GWAS4D

GWAS4D prioritizes context-specific regulatory variants by evaluating GWAS signals using integrated functional genomics, epigenomics, transcriptional regulator motifs, and uniformly processed Hi-C chromatin interactions.

Key Features:

• Regulatory Variant Prioritization: Implements a novel algorithm to prioritize regulatory variants among GWAS loci with emphasis on non-coding regions.
• Functional Genomics and Epigenomics Integration: Leverages extensive functional genomics and epigenomics datasets to inform variant prioritization.
• Tissue/Cell Type-Specific Epigenomes: Incorporates data from 127 tissue and cell type-specific epigenomes for context-specific predictions.
• Transcriptional Regulator Motifs Integration: Integrates motifs of 1480 transcriptional regulators compiled from 13 public resources.
• Hi-C Data Processing: Uniformly processes Hi-C data to generate significant chromatin interactions at 5 kb resolution across 60 tissues or cell types.
• Non-Coding Variant Functional Annotations: Provides comprehensive functional annotations for non-coding variants to support interpretation of regulatory impact.

Scientific Applications:

• Pathogenic Mechanism Elucidation: Elucidating pathogenic mechanisms of complex diseases by identifying causal regulatory variants in relevant tissues or cell types.
• Causal Regulatory Variant Identification: Prioritizing candidate causal regulatory variants among GWAS-identified susceptibility loci.
• Fine-Mapping of GWAS Loci: Fine-mapping GWAS loci by integrating variant prioritization, epigenomes, transcriptional regulator motifs, and chromatin interactions.
• Precision Medicine Research: Supporting precision-medicine studies through context-specific identification of regulatory variants that influence disease susceptibility.

Methodology:

Implements a novel variant prioritization algorithm; integrates functional genomics and epigenomics datasets including 127 tissue/cell-type epigenomes; incorporates motifs of 1480 transcriptional regulators from 13 public resources; uniformly processes Hi-C data to call significant chromatin interactions at 5 kb across 60 tissues or cell types; and provides comprehensive non-coding variant annotations.