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 seuratpackage@gmail.com with any questions or if you would like to contribute
Version History
August 20, 2019
- Version 3.1
- Changes:
- Support for SCTransform integration workflows
- Integration speed ups: reference-based integration + reciprocal PCA
April 12, 2019
- Version 3.0
- Changes:
- Preprint published describing new methods for identifying anchors across single-cell datasets
- Restructured Seurat object with native support for multimodal data
- Parallelization support via future
July 20, 2018
- Version 2.4
- Changes:
- Java dependency removed and functionality rewritten in Rcpp
March 22, 2018
- Version 2.3
- Changes:
- New utility functions
- Speed and efficiency improvments
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)