VAT

VAT assesses the clinical significance of genetic variants identified by molecular genetic testing to determine variant pathogenicity for diagnostic and research applications.

Key Features:

• Comprehensive Data Integration: VAT integrates data from published literature, internal databases, collaborative resources, and public repositories to inform assessments.
• Evidence-Based Assessment: VAT applies rigorous statistical analyses to evaluate variant observations in general population samples and disease-specific cohorts.
• Experimental Data Evaluation: VAT incorporates experimental evidence from in vivo and in vitro studies to assess variant impact on biological function.
• Computational Predictions: VAT uses computational models to predict potential effects of genetic variants on protein structure and function.
• Holistic Evidence Weighing: VAT synthesizes evidence across data types to reach an overall conclusion on a variant's likelihood of being disease-causing.

Scientific Applications:

• Genetic diagnostics: VAT supports interpretation of variants for clinical genetic testing and diagnostic decision-making.
• Prognosis and risk assessment: VAT aids prognosis and risk assessment by classifying variant pathogenicity.
• Research on genetic disease mechanisms: VAT provides a standardized framework for research into the genetic basis of diseases and consistent variant interpretation.

Methodology:

Data collection from diverse sources; statistical analysis of population and disease-cohort observations; evaluation of experimental (in vivo and in vitro) evidence; computational modeling of variant effects; and synthesis of evidence to reach pathogenicity conclusions.