Selected article for: "detection rate and false negative"
Author: Alejandro Lopez-Rincon; Alberto Tonda; Lucero Mendoza-Maldonado; Eric Claassen; Johan Garssen; Aletta D. Kraneveld
Title: Accurate Identification of SARS-CoV-2 from Viral Genome Sequences using Deep Learning
  • Document date: 2020_3_14
    • ID: c2lljdi7_4
    Snippet: As a typical RNA virus, new mutations appears every replication cycle of 10 Coronavirus, and its average evolutionary rate is roughly 10-4 nucleotide sub-2 . CC-BY-NC 4.0 International license author/funder. It is made available under a The copyright holder for this preprint (which was not peer-reviewed) is the . https://doi.org/10.1101/2020.03.13.990242 doi: bioRxiv preprint stitutions per site each year [2] . In the specific case of SARS-CoV-2,.....
    Document: As a typical RNA virus, new mutations appears every replication cycle of 10 Coronavirus, and its average evolutionary rate is roughly 10-4 nucleotide sub-2 . CC-BY-NC 4.0 International license author/funder. It is made available under a The copyright holder for this preprint (which was not peer-reviewed) is the . https://doi.org/10.1101/2020.03.13.990242 doi: bioRxiv preprint stitutions per site each year [2] . In the specific case of SARS-CoV-2, RT-qPCR testing using primers in ORF1ab and N genes have been used to identified the infection in humans. However, this method presents a high false negative rate (FNR), with a detection rate of 30-50% [3, 4] . This low detection rate can be 15 explained by the variation of viral RNA sequences within virus species, and the viral load in different anatomic sites [5] . Population mutation frequency of site 8,872 located in ORF1ab gene and site 28,144 located in ORF8 gene gradually increased from 0 to 29% as the epidemic progressed [6] .

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