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