ShinyDisVar: A web application for identifying disease- and trait-associated variants using large-scale personal genetic information

Existing web-based tools for identifying disease- and trait-associated genetic variants often struggle with scalability and limited database coverage. Their usability in routine genetic analysis and research is often reduced by a lack of support for whole-genome variants and incompatibility with the Genome Reference Consortium Human Build 38 (GRCh38). We developed ShinyDisVar, a web application built with the R Shiny framework. The application supports large-scale variant analysis from genomes by accepting whole-genome variant calling format (VCF) files and querying six integrated disease- and trait-related variant databases: GWAS Catalog, GWASdb, GRASP, GADCDC, Johnson and O’Donnell Database, and ClinVar. All databases were mapped to the GRCh38 genome assembly. Benchmarking was conducted using whole-genome VCF files from ten individuals in the 1000 Genomes Project, each containing 3.87 to 4.74 million variants. Moreover, unlike existing tools, ShinyDisVar uniquely reports disease and trait frequencies, quantifying how often each disease or trait appears across matched variants alongside per-database hit frequency. ShinyDisVar completed variant reading and analysis within 42 to 59 s per sample. Validation tests demonstrated 100% sensitivity and 100% specificity when comparing outputs to known pathogenic and negative control datasets. The platform supports up to 9.5 million variants per file and delivers results in both tabular and graphical formats, allowing users to explore disease- and trait-associations interactively and export results for further analysis. ShinyDisVar addresses the limitations of current web tools by supporting whole-genome VCF input, integrating multiple curated disease and trait databases, and providing fast, accurate, and accessible variant analysis. It enables researchers and clinicians to identify disease- and trait-associated variants without requiring local computational infrastructure or programming expertise. ShinyDisVar is freely available as a user-friendly solution for large-scale genomic variant interpretation in both research and clinical contexts.