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An R package for analysis and visualization of COVID-19 wastewater viral signal and variant frequency data.

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viv-wang/CovidWasteWatch

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CovidWasteWatch

Description

CovidWasteWatch is an R package for analysis and visualization of COVID-19 wastewater viral signal and variant frequency data. Using user-provided pre-processed data, this package aims to provide users with various statistical backgrounds a simple and efficient way to observe trends in COVID-19 viral signal levels and variant frequencies over time. CovidWasteWatch was developed using R version 4.3.1 (2023-06-16 ucrt), Platform: x86_64-w64-mingw32/x64 (64-bit), and Running under: Windows 11 x64 (build 22621).

Installation

To install the latest version of the package:

require("devtools")
devtools::install_github("viv-wang/CovidWasteWatch", build_vignettes = TRUE)
library("CovidWasteWatch")

To run the Shiny app:

runCovidWasteWatch()

Overview

To see an overview of the package:

ls("package:CovidWasteWatch")
data(package = "CovidWasteWatch")
browseVignettes("CovidWasteWatch") 

CovidWasteWatch provides 4 functions:

  • ViralSignal() loads and extracts relevant data from a CSV file containing COVID-19 viral signal data over time, producing a statistical and graphical (line plot) overview of the data.
  • VarBreakdown() loads and extracts relevant data from a CSV file containing COVID-19 viral variant proportion data over time, producing a statistical and graphical (stacked bar plot) overview of the data.
  • PlotViralSignal() plots viral signal data from a given dataframe as a line plot, with dots as markers for each data point.
  • PlotVarBreakdown() plots viral variant breakdown data from a given dataframe as a stacked bar plot, where each stacked bar represents the variant breakdown at one time point.

For a tutorial demonstrating these functions, please see the vignettes. The package also contains two sample datasets, one for each COVID-19 data type, which are described in the data documentation and the introductory vignette.

An overview of CovidWasteWatch is illustrated below.

Contributions

The author of this package is Vivian Wang, who wrote the functions and Shiny app implementation. The data overview functions ViralSignal() and VarBreakdown() useR.utils to read the input CSV files, and dplyr to arrange the loaded datasets. The plotting functions PlotViralSignal() and PlotVarBreakdown() utilize ggplot2 to create graphical output from the processed data. runCovidWasteWatch and app.R used Shiny to provide an interactive app for this package.

References

Attali, D., Edwards, T. (2021). shinyalert: Easily Create Pretty Popup Messages (Modals) in ‘Shiny’. https://github.com/daattali/shinyalert

Bengtsson, H. (2022). R.utils: Various Programming Utilities. https://henrikbengtsson.github.io/R.utils/

Chang, W., Cheng, J., Allaire, J., Sievert, C., Schloerke, B., Xie, Y., Allen, J., McPherson, J., Dipert, A., Borges, B. (2023). shiny: Web Application Framework for R. https://github.com/rstudio/shiny, https://shiny.posit.co/

Grolemund, G. (2015). Learn Shiny - Video Tutorials. https://shiny.rstudio.com/tutorial/

Health Canada (2023). COVID-19 epidemiology update: Testing and variants. https://health-infobase.canada.ca/covid-19/testing-variants.html

Public Health Ontario (2023). COVID-19 Wastewater Surveillance in Ontario. https://www.publichealthontario.ca/en/Data-and-Analysis/Infectious-Disease/COVID-19-Data-Surveillance/Wastewater

R Core Team (2023). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/

Silva, A. (2022) TestingPackage: An Example R Package For BCB410H. https://github.com/anjalisilva/TestingPackage

Wickham, H. (2016). ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York. ISBN 978-3-319-24277-4. https://ggplot2.tidyverse.org

Wickham, H., François, R., Henry, L., Müller, K., Vaughan, D. (2023). dplyr: A Grammar of Data Manipulation. https://dplyr.tidyverse.org

Acknowledgements

This package was developed as part of an assessment for 2023 BCB410H: Applied Bioinformatics course at the University of Toronto, Toronto, CANADA. CovidWasteWatch welcomes issues, enhancement requests, and other contributions. To submit an issue, use the GitHub issues. Many thanks to those who provided feedback to improve this package.

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An R package for analysis and visualization of COVID-19 wastewater viral signal and variant frequency data.

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