HOME  ›   pipelines
If your question is not answered here, please email us at:  ${email.software}

10x Genomics
Chromium Single Cell Gene Expression

Secondary Analysis in R

The primary analysis output of Cell Ranger is a gene-barcode matrix. Cell Ranger R Kit is an R package for 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.

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.

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-1.1.0.R")

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] '1.1.0'

## 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":

Additional tutorials/vignettes will be released over time.

Third-Party Analysis Packages

The bioinformatics community is also actively developing software to analyze Chromium Single Cell data. See below for some featured examples. These packages are not supported by 10x Genomics.