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      A Public Website for the Automated Assessment and Validation of SARS-CoV-2 Diagnostic PCR Assays

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          Abstract

          Summary

          Polymerase chain reaction-based assays are the current gold standard for detecting and diagnosing SARS-CoV-2. However, as SARS-CoV-2 mutates, we need to constantly assess whether existing PCR-based assays will continue to detect all known viral strains. To enable the continuous monitoring of SARS-CoV-2 assays, we have developed a web-based assay validation algorithm that checks existing PCR-based assays against the ever-expanding genome databases for SARS-CoV-2 using both thermodynamic and edit-distance metrics. The assay screening results are displayed as a heatmap, showing the number of mismatches between each detection and each SARS-CoV-2 genome sequence. Using a mismatch threshold to define detection failure, assay performance is summarized with the true positive rate (recall) to simplify assay comparisons.

          Availability and implementation

          The assay evaluation website and supporting software are Open Source and freely available at https://covid19.edgebioinformatics.org/#/assayValidation, https://github.com/jgans/thermonucleotideBLAST, and https://github.com/LANL-Bioinformatics/assay_validation.

          Supplementary information
          btaa710_Supplementary_Data

          Supplementary data are available at Bioinformatics online.

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          Author and article information

          Journal
          Bioinformatics
          Bioinformatics
          bioinformatics
          Bioinformatics
          Oxford University Press
          1367-4803
          1367-4811
          10 August 2020
          : btaa710
          Affiliations
          Bioscience Division, Los Alamos National Laboratory , Los Alamos, New Mexico
          Author notes
          [1]

          Po-E Li and Adán Myers y Gutiérrez Contributed equally to this work.

          To whom correspondence should be addressed. E-mail: jgans@ 123456lanl.gov ) and Patrick Chain ( pchain@ 123456lanl.gov )
          Article
          btaa710
          10.1093/bioinformatics/btaa710
          7559084
          32777813
          3a33b7de-6b4e-490d-b154-c735059144ed
          © The Author(s) 2020. Published by Oxford University Press.

          This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

          History
          : 22 May 2020
          : 20 July 2020
          : 30 July 2020
          Page count
          Pages: 2
          Categories
          Applications Note
          AcademicSubjects/SCI01060
          Custom metadata
          accepted-manuscript
          PAP

          Bioinformatics & Computational biology
          Bioinformatics & Computational biology

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