COLOCdb

COLOCdb integrates over 3,000 genome-wide association study (GWAS) summary statistics and data from 13 distinct types of expression quantitative trait loci (xQTL) to enable pair-wise colocalization analyses that identify shared genetic variants linking complex traits and molecular phenotypes.

Key Features:

• Integration of Extensive Datasets: Consolidates over 3,000 GWAS summary statistics alongside data from 13 distinct types of expression quantitative trait loci (xQTL) for cross-layer genomic analysis.
• Colocalization Modes: Performs pair-wise GWAS-xQTL, GWAS-GWAS, and xQTL-xQTL colocalization analyses to detect shared genetic signals.
• Analytical Components: Implements GWAS-xQTL, GWAS-GWAS, and xQTL-xQTL components to map pleiotropic effects across datasets.
• Shared Variant Identification: Expands the set of shared genetic variants with pleiotropic effects to provide a detailed map of potential biological interactions.

Scientific Applications:

• Variant Prioritization: Identifies shared genetic variants that contribute to multiple traits or diseases.
• Mechanistic Inference: Facilitates exploration of molecular pathways through which genetic variants exert effects by linking GWAS loci to xQTLs.
• Hypothesis Generation: Supports generation of hypotheses for experimental validation of genetic mechanisms underlying complex traits.

Methodology:

Performs pair-wise colocalization analyses across GWAS and xQTL datasets using sophisticated algorithms to identify shared genetic variants (GWAS-xQTL, GWAS-GWAS, xQTL-xQTL).