Background: The expanding availability of large-scale genomic data and the growing interest in uncovering gene-disease associations call for efficient tools to visualize and evaluate gene expression and genetic variation data. Methodology: Data collection involved filtering biomarkers related to multiple neurological diseases from the ClinGen database. We developed a comprehensive pipeline that was implemented as an interactive Shiny application and a standalone desktop application. Results: NeuroVar is a tool for visualizing genetic variation (single nucleotide polymorphisms and insertions/deletions) and gene expression profiles of biomarkers of neurological diseases. Conclusion: The tool provides a user-friendly graphical user interface to visualize genomic data and is freely accessible on the project's GitHub repository (https://github.com/omicscodeathon/neurovar).

NeuroVar: An Open-source Tool for Gene Expression and Variation Data Visualization for Biomarkers of Neurological Diseases