Documentation / Variant Analysis / ACMG/AMP Framework
ACMG variant classification framework and criteria
ACMG variant classification organizes evidence for a germline sequence variant into one of five classes: Pathogenic, Likely pathogenic, Uncertain significance, Likely benign, or Benign. Folklore proposes a class for supported nuclear variants by recording each eligible criterion, its direction, strength, source, and safeguards before applying published combining rules. A qualified professional reviews the result in the full clinical context.
For case-based VCF analysis, continue to the variant classification platform.
Review one public GRCh38 variant against Folklore's current evidence snapshot. Public search accepts a variant expression only. Do not enter patient or case information.
Search a public variantFive Classification Tiers
| Class | Meaning in the framework |
|---|---|
| Pathogenic | The evidence combination satisfies a published pathogenic rule. |
| Likely pathogenic | The evidence combination supports pathogenicity below the Pathogenic threshold. |
| Uncertain significance | The evidence is insufficient, conflicting, or does not satisfy a benign or pathogenic combining rule. |
| Likely benign | The evidence combination supports a benign interpretation below the Benign threshold. |
| Benign | The evidence combination satisfies a published benign rule, including an eligible stand-alone benign criterion. |
Evidence Model
ACMG/AMP criteria cover population, computational, functional, segregation, de novo, allelic, phenotype, and curated clinical evidence. Pathogenic criteria use the PVS, PS, PM, and PP families. Benign criteria use BA, BS, and BP. Strength-modified criteria retain their original code with an explicit strength suffix so the evidence trace remains reviewable.
| Direction | Strengths | Examples |
|---|---|---|
| Pathogenic | Very Strong, Strong, Moderate, Supporting | PVS1, PS1, PM2, PP3 |
| Benign | Stand-alone, Strong, Supporting | BA1, BS1, BP4 |
Combining Evidence
A single criterion usually does not determine the class. Published rules combine evidence by direction and strength. Examples include one Very Strong criterion with one Strong criterion for a Pathogenic combination, or one Strong pathogenic criterion with one or two Moderate criteria for a Likely pathogenic combination. Conflicting pathogenic and benign evidence requires review and can retain an Uncertain significance result. See the combining-rules guide for the complete implementation summary.
Computed Proposals and Review-Dependent Evidence
Folklore can evaluate eligible criteria from managed annotations and recorded case data. Other criteria depend on family, segregation, phenotype, functional, or assay evidence that needs qualified review. The interface keeps computed evidence, unavailable evidence, and reviewer-supplied evidence distinct. A generated class is a decision-support proposal, not a diagnosis or an automatic clinical sign-out.
Gene-Specific Guidance
When an applicable ClinGen Variant Curation Expert Panel specification is available, Folklore can apply its gene- or disease-specific evidence refinements. The result records the panel and specification version so the reviewer can see when a general rule was modified.
Interpretation boundary
A reproducible rules engine can apply recorded evidence consistently, but it cannot replace assessment of phenotype fit, penetrance, inheritance, assay validity, or newly published evidence. The displayed class must be reviewed in the full clinical context.
Evidence Sources and Provenance
Population frequency and gene constraint can draw on gnomAD. Splice predictions can draw on precomputed SpliceAI scores. Each source has its own build, version, coverage, and limitations. Folklore records the criteria and source context used for a result so a reviewer can inspect why the proposed class was produced.
Reference: Richards S, et al. Genetics in Medicine. 2015;17(5):405-424. PMID: 25741868
Review the criteria reference.