Complexity in SARS-CoV-2 genome data: Price theory of mutant isolates
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Abstract
SARS-CoV-2 is a highly virulent and deadly RNA virus causing the Covid-19 pandemic and several deaths across the world. The pandemic is so fast that any concrete theory of sudden widespread of this disease is still not known. In this work, we studied and analyzed a large number of publicly available SARS-CoV-2 genomes across the world using the multifractal approach. The mutation events in the isolates obey the Markov process and exhibit very high mutational rates, which occur in six specific genes and highest in orf1ab gene, leading to virulent nature. f ( α ) analysis indicated that the isolates are highly asymmetric (left-skewed), revealing the richness of complexity and dominance by large fluctuations in genome structure organization. The values of H q and D q are found to be significantly large, showing heterogeneous genome structure self-organization, strong positive correlation in organizing the isolates, and quite sensitive to fluctuations in and around it. We then present multiple-isolates hosts-virus interaction models, and derived Price equation for the model. The phase plane analysis of the model showed asymptotic stability type bifurcation. The competition among the mutant isolates drives the trade-off of the dominant mutant isolates, otherwise confined to the present hosts.
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SciScore for 10.1101/2020.05.04.077511: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.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 …
SciScore for 10.1101/2020.05.04.077511: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.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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