by John D. Gagnon University of California, San Francisco
Overview Installation Usage Session info License
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If you do not already have R installed, or your version is out of date, download and install the latest version.
Download the package from Bioconductor.
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("plotGrouper")
'Bioconductor'
BiocManager::install("plotGrouper", version = "devel")
BiocManager::install("jdgagnon/plotGrouper")
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.
The Unique identifier
column should contain only unique values
that identify each individual sample (e.g., Sample
within iris
Raw Data
).
The Comparisons
column should contain replicated values that
identify each individual as belonging to a group (e.g., Species
within iris
Raw Data
).
The Variables
column(s) should created for each variable you wish
to plot. The values in these columns must be numeric (e.g.,
Sepal.Length
, Sepal.Width
, Petal.Length
, Petal.Width
within
iris
Raw Data
)
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.
The Variables to plot
selection window is used to choose which
variable(s) to plot (e.g., Sepal.Width
from the iris
data). If
multiple are selected, they will be grouped according to the
Independent variable
selected.
The Comparisons
selection window is used to choose which column
contains the information that identifies which condition each sample
belongs to (e.g., the Species
column within the iris
data).
The Independent variable
selection window is used to select how
the plots should be grouped. If variable
is selected (the
default), the plots will be grouped by the values in Variables to
plot
.
Use the Shapes
selector to change the shape of the points for each
comparison variable.
Use the Colors
selector to change the point colors for each
comparison variable.
Use the Fills
selector to change the fill color for the other
geoms being plotted for each comparison variable.
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
.
The statistics calculated for the current plot being displayed in
the Plot
tab are stored in the Statistics
tab. These can be
saved by clicking the Download
button on the Statistics
tab.
The Plot Data
tab contains the reorganized subset of data being
plotted.
The Raw Data
tab displays the dataframe that was created upon
import of the file along with the automatically created Sheet
column.
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
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