10x Genomics
Chromium Single Cell Gene Expression

Cell Ranger2.2, printed on 11/14/2024

Secondary Analysis in R

Third-Party Analysis Packages

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.

• Seurat by the Satija Lab at New York Genome Center
  • See the tutorial named "Unsupervised identification of immune cell types and biomarkers from 2,700 PMBCs (10X Chromium)" at the Seurat website.
  • Additional Seurat R tutorial script for the PBMC 33,000 Cell Dataset

If you are a developer of scRNA-seq analysis software and would like to be listed here, please e-mail opensource@10xgenomics.com.

Cell Ranger R kit - Analysis Intro

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.

Installation

Install R

R version 3.1 or greater is required for Cell Ranger R Kit and its dependencies.

• Download R for Windows from CRAN
• Download R for macOS from CRAN
• Download R for Linux from CRAN

Note for macOS: If you do not already have X11 installed in Applications > X11, download and install it.

Install RStudio

RStudio is a graphical development environment you can use as an alternative to command line R. RStudio requires R to be installed.

• Download RStudio for your operating system

Install Cell Ranger R Kit

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")

• Cell Ranger R Kit 2.0 Release Notes
• Cell Ranger R Kit 1.1 Release Notes

Once R Kit is successfully installed, confirm that you can load the cellrangerRkit library in R.

> library(cellrangerRkit)
> packageVersion("cellrangerRkit")
[1] '2.0.0'

Using Cell Ranger R Kit

After successful installation, you can learn how to use R Kit to analyze Cell Ranger data with the following tutorials, also called "R vignettes":

• Introduction to R Kit with PBMC Data