An Early Pandemic Analysis of SARS-CoV-2 Population Structure and Dynamics in Arizona
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Abstract
As the COVID-19 pandemic swept across the United States, there was great differential impact on local and regional communities. One of the earliest and hardest hit regions was in New York, while at the same time Arizona (for example) had low incidence. That situation has changed dramatically, with Arizona now having the highest rate of disease increase in the country. Understanding the roots of the pandemic during the initial months is essential as the pandemic continues and reaches new heights. Genomic analysis and phylogenetic modeling of SARS-COV-2 in Arizona can help to reconstruct population composition and predict the earliest undetected introductions. This foundational work represents the basis for future analysis and understanding as the pandemic continues.
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SciScore for 10.1101/2020.05.08.20095935: (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
Software and Algorithms Sentences Resources Sequencing reads were quality filtered with BBtools (BBMap – Bushnell B. – sourceforge.net/projects/bbmap/) and mapped to a SARS-CoV-2 reference genome (MN908947). BBMapsuggested: (BBmap, RRID:SCR_016965)Maximum-likelihood phylogenies were generated using RAxML-NG v0.5.1b43 with the GTR+G4 model, as indicated by a substitution model selection analysis carried out in IQTree, with 20 distinct starting trees and 100 bootstrap replicates. RAxML-NGsuggested: NoneWe employed a Bayesian molecular clock method implemented in the BEAST v1.10.445 software package to estimate the divergence times … SciScore for 10.1101/2020.05.08.20095935: (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
Software and Algorithms Sentences Resources Sequencing reads were quality filtered with BBtools (BBMap – Bushnell B. – sourceforge.net/projects/bbmap/) and mapped to a SARS-CoV-2 reference genome (MN908947). BBMapsuggested: (BBmap, RRID:SCR_016965)Maximum-likelihood phylogenies were generated using RAxML-NG v0.5.1b43 with the GTR+G4 model, as indicated by a substitution model selection analysis carried out in IQTree, with 20 distinct starting trees and 100 bootstrap replicates. RAxML-NGsuggested: NoneWe employed a Bayesian molecular clock method implemented in the BEAST v1.10.445 software package to estimate the divergence times for the total SARS-CoV-2 dataset as well as several Arizona-specific lineages, and overall evolutionary rates. BEASTsuggested: (BEAST, RRID:SCR_010228)For both model combinations, we found convergence within and among chains using Tracer v1.6. Tracersuggested: (Tracer, RRID:SCR_019121)Results from OddPub: Thank you for sharing your code.
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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