GeneYenta

GeneYenta matches phenotype-annotated exome sequencing (NGS) cases to identify candidate causal genetic variants and shared disrupted genes in rare genetic disorders.

Key Features:

• Phenotype annotation focus: Emphasizes structured phenotype annotation of cases derived from exome sequencing (NGS) while protecting highly confidential data.
• Ontology-based semantic matching algorithm: Implements an ontology-based semantic case matching algorithm to compute phenotype profile similarity.
• Attribute weighting: Uses attribute weighting to adjust the importance of phenotype features during semantic matching.
• Clinician-driven weights: Incorporates clinician-assigned weights to refine matching based on expert input.
• Identification of shared disrupted genes: Facilitates identification of common disrupted genes among matched unrelated individuals.
• Evaluation and comparison: Evaluated using a curated reference dataset and 19 clinician-entered cases with comparisons across four matching algorithms.

Scientific Applications:

• Variant prioritization: Identification and prioritization of candidate causal genetic variants from exome sequencing cases.
• Gene discovery and causality assessment: Establishing causality by finding common disrupted genes across unrelated phenotypically similar cases.
• Phenotype-driven aggregation: Aggregating phenotypically similar cases to support gene-disease association studies and interpretation of genetic findings.

Methodology:

Structured phenotype annotation; ontology-based semantic case matching with attribute weighting; incorporation of clinician-assigned weights; evaluation using a curated reference dataset and 19 clinician-entered cases comparing four matching algorithms.