Statistical Design and Analysis of Diagnostic Tests for Mutating Viruses
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Abstract
As the SARS-CoV-2 virus mutates, mutations harboured in patients become increasingly diverse. Patients classified into two strains may have overlapping non-variant-defining mutations.
Mutation calling by sequencing is relative to a reference genome . As SARS-CoV-2 mutates, tracking emerging mutant strains may become increasingly problematic if the reference genome remains Wuhan-Hu-1, because the comparison then becomes indirect : current dominant strain relative to Wuhan-Hu-1 versus emerging strain relative to Wuhan-Hu-1.
The original Thermo Fisher’s TaqPath PCR test, on which the UK has standardized national testing of SARS-CoV-2 primarily, targets Wuhan-Hu-1. PCR targets appear readily updated, as TaqPath 2.0 now targets both currently known and future SARS-CoV-2 mutations, probing the N gene and ORF1ab but not the S gene, with 8 probes instead of the original 3 probes. Going forward, our statistical method can more directly compare current wildtype versus emerging mutants, since our new method can use any pair of probes updated to probe the current wildtype and anticipated mutations.
The fact that patients harbour mixtures of mutations allows our statistical methods to potentially catch emerging mutants. Given a PCR test which targets the current dominant strain (current wildtype), our statistical method can potentially directly differentiate the current wildtype from an emerging strain.
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SciScore for 10.1101/2021.04.07.21254917: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization Due to the large size of the training data set, for clarify of message, the dots in Figure 2 represent only 10,000 randomly selected patients. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdent…
SciScore for 10.1101/2021.04.07.21254917: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization Due to the large size of the training data set, for clarify of message, the dots in Figure 2 represent only 10,000 randomly selected patients. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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