by John D. Gagnon
University of California, San Francisco
Table of Contents
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:
If you do not already have R installed, or your version is out of date, download and install the latest version.
- Optionally, install the latest version of RStudio Desktop.
Download the package from Bioconductor.
if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install("plotGrouper")
- Or install the development version of the package from Bioconductor:
'Bioconductor' BiocManager::install("plotGrouper", version = "devel")
- Or GitHub:
Load the package into the R session.
To initialize the shiny app, paste the following code in your R console and run it.
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
loads, the selection windows will be automatically populated and a graph
should be displayed.
Raw Data tab displays the structure of the data loaded. Your file
should be organized in the following way:
These columns can be titled anything you want but values in the columns are important.
Unique identifiercolumn should contain only unique values that identify each individual sample (e.g.,
Comparisonscolumn should contain replicated values that identify each individual as belonging to a group (e.g.,
Variablescolumn(s) should created for each variable you wish to plot. The values in these columns must be numeric (e.g.,
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.
Variables to plotselection window is used to choose which variable(s) to plot (e.g.,
irisdata). If multiple are selected, they will be grouped according to the
Comparisonsselection window is used to choose which column contains the information that identifies which condition each sample belongs to (e.g., the
Speciescolumn within the
Independent variableselection window is used to select how the plots should be grouped. If
variableis selected (the default), the plots will be grouped by the values in
Variables to plot.
Shapesselector to change the shape of the points for each comparison variable.
Colorsselector to change the point colors for each comparison variable.
Fillsselector to change the fill color for the other geoms being plotted for each comparison variable.
To prevent the
Fills from reverting to their
defaults, click the
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
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
The statistics calculated for the current plot being displayed in the
Plottab are stored in the
Statisticstab. These can be saved by clicking the
Downloadbutton on the
Plot Datatab contains the reorganized subset of data being plotted.
Raw Datatab displays the dataframe that was created upon import of the file along with the automatically created
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: #>  en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8 #> #> attached base packages: #>  stats graphics grDevices utils datasets methods base #> #> loaded via a namespace (and not attached): #>  compiler_3.5.1 backports_1.1.2 magrittr_1.5 rprojroot_1.3-2 #>  tools_3.5.1 htmltools_0.3.6 yaml_2.2.0 Rcpp_0.12.19 #>  stringi_1.2.4 rmarkdown_1.10 highr_0.7 knitr_1.20 #>  stringr_1.3.1 digest_0.6.18 evaluate_0.12