Cell Ranger2.0, printed on 11/14/2024
The bioinformatics community is actively developing software to analyze Chromium Single Cell data. See below for some featured examples. These packages are not supported by 10x Genomics.
If you are a developer of scRNA-seq analysis software and would like to be listed here, please e-mail opensource@10xgenomics.com.
The primary analysis output of Cell Ranger is a gene-barcode matrix. Cell Ranger R Kit is an R package for simple secondary analysis of this matrix data, including PCA and t-SNE projection, and k-means clustering. R is a programming language widely used for data analysis and visualization in statistics and computational biology.
To get started with secondary analysis using Cell Ranger R Kit, you will need to install or already have access to R. Optionally, you may also install a graphical development environment such as RStudio. Follow the steps below to install R, RStudio, and Cell Ranger R Kit.
R version 3.1 or greater is required for Cell Ranger R Kit and its dependencies.
Note for macOS: If you do not already have X11 installed in Applications > X11, download and install it.
RStudio is a graphical development environment you can use as an alternative to command line R. RStudio requires R to be installed.
Install Cell Ranger R Kit by running the following command in R. This script automatically downloads and installs the package and all of its dependencies.
> source("https://cf.10xgenomics.com/supp/cell-exp/rkit-install-2.0.0.R")
Once R Kit is successfully installed, confirm that you can load the cellrangerRkit library in R.
> library(cellrangerRkit) > packageVersion("cellrangerRkit") [1] '2.0.0'
After successful installation, you can learn how to use R Kit to analyze Cell Ranger data with the following tutorials, also called "R vignettes":