MendelVar

MendelVar integrates molecular evidence and Mendelian disease knowledge to prioritize candidate genes at Genome-Wide Association Study (GWAS) loci.

Key Features:

• Integrated database: Comprehensive integrated database of gene–Mendelian disease associations and variant information.
• Genomic interval querying: Queries pre-defined or linkage disequilibrium (LD)-determined genomic intervals.
• Overlap identification: Identifies overlaps between queried genomic intervals and genes linked to Mendelian diseases.
• ClinVar integration: Leverages ClinVar records of rare pathogenic mutations and gene–disease annotations.
• Enrichment analysis: Performs enrichment analysis using ontologies including the Human Phenotype Ontology and Disease Ontology.
• Ontology and pathway overlap: Assesses overlaps with ontology terms and pathways associated with identified Mendelian genes.
• Drug-target implication: Highlights Mendelian-linked genes as potential therapeutic targets to support drug discovery.
• GWAS case studies: Applied to GWAS summary statistics including male-pattern baldness, intelligence, and atopic dermatitis for candidate gene prioritization.

Scientific Applications:

• GWAS gene prioritization: Prioritizes candidate genes at GWAS loci by integrating Mendelian disease evidence.
• Phenotype and disease enrichment: Identifies enriched phenotype and disease terms via Human Phenotype Ontology and Disease Ontology.
• Variant annotation: Annotates overlaps between GWAS intervals and rare pathogenic variants documented in ClinVar.
• Drug discovery support: Informs target selection by highlighting genes with Mendelian disease associations.
• Reanalysis of GWAS summary statistics: Enables reanalysis of GWAS summary statistics for trait-specific case studies such as male-pattern baldness, intelligence, and atopic dermatitis.

Methodology:

Queries pre-defined or LD-determined genomic intervals against an integrated database to identify overlaps with genes linked to Mendelian diseases and ClinVar pathogenic variants, followed by enrichment analysis using ontologies including the Human Phenotype Ontology and Disease Ontology.