cytofkit2: an integrated mass cytometry data analysis pipeline

NOTE: This is the development version of cytofkit2 package

cytofkit2

This package is designed to facilitate the analysis workflow of mass cytometry data with automatic subset identification and mapping of cellular progression. Both command line and a GUI client are provided for executing the workflow easily.

Installation

1. Install R and Rstudio

If you have never used R, please install R and Rstudio following the steps below:

Download the proper R version for your operation system from R download page.
Double-click the downloaded R installation file, install with all the defaults.
Download the proper Rstudio version for your operation system from here.
Double-click the downloaded Rstudio installation file, install with all the defaults.

Special Notes for Mac Users

For Mac OS X 10.8 or later, you need to install XQuartz to support the GUI:

Download the disk image (dmg) file for XQuartz.
Open the dmg file by double-clicking on it, you'll find XQuartz.pkg, double-click on it to run the installer, clicking through all the defaults.
After the installer runs, you'll have to restart your mac computer.

2. Install python

3. Install cytofkit2 package

The offical and stable version, please refer to

Install the stable version from Bioconductor, use:

## try http:// if https:// URLs are not supported
if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("cytofkit2")

Install this development version, use:

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("reticulate")

#### check if python is installed
vv <- system("pyv=\"$(python -V)\" | echo $pyv| grep \"Python\"")
if(vv){
 print("Python is installed")
}

#### install python package umap-learn
library(reticulate)
py_install("umap-learn")

#### install cytofkit2 from github
if(!require(devtools)){
  install.packages("devtools") # If not already installed
}
devtools::install_github("JinmiaoChenLab/cytofkit2", dependencies=TRUE)

Usage

After successfully installing the cytofkit2 package, run the following codes to open the cytofkit2 shiny_dashboard:

library("cytofkit2")
cytofkit_shiny_dashboard()

Check the following vignettes for more details: