Author: Hayden C. Metsky; Catherine A. Freije; Tinna-Solveig F. Kosoko-Thoroddsen; Pardis C. Sabeti; Cameron Myhrvold
Title: CRISPR-based surveillance for COVID-19 using genomically-comprehensive machine learning design Document date: 2020_3_2
ID: 7tkvl894_10
Snippet: We initially screened a set of 4 designs for SHERLOCK [6, 8, 9] assays, output by ADAPT to detect SARS-CoV-2. We identified an assay, which was the best-performing and also our highest ranked design a priori . We extensively tested this assay using a synthetic RNA target and determined the limit of detection to be 10 copies/µl using both fluorescent and lateral flow detection ( Figure 1 ). This assay performs well in comparison to the recently d.....
Document: We initially screened a set of 4 designs for SHERLOCK [6, 8, 9] assays, output by ADAPT to detect SARS-CoV-2. We identified an assay, which was the best-performing and also our highest ranked design a priori . We extensively tested this assay using a synthetic RNA target and determined the limit of detection to be 10 copies/µl using both fluorescent and lateral flow detection ( Figure 1 ). This assay performs well in comparison to the recently disclosed DETECTR [10] assay (sensitivity: 70-300 cp/µl) [11] and SHERLOCK assay (10-100 cp/µl) [12] for SARS-CoV-2. A protocol for performing this assay is provided in the Methods section and can be used for testing any of the other designs we have provided.
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