CytoExploreR is comprehensive collection of interactive exploratory cytometry analysis tools designed under a unified framework. CytoExploreR has been specifically designed to integrate all existing cytometry analysis techniques (e.g. manual gating, automated gating and dimension reduction) in a format that makes these tools freely accessible to users with no coding experience. If you are new to CytoExploreR visit https://dillonhammill.github.io/CytoExploreR/ to get started.
CytoExploreR has a minimal requirement for R 3.5.0. If necessary, newer versions of R can be installed by clicking on your operating system in this link and following the installation instructions. For the best user experience it is recommended that RStudio be installed as well. RStudio Desktop is free to download and can installed from the RStudio website.
After successfully installing R and RStudio, the following additional platform-specific tools are required:
Now that all the setup is complete, let’s install all the necessary dependencies of CytoExploreR. From within RStudio, run the following in the console to install the latest versions of the cytoverse packages from Bioconductor.
# Bioconductor
install.packages("BiocManager")
# Install cytoinstaller
remotes::install_github("RGLab/cytoinstaller")
# Install cytoverse packages
cytoinstaller::install_cyto(bioc_ver = "devel")
Now that all the dependencies are installed, let’s move on to installing CytoExploreR. To successfully install CytoExploreR users will first need to install CytoExploreRData which contains example datasets that will be used within CytoExploreR to demonstrate key features.
# CytoExploreRData
devtools::install_github("DillonHammill/CytoExploreRData")
# CytoExploreR
devtools::install_github("DillonHammill/CytoExploreR")
To ease the transition from GUI oriented software, CytoExploreR has been designed to be a consistent and auto-complete friendly package for cytometry data analysis. All exported functions from CytoExploreR are prefixed with cyto_
, followed by the name of the object you wish to change (e.g. cyto_gate_
) and finally the action that you would like to perform (e.g. cyto_gate_draw
). To see all available functions simply start typing cyto_
and you will be greeted with a complete list of exported functions that can be selected from the auto-complete dropdown list:
Some of the key features of CytoExploreR are outlined below:
cyto_setup
cyto_spillover_compute
cyto_spillover_edit
cyto_spillover_spread_compute
cyto_plot_compensation
cyto_transform
which includes support for log, arcsinh, logicle and biexponential data transformationscyto_gate_draw
cyto_gate_edit
cyto_gate_remove
cyto_gate_rename
gatingTemplate
for future useopenCyto
cyto_plot
cyto_plot_gating_scheme
cyto_plot_gating_tree
cyto_plot_profile
cyto_plot_explore
cyto_map
cyto_save
cyto_stats_compute
CytoExploreR is large package and we would not do it justice by demonstrating its usage here. Instead we will explore the use of CytoExploreR in a series of vignettes which tackle specific components of the cytometry data analysis pipeline. To work through these vignettes you will need to create a new R project (File -> New Project) and download the example datasets shipped with CytoExploreRData.
# Load required packages
library(CytoExploreR)
library(CytoExploreRData)
# Download Compensation FCS files
cyto_save(Compensation,
save_as = "Compensation-Samples")
# Download Activation FCS files
cyto_save(Activation,
save_as = "Activation-Samples")
These datasets will be used throughout the package vignettes to demonstrate the key features of CytoExploreR. A brief summary of each of the package vignettes is provided below:
The CytoExploreR
vignette outlines a basic flow cytometry data analysis pipeline, which includes steps to compensate for fluorescent spillover, transform data for visualisation and manually gate populations to export population level statistics. This vignette serves as a basic introduction to the package and users are encouraged to explore other vignettes which explore these aspects in a lot more detail.
The Visualisations
vignette will demonstrate the use of cyto_plot
, a powerful data visualisation tool to explore cytometry data.
Compensation
vignette useful in describing the process of using compensation controls to correctly compensate for fluorescent spillover.Transformations
vignette we will explore the tools available in CytoExploreR to apply log, arcsinh, biexponential and/or logicle transformations to the data.Manual Gating
vignette we will demonstrate the use of cyto_gate_draw
to interactively draw gates around populations. In particular, we will focus on the different gate types that are supported and how they can be used to gate populations.Dimensionality Reduction
vignette we will demonstrate the use of cyto_map
to produce PCA, tSNE, FIt-SNE, UMAP and EmbedSOM maps of cytometry data (coming soon).There is a changelog for the GitHub master
branch which will reflect any updates made to improve the stability, usability or plenitude of the package. Users should refer to the Changelog prior to installing new versions of the package.
CytoExploreR would not be possible without the existing flow cytometry infrastructure developed by the RGLab. CytoExploreR started out as simple plugin for openCyto to facilitate gate drawing but has evolved into a fully-fledged cytometry analysis package thanks to the support and guidance of members of the RGLab. Please take the time to check out their work on GitHub.
CytoExploreR is a maturing package which will continue to be sculpted by the feedback and feature requests of users. The GitHub master
branch will always contain the most stable build of the package. New features and updates will be made to a separate branch and merged to the master
branch when stable and tested. The Changelog will reflect any changes made to the master
branch.
The Get Started and Reference sections on the CytoExploreR website are your first port of call if you require any help. For more detailed workflows refer the Articles tab. If you encounter any issues with the functioning of the package refer to these issues to see if the problem has been identified and resolved. Feel free to post new issues on the GitHub page if they have not already been addressed.
Please note that the CytoExploreR project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.
A CytoExploreR publication is on the way, but in the meantime if you use CytoExploreR for your work please cite the package as follows:
citation("CytoExploreR")
#>
#> To cite package 'CytoExploreR' in publications use:
#>
#> Dillon Hammill (2021). CytoExploreR: Interactive Analysis of
#> Cytometry Data. R package version 1.1.0.
#> https://github.com/DillonHammill/CytoExploreR
#>
#> A BibTeX entry for LaTeX users is
#>
#> @Manual{,
#> title = {CytoExploreR: Interactive Analysis of Cytometry Data},
#> author = {Dillon Hammill},
#> year = {2021},
#> note = {R package version 1.1.0},
#> url = {https://github.com/DillonHammill/CytoExploreR},
#> }