Abstract
Motivation: Identifying and tracking recombinant strains of SARS-CoV-2 is critical to understanding the evolution of the virus and controlling its spread. But confidently identifying SARS-CoV-2 recombinants from thousands of new genome sequences that are being shared online every day is quite challenging, causing many recombinants to be missed or suffer from weeks of delay in being formally identified while undergoing expert curation. Results: We present RIVET - a software pipeline and visual platform that takes advantage of recent algorithmic advances in recombination inference to comprehensively and sensitively search for potential SARS-CoV-2 recombinants and organize the relevant information in a web interface that would help greatly accelerate the process of identifying and tracking recombinants.
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CITATION STYLE
Smith, K., Ye, C., & Turakhia, Y. (2023). Tracking and curating putative SARS-CoV-2 recombinants with RIVET. Bioinformatics, 39(9). https://doi.org/10.1093/bioinformatics/btad538
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