Classification
Variant classification follows the ACMG/AMP 2015 guidelines implemented through the Bayesian point-based framework (Tavtigian et al. 2018, 2020) with ClinGen SVI calibrated computational predictor thresholds (Pejaver et al. 2022) and SpliceAI integration aligned to ClinGen SVI 2023 recommendations (Walker et al. 2023).
Classification is strictly evidence-based. No machine learning model determines variant pathogenicity. The framework evaluates 28 evidence criteria -- 19 automated, 9 requiring manual curation -- and combines them using calibrated point values to produce one of five standard classifications: Pathogenic, Likely Pathogenic, VUS, Likely Benign, or Benign.
Classification Priority Order
Classification logic is applied in strict priority order. Higher-priority rules are evaluated first, and the first matching rule determines the final classification:
BA1 Stand-alone
Allele frequency > 5% is always classified Benign. BA1 cannot be overridden by any other evidence, including ClinVar assertions.
High-Confidence Conflict Check
When pathogenic evidence at Strong or Very Strong level conflicts with Strong benign evidence, the variant is flagged for manual review regardless of point total.
ClinVar Override
ClinVar classification applied only when no conflicting computational evidence exists. Requires minimum 1 review star. ClinVar VUS does not override computational classification.
Bayesian Point System
Each criterion contributes calibrated points. Total determines classification: >= 10 Pathogenic, 6-9 Likely Pathogenic, 0-5 VUS, -1 to -5 Likely Benign, <= -6 Benign.
Default
Variants not meeting any rule are classified as Variant of Uncertain Significance (VUS).
Classification Output
Each variant receives one of five ACMG classifications, a list of triggered criteria with evidence strength levels, a Bayesian point total, and a continuous confidence score.
Pathogenic
>= 10 pts
Likely Pathogenic
6-9 pts
VUS
0-5 pts
Likely Benign
-1 to -5 pts
Benign
<= -6 pts
In This Section
ACMG Framework
The ACMG/AMP 2015 variant classification standard and how Helix Insight implements it.
Criteria Reference
Complete reference for all 28 ACMG criteria -- 19 automated, 9 manual.
Combining Rules
How individual criteria are combined using the Bayesian point system to reach a classification.
ClinVar Integration
How ClinVar assertions are used as evidence and when they override computational classification.
Conflicting Evidence
How the platform handles variants with both pathogenic and benign evidence.
Confidence Scores
Continuous confidence scoring based on Bayesian point distance to classification boundaries.
For the full methodology with all thresholds and implementation details, see the dedicated Methodology page.