vaRHC

vaRHC implements semi-automated classification of germline variants in hereditary cancer genes as an R package by applying ACMG/AMP and ClinGen gene-specific guidelines.

Key Features:

• Integration of Diverse Data Sources: Aggregates information from multiple databases to assemble comprehensive evidence for variant assessment.
• Evidence Assignment: Assigns or denies evidence codes according to updated criteria for genes including ATM, CDH1, CHEK2, MLH1, MSH2, MSH6, PMS2, PTEN, and TP53, while applying general ACMG/AMP criteria for other genes.
• Automated Classification: Performs automated variant classification using a Bayesian metastructure and incorporates CanVIG-UK recommendations.
• Output Flexibility: Exports results to .xlsx files.
• Validation and Performance: Validated on 659 classified variants with superior criteria assignment compared to Cancer SIGVAR.

Scientific Applications:

• Hereditary cancer variant classification: Streamlines and semi-automates germline variant classification workflows in hereditary cancer research.
• Clinical interpretation of NGS data: Supports interpretation of germline variants derived from next-generation sequencing in clinical settings by applying standardized and gene-specific criteria.
• Research and clinical evidence integration: Integrates multiple evidence types and gene-specific criteria to support researchers and clinicians in variant curation and assessment.

Methodology:

Collects diverse database information, assigns evidence according to ACMG/AMP and ClinGen gene-specific criteria for specified genes, and applies a Bayesian metastructure for automated classification while considering CanVIG-UK recommendations.