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bioRxiv · 10.1101/2025.04.10.648172

GenMasterTable: A user-friendly desktop application for filtering, summarising, and visualising large-scale annotated genetic variants

ZHAI, J.·Pitteloud, N.·Santoni, F.
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Abstract

BackgroundThe rapid expansion of next-generation sequencing (NGS) technologies has generated vast amounts of genomic data, creating a growing demand for secure, scalable, and accessible tools to support variant interpretation. However, many existing solutions are command-line based, rely on cloud or server infrastructures that may pose data privacy risks, lack flexibility in supporting both VCF and CSV formats, or struggle to handle the scale and complexity of modern genomic datasets. There is a clear need for a user-friendly, locally operated application capable of efficiently processing annotated variant data for large-scale cohort level analysis. ResultsWe introduce GenMasterTable, a free, secure, and cross-platform desktop application designed to simplify variant analysis through an intuitive graphical user interface (GUI). As the first tool to enable comprehensive cohort-level analysis from both VCF and CSV files, GenMasterTable provides advanced functionality for merging, filtering, summarizing, and visualizing large-scale annotated datasets. Tailored for users without programming expertise, it enables rapid and accurate exploration of genetic variants, making it a practical solution for both research and clinical settings. ConclusionGenMasterTable addresses critical limitations in current variant analysis workflows by combining usability, data security, and scalability. Its support for multiple input formats and locally executed operations empowers clinicians, geneticists, and researchers to perform comprehensive variant analysis efficiently without the need for programming expertise.

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ZHAI, J., Pitteloud, N., Santoni, F.. 2025-04-16. GenMasterTable: A user-friendly desktop application for filtering, summarising, and visualising large-scale annotated genetic variants. https://doi.org/10.1101/2025.04.10.648172

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