Navigating the variant landscape: integrating MAVE data analysis into Galaxy
Creators: name: Polunina, Polina
Publisher: name: F1000 Research Limited
Year: 2024

description: Multiplexed assays of variant effect (MAVEs) have emerged as powerful tools in molecular biology, particularly in elucidating the functional consequences of genetic variants, which are pivotal for human diseases and beyond. MAVE experiments systematically introduce mutations into genes or proteins, allowing for the simultaneous assessment of thousands of variants on a particular protein function. In MAVE experiments, the results often manifest as scores that quantify the impact of genetic variants on protein stability, function, or phenotype. Researchers use these scores to identify significant variants, characterize their effects, and gain insights into the functional consequences of genetic alterations. However, the sheer volume of data generated necessitates robust storage and analysis platforms. MaveDB, a dedicated collaborative and open-source database, consolidates MAVE data, facilitating data sharing among researchers worldwide.<br>
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MAVE's significance extends prominently to cancer research and other clinical domains, where understanding variant effects is essential for precision medicine and therapeutic development. Despite its paramount importance, less than 1% of genetic variation has been functionally characterized through MAVE studies. To address this gap, researchers worldwide are performing MAVE experiments. The MAVE community collaboratively endeavors to construct an Atlas of variant effect (AVE), fostering a collective and open approach towards data standardization and sharing.<br>
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Recognizing the synergies between the Galaxy and MAVE communities, the Galaxy-MaveDB project aims to seamlessly integrate MAVE data analysis into the Galaxy platform. This integration not only enhances the visibility and reproducibility of MAVE research but also enriches the Galaxy ecosystem with valuable insights from MAVE experiments.<br>
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Current accomplishments include the development of a Galaxy data_source tool for MaveDB integration, facilitating easy access to relevant MAVE data. Moreover, MAVE scores have been successfully integrated into a Galaxy’s SARS-CoV-2 clinical surveillance pipeline, showcasing the versatility of MAVE data in cancer research and other research domains.<br>
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Future plans entail creating plugins for bidirectional data transfer between Galaxy and MaveDB, automating the process of downloading MAVE scores for reports and visualizations within Galaxy. Additionally, efforts are underway to enhance user experience, accessibility, and reproducibility of MAVE data analysis within the Galaxy platform.<br>
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Furthermore, the project aims to bridge insights from human-centric MAVE research to non-human organisms, leveraging the conservation of fundamental genes across species. By enabling comparative genomics within Galaxy, researchers can explore the functional consequences of genetic variants across diverse organisms, facilitating advancements in both clinical and basic research domains.<br>
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In conclusion, the Galaxy-MaveDB project, through the integration of MAVE data analysis into the Galaxy platform, fosters collaboration and accelerates research advancements across diverse domains.