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

Abstract

Background: The 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, CSV and TSV 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.

Results: We 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 VCF, CSV to TSV files, GenMasterTable provides advanced functionality for concatenation, 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.

Conclusion: GenMasterTable 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.

Supplementary Information: The online version contains supplementary material available at 10.1186/s12859-025-06238-6.

Keywords: Cohort-level analysis; Desktop bioinformatics tool; Genetic variant analysis; Graphical user interface (GUI); Next-generation sequencing (NGS).

Fig. 1

GenMasterTable graphical user interface for variant filtering and exploration. Screenshot of the GenMasterTable desktop application, showing the main interface for loading and interacting with annotated variant datasets. The top panel displays the merged and parsed VCF data in a tabular format with sortable columns. The lower panel provides user-friendly filtering options, allowing intuitive column-based filtering using dropdowns and value inputs without requiring programming. Users can load or merge multiple CSV/TSV/VCF files and export filtered results directly

Fig. 2

Performance comparison of GenMasterTable with other variant analysis tools. a Execution time (log scale) for loading datasets of increasing size (from 10,000 to 100 million variants) into GenMasterTable (blue), CuteVariant (red), and Excel (green). GenMasterTable demonstrates linear scaling and superior performance for large datasets. Excel fails to handle files beyond ~ 1 million variants (black cross). b Hardware resource usage (peak CPU usage, RAM consumption, average disk read/write speeds) during the loading of a 10-million-variant dataset by GenMasterTable and CuteVariant. c Average disk read performance of GenMasterTable during the loading of a 10-million-variant dataset, using different chunksize values in the pandas.read_csv() function