GeneVetter

GeneVetter quantifies the background prevalence of exonic variants predicted to be pathogenic to improve interpretation of DNA sequencing for monogenic rare disease diagnostics.

Key Features:

• Quantification of Background Prevalence: Calculates the frequency of exonic variants predicted to be pathogenic that occur in unaffected individuals to contextualize observed variants from DNA sequencing.
• User-Specified Filtering Parameters: Applies user-defined filters to variant sets, including gene-specific criteria and predicted-disruptive annotations, to tailor analyses.
• Power and Sample Size Support: Provides computations to inform study design by estimating power and required sample size for detecting variant-disease associations in monogenic contexts.
• Use of Population-Scale Sequence Resources: Leverages population-scale data sources such as the 1000 Genomes Project to anchor prevalence estimates of rare disruptive variants.
• Probability Estimation of Unaffected Carriers: Computes the probability that an unaffected individual carries a variant predicted to be causal based on specified filters and parameters.

Scientific Applications:

• Monogenic Disease Variant Interpretation: Supports assessment of whether identified exonic variants in sequencing data are likely causal versus part of background variation in rare monogenic disorders.
• Diagnostic Risk Reduction: Reduces false-positive attribution of pathogenicity by quantifying background prevalence to refine clinical variant interpretation.
• Genetic Study Design: Informs power and sample size decisions for studies aimed at associating rare disruptive variants with monogenic phenotypes.

Methodology:

Uses population-scale sequence resources (e.g., 1000 Genomes Project) and calculates the probability that an unaffected individual carries a variant predicted to be causal based on user-defined filtering parameters and criteria.