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Stylized image of a CLASSIX clustering result overlaid on top of a coronavirus illustration. Credit: University of Manchester, CDC / Alissa Eckert, MSMI; Dan Higgins, MAMSvariants, using a novel algorithm named CLASSIX to efficiently process large genomic datasets and enhance early detection efforts.
Roberto Cahuantzi, a researcher at The University of Manchester and first and corresponding author of the paper, said: “Since the emergence of COVID-19, we have seen multiple waves of new variants, heightened transmissibility, evasion of immune responses, and increased severity of illness. Currently, there are almost 16 million sequences available on the GISAID database , which provides access to genomic data of influenza viruses.
Thomas House, Professor of Mathematical Sciences at The University of Manchester, said: “The unprecedented amount of genetic data generated during the pandemic demands improvements to our methods to analyze it thoroughly. The data is continuing to grow rapidly but without showing a benefit to curating this data, there is a risk that it will be removed or deleted.
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