Filtering and Interpretation Algorithm based on VarClaM Conceptual Model

The accurate interpretation of genomic variants is crucial for hereditary cancer diagnostics and management. We present a standardized variant interpretation algorithm based on the American College of Medical Genetics and Genomics-Association for Molecular Pathology (ACMG-AMP) guidelines s. This algorithm incorporates structured filtering criteria for identifying relevant variants and comprehensive interpretation metrics that leverage multiple data sources, including population databases, computational predictions, and clinical evidence. The framework employs three primary filtering tiers that evaluate structural variants, pathogenicity interpretations from established databases, rare null variants. The interpretation system utilizes a quantitative scoring approach with 22 distinct criteria, each weighted according to strength of evidence, resulting in a refined nine-tier interpretation system ranging from benign to pathogenic. This workflow has been validated through expert review and successfully tested on more than 30 clinical cases.