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plotGrouper

A shiny app-based GUI wrapper for ggplot2 with built-in statistical analysis.

plotGrouper

by John D. Gagnon
University of California, San Francisco


Table of Contents

Overview
Installation
Usage
Session info
License

Overview

A shiny app-based GUI wrapper for ggplot2 with built-in statistical analysis. Import data from file and use dropdown menus and checkboxes to specify the plotting variables, graph type, and look of your plots. Once created, plots can be saved independently or stored in a report that can be saved as a pdf. If new data are added to the file, the report can be refreshed to include new data. Statistical tests can be selected and added to the graphs.

Analysis of flow cytometry data is especially integrated with plotGrouper. Count data can be transformed to return the absolute number of cells in a sample (this feature requires inclusion of the number of beads per sample and information about any dilution performed).

Examples of some of the types of plots you can create:



Installation

if (!requireNamespace("BiocManager", quietly = TRUE))
  install.packages("BiocManager")
  BiocManager::install("plotGrouper")
'Bioconductor'
BiocManager::install("plotGrouper", version = "devel")
BiocManager::install("jdgagnon/plotGrouper")

Usage

Load the package into the R session.

library(plotGrouper)

To initialize the shiny app, paste the following code in your R console and run it.

plotGrouper()

Once the web app opens, you can access the iris dataset by clicking the iris button to learn how to use the app. After the iris data loads, the selection windows will be automatically populated and a graph should be displayed.
The Raw Data tab displays the structure of the data loaded. Your file should be organized in the following way:

Unique identifier Comparisons Variables
Sample Species Sepal.Length
setosa_1 setosa 5.1
setosa_2 setosa 4.9
versicolor_1 versicolor 7
versicolor_2 versicolor 6.4
virginica_1 virginica 6.3
virginica_2 virginica 5.8
etc… etc… etc…

These columns can be titled anything you want but values in the columns are important.

After importing a data file, a Sheet column will be created and populated with the sheet name(s) from the file if it came from an excel spreadsheet or the file name if it came from a csv or tsv file.

To prevent the Shapes, Colors, or Fills from reverting to their defaults, click the Lock checkboxes.

Individual plots can be saved by clicking Save on the Plot tab or multiple plots may be arranged on a single page by clicking Add plot to report. Clicking this button will send the current plot to the Report tab and assign it a number in the Report plot # dropdown menu. To revisit a plot stored in the Report tab, select the plot you wish to restore and click Load plot from report. Changes can be made to this plot and then updated in the Report by clicking Update plot in report.

Session info

Here is the output of sessionInfo() on the system on which this package was developed:

sessionInfo()
#> R version 3.5.1 (2018-07-02)
#> Platform: x86_64-apple-darwin17.6.0 (64-bit)
#> Running under: macOS High Sierra 10.13.6
#> 
#> Matrix products: default
#> BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
#> LAPACK: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libLAPACK.dylib
#> 
#> locale:
#> [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
#> 
#> attached base packages:
#> [1] stats     graphics  grDevices utils     datasets  methods   base     
#> 
#> loaded via a namespace (and not attached):
#>  [1] compiler_3.5.1  backports_1.1.2 magrittr_1.5    rprojroot_1.3-2
#>  [5] tools_3.5.1     htmltools_0.3.6 yaml_2.2.0      Rcpp_0.12.19   
#>  [9] stringi_1.2.4   rmarkdown_1.10  highr_0.7       knitr_1.20     
#> [13] stringr_1.3.1   digest_0.6.18   evaluate_0.12



License

GNU GPL-3.0-or-later