• Joint fine-mapping and colocalization: Performs fine-mapping and colocalization simultaneously across numerous phenotypes to identify causal variants with greater precision.
• Scalability: Handles tens of phenotypes and thousands of genetic variants efficiently, with reported processing on the order of minutes.
• Tissue specificity analysis: Investigates tissue-specificity of genetic effects on gene expression that can be obscured by linkage disequilibrium in traditional meta-analytic approaches.
• Handling allelic heterogeneity: Models allelic heterogeneity to identify multiple causal variants and improve prioritization of target tissues for GWAS loci.

Scientific Applications:

• Understanding eQTLs: Elucidates the role of expression quantitative trait loci (eQTLs) across human tissues to connect genetic associations and disease mechanisms.
• Disease locus interpretation: Identifies genes with tissue-specific effects at complex trait loci to aid interpretation of disease-relevant targets.
• Prioritization of target tissues: Leverages allelic heterogeneity to improve prioritization of tissues for follow-up of GWAS loci.

Methodology:

CAFEH employs a Bayesian framework to integrate genetic association data across multiple phenotypes and explicitly models linkage disequilibrium and the presence of multiple causal variants (allelic heterogeneity) within and across tissues.