Tools for Single Cell Genomics

A toolkit for quality control, analysis, and exploration of single cell RNA sequencing data. 'Seurat' aims to enable users to identify and interpret sources of heterogeneity from single cell transcriptomic measurements, and to integrate diverse types of single cell data. See Satija R, Farrell J, Gennert D, et al (2015) , Macosko E, Basu A, Satija R, et al (2015) , and Butler A and Satija R (2017) for more details.

Seurat is an R toolkit for single cell genomics, developed and maintained by the Satija Lab at NYGC.

Instructions, documentation, and tutorials can be found at:

• http://www.satijalab.org/seurat

Seurat is also hosted on GitHub, you can view and clone the repository at

• https://github.com/satijalab/seurat

Seurat has been successfully installed on Mac OS X, Linux, and Windows, using the devtools package to install directly from GitHub

Improvements and new features will be added on a regular basis, please contact [email protected] with any questions or if you would like to contribute

Version History

January 10, 2018

• Version 2.2
• Changes:
  • Support for multiple-dataset alignment with RunMultiCCA and AlignSubspace
  • New methods for evaluating alignment performance

October 12, 2017

• Version 2.1
• Changes:
  • Support for using MAST and DESeq2 packages for differential expression testing in FindMarkers
  • Support for multi-modal single-cell data via @assay slot

July 26, 2017

• Version 2.0
• Changes:
  • Preprint released for integrated analysis of scRNA-seq across conditions, technologies and species
  • Significant restructuring of code to support clarity and dataset exploration
  • Methods for scoring gene expression and cell-cycle phase

October 4, 2016

• Version 1.4 released
• Changes:
  • Improved tools for cluster evaluation/visualizations
  • Methods for combining and adding to datasets

August 22, 2016:

• Version 1.3 released
• Changes :
  • Improved clustering approach - see FAQ for details
  • All functions support sparse matrices
  • Methods for removing unwanted sources of variation
  • Consistent function names
  • Updated visualizations

May 21, 2015:

• Drop-Seq manuscript published. Version 1.2 released
• Changes :
  • Added support for spectral t-SNE and density clustering
  • New visualizations - including pcHeatmap, dot.plot, and feature.plot
  • Expanded package documentation, reduced import package burden
  • Seurat code is now hosted on GitHub, enables easy install through devtools
  • Small bug fixes

April 13, 2015:

• Spatial mapping manuscript published. Version 1.1 released (initial release)