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Lin, Jiadong; Wang, Songbo; Audano, Peter A; Meng, Deyu; Flores, Jacob I; Kosters, Walter; Yang, Xiaofei; Jia, Peng; Marschall, Tobias; Beck, Christine R; Ye, Kai
Nature methods, 10/2022, Letnik: 19, Številka: 10Journal Article
Complex structural variants (CSVs) encompass multiple breakpoints and are often missed or misinterpreted. We developed SVision, a deep-learning-based multi-object-recognition framework, to automatically detect and haracterize CSVs from long-read sequencing data. SVision outperforms current callers at identifying the internal structure of complex events and has revealed 80 high-quality CSVs with 25 distinct structures from an individual genome. SVision directly detects CSVs without matching known structures, allowing sensitive detection of both common and previously uncharacterized complex rearrangements.
