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Using Genome Sequence Data to Predict SARS-CoV-2 Detection Cycle Threshold Values
2022-11-15
epidemiology
Title + abstract only
View on medRxiv
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The continuing emergence of SARS-CoV-2 variants of concern (VOCs) presents a serious public health threat, exacerbating the effects of the COVID19 pandemic. Although millions of genomes have been deposited in public archives since the start of the pandemic, predicting SARS-CoV-2 clinical characteristics from the genome sequence remains challenging. In this study, we used a collection of over 29,000 high quality SARS-CoV-2 genomes to build machine learning models for predicting clinical detection...
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