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 parallel 、 Interoperability 、 Open source 、 Biology 、 Genomics 、 Multiplex 、 Data mining 、 Multiplexing 、 Personalized medicine 、 Software
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