Variant Score Ranker-a web application for intuitive missense variant prioritization

Area of Science:

• Genetics
• Bioinformatics
• Computational Biology

Background:

• Accurate classification of missense variants as benign or pathogenic is a significant challenge in genetic research.
• Existing variant annotation tools often lack gene-specific context regarding the scores of benign population variants.
• Pathogenic variants are generally predicted to have higher deleteriousness scores than benign variants within the same gene.

Purpose of the Study:

• To develop and present a web application, Variant Score Ranker, for efficient variant annotation and gene-specific score ranking.
• To enable users to perform population-level, gene-specific variant score ranking.
• To demonstrate the utility of gene- and population-calibrated variant ranking for improving variant prioritization, using epilepsy as an example.

Main Methods:

• Development of a web application, Variant Score Ranker.
• Implementation of gene-specific variant score ranking based on population data.
• Application of the tool to prioritize variants associated with epilepsy.

Main Results:

• The Variant Score Ranker web application is available for rapid variant annotation and gene-specific ranking.
• The tool provides gene-level, population-calibrated variant scores.
• Gene- and population-calibrated scores enhance the prioritization of disease-causing variants, as shown in an epilepsy case study.

Conclusions:

• Variant Score Ranker addresses the limitations of existing tools by incorporating gene-specific population variant data.
• The application facilitates more accurate variant classification and prioritization.
• This approach can improve the diagnostic yield for genetic disorders by refining variant interpretation.