TURF

TURF (Tissue-specific Unified Regulatory Features) prioritizes regulatory non-coding genetic variants and predicts organism-wide and tissue/organ-specific regulatory impact by integrating RegulomeDB-derived features with evidence from over three thousand ENCODE functional genomics datasets.

Key Features:

• RegulomeDB integration: Built upon the RegulomeDB framework to derive regulatory annotations and features.
• Dual-level scoring: Produces organism-wide and tissue/organ-specific prediction scores for non-coding variants.
• ENCODE evidence integration: Leverages evidence from more than three thousand ENCODE functional genomics datasets to inform predictions.
• MPRA validation: Analyzes validated variants from massively parallel reporter assay (MPRA) experiments to validate predictive performance.
• Variant prioritization: Prioritizes regulatory variants within candidate lists from association studies with tissue-specific resolution.
• GWAS trait enrichment: Enriches identification of regulatory variants associated with genome-wide association study (GWAS) traits in trait-relevant organs.

Scientific Applications:

• Tissue-specific variant discovery: Identify tissue-specific regulatory variants among candidate variants from association studies.
• Functional interpretation of non-coding variation: Assess the potential regulatory impact of non-coding genetic variants across biological contexts.
• GWAS follow-up: Prioritize regulatory variants linked to GWAS traits in trait-relevant organs to inform downstream experimental studies.

Methodology:

Integrates RegulomeDB-derived features with evidence from over three thousand ENCODE functional genomics datasets and analyzes validated variants from massively parallel reporter assay (MPRA) experiments.