How are genetic variants classified for clinical interpretation and what resources are used?

Clinical variant interpretation follows ACMG/AMP guidelines classifying variants into 5 categories: Pathogenic, Likely Pathogenic, Uncertain Significance (VUS), Likely Benign, Benign. Evidence types: 1) Population data - allele frequency in gnomAD; rare in controls supports pathogenicity. 2) Computational predictions - CADD, REVEL, SpliceAI for predicted impact; moderate evidence only. 3) Functional data - experimental assays, cell-based studies, animal models; strong evidence. 4) Segregation - co-segregation with disease in families. 5) De novo status - confirmed de novo variants in sporadic cases. Resources: ClinVar (aggregated interpretations), HGMD (mutation database), gnomAD (population frequencies), UniProt/InterPro (functional domains), PubMed (literature). Challenges: VUS resolution requires functional studies or additional cases; reinterpretation as knowledge grows; phenotype-genotype correlation; somatic vs germline distinction in cancer. Tools: Varsome, InterVar automate ACMG criteria.