Exomiser

Exomiser prioritizes genes and variants from next-generation sequencing (whole-exome or whole-genome) VCF files using Human Phenotype Ontology (HPO) phenotypes to identify candidate causative variants for Mendelian disease research and differential diagnostics.

Key Features:

• Input data: Accepts variant call format (VCF) files derived from whole-exome sequencing (WES) or whole-genome sequencing (WGS) data.
• Phenotype encoding: Uses the Human Phenotype Ontology (HPO) to encode patient phenotypes for phenotype-driven prioritization.
• Variant annotation and prioritization: Annotates, filters, and prioritizes variants based on defined computational criteria.
• Network-based analysis: Performs random-walk analysis within protein interaction networks to assess clinical relevance.
• Cross-species comparison: Incorporates cross-species phenotype comparisons to leverage model organism phenotype data.
• Frequency and pathogenicity filters: Applies filters evaluating variant frequency and predicted pathogenicity.
• Pedigree-aware filtering: Uses pedigree information for inheritance-aware filtering of variants.
• Performance: Reported typical resource usage is approximately 3 GB RAM with processing times of 15–90 seconds per VCF on a standard desktop.

Scientific Applications:

• Novel disease-gene discovery: Ranks candidate genes to support discovery of novel gene–disease associations in Mendelian disorders.
• Differential diagnostics of Mendelian diseases: Supports differential diagnosis by prioritizing variants consistent with clinical phenotypes and inheritance patterns.
• Variant interpretation in research and diagnostics: Facilitates identification of candidate causative variants for interpretation in research and clinical diagnostic contexts.
• Model organism phenotype integration: Enables interpretation of human phenotypes by integrating model organism phenotype data through cross-species comparisons.

Methodology:

Analyzes WES/WGS data from VCF files, encodes phenotypes using the Human Phenotype Ontology (HPO), annotates, filters, and prioritizes variants, applies variant frequency and predicted pathogenicity filters, uses pedigree information for inheritance-aware filtering, performs random-walk analysis on protein interaction networks, and incorporates cross-species phenotype comparisons.