VannoPortal

VannoPortal provides comprehensive, context-specific annotations of human genomic variants to support interpretation of variant function and disease and trait associations.

Key Features:

• Large-scale data integration: Integrates over 4TB of genomic and epigenomic profiles and widely-used annotation databases, compiling 40 genome-wide variant annotations and prediction scores including allele frequency, linkage disequilibrium, evolutionary signatures, disease/trait associations, tissue/cell type-specific epigenomes, base-wise functional predictions, allelic imbalance, and pathogenicity.
• Efficient data management: Employs a novel index system and parallel random-sweep searching algorithms to manage backend databases and enable rapid information extraction.
• Context-dependent annotation expansion: Incorporates large-scale epigenomic maps and regulatory profiles such as EpiMap across over 33 tissue and cell types to expand context-specific annotations.
• Genome-scale base-wise prediction scores: Compiles base-wise prediction scores to support classification of regulatory and pathogenic variants beyond protein-coding regions.

Scientific Applications:

• Molecular mechanism interpretation: Supports analysis of molecular mechanisms underlying genomic variants and their causal relationships with diseases or traits.
• Non-coding variant classification: Enables classification and prioritization of regulatory and pathogenic variants located outside protein-coding regions.
• Support for genetic research and clinical studies: Provides comprehensive annotations applicable to a range of genetic studies from basic research to clinical applications.

Methodology:

Integrates over 4TB of genomic and epigenomic profiles and widely-used annotation databases; systematically compiles 40 genome-wide variant annotations and prediction scores; incorporates large-scale epigenomic maps and regulatory profiles (e.g., EpiMap) across over 33 tissue/cell types; implements a novel index system and parallel random-sweep searching algorithms for backend data management and rapid retrieval; compiles genome-scale base-wise prediction scores.