Seurat v3.1.3

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:

• https://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 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)