MaveDB: an open-source platform to distribute and interpret data from multiplexed assays of variant effect

作者: Daniel Esposito , Jochen Weile , Jay Shendure , Lea M. Starita , Anthony T. Papenfuss

DOI: 10.1186/S13059-019-1845-6

关键词: Massively parallelInteroperabilityOpen sourceBiologyGenomicsMultiplexData miningMultiplexingPersonalized medicineSoftware

摘要: Multiplex assays of variant effect (MAVEs), such as deep mutational scans and massively parallel reporter assays, test thousands sequence variants in a single experiment. Despite the importance MAVE data for basic clinical research, there is no standard resource their discovery distribution. Here, we present MaveDB ( https://www.mavedb.org ), public repository large-scale measurements impact, designed interoperability with applications to interpret these datasets. We also describe first application, MaveVis, which retrieves, visualizes, contextualizes maps. Together, database will empower community mine powerful

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