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) , Stuart T, Butler A, et al (2019) , and Hao, Hao, et al (2020) 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:
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
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)
News
News
All notable changes to Seurat will be documented in this file.
The format is based on Keep a Changelog
[3.0.0] - 2019-04-16
Added
New method for identifying anchors across single-cell datasets
Parallelization support via future
Additional method for demultiplexing with MULTIseqDemux
Support normalization via sctransform
New option for clustering with the Leiden algorithm
Support for reading 10X v3 files
New function to export Seurat objects for the UCSC cell browser
Support for data import from Alevin outputs
Imputation of dropped out values via ALRA
Changed
Significant code restructuring
Most occurances of "gene(s)" in function names/arguments renamed to "feature(s)"
Changes to the Seurat object class to facilitate multimodal data
New BlendPlot implementation
[2.3.4] - 2018-07-13
Added
GetIdent function added to pull identity info
Changed
DiffusionMap dependency replaced with destiny to avoid archival
Java dependency removed and functionality rewritten in Rcpp
Speed and efficiency improvements for Rcpp code
More robust duplicate handling in CellCycleScoring
[2.3.3] - 2018-07-02
Added
New HTOHeatmap function
Support for custom PNG arguments for vector-friendly plotting
Fix for 'NA'-labeled cells disappearing with custom color scale
Changed
Replaced FNN with RANN
Removed unused compiler flags
Moved several lightly-used packages from 'imports' to 'suggests'
[2.3.2] - 2018-06-11
Added
RenameCells added for easy renaming of all cells
Read10X_h5 added to read in 10X formatted h5 files
SetAssayData ensures cell order is the same between assay objects and the Seurat object
Compatability updates for ggplot2 v2.3.0
[2.3.1] - 2018-05-03
Added
Support for UMAP dimensional reduction technique
New conversion functions for SingleCellExperiment and anndata
Changed
FetchData preserves cell order
Require Matrix 1.2-14 or higher
AddModuleScore no longer densifies sparse-matrices
Various visualization fixes and improvements
Default value for latent.vars in FindMarkers/FindAllMarkers changed to NULL.
[2.3.0] - 2018-03-22
Added
Support for HTO demultiplexing
Utility functions: TransferIdent, CombineIdent, SplitObject, vector.friendly
C++ implementation for parts of BuildSNN
Preliminary parallelization support (regression and JackStraw)
Support for FItSNE
Changed
MetaDE replaced with metap for combining p-values (MetaDE was removed from CRAN)
NMF heatmaps replaced (NMF to be archived by CRAN)
[2.2.1] - 2018-02-14
Changed
MetaDE replaced with metap for combining p-values (MetaDE was removed from CRAN)
NMF heatmaps replaced (NMF to be archived by CRAN)
[2.2.0] - 2018-01-10
Added
Multiple alignment functionality with RunMultiCCA and AlignSubspace extended to multiple datasets
CalcAlignmentScore added to evaluate alignment quality
MetageneBicorPlot added to guide CC selection
Change cluster order in DoHeatmap with group.order parameter
Ability to change plotting order and add a title to DimPlot
do.clean and subset.raw options for SubsetData
Changed
JoyPlot has been replaced with RidgePlot
FindClusters is now more robust in making temp files
MetaDE support for combining p-values in DE testing
[2.1.0] - 2017-10-12
Added
Support for using MAST and DESeq2 packages for differential expression testing in FindMarkers
Support for multi-modal single-cell data via @assay slot
Changed
Default DE test changed to Wilcoxon rank sum test
[2.0.1] - 2017-08-18
Added
Now available on CRAN
Updated documentation complete with examples
Example datasets: pbmc_small
and cc.genes
C++ implementation for parts of FindVariableGenes
Minor bug fixes
[2.0.0] - 2017-07-26
Added
New method for aligning scRNA-seq datasets
Significant code restructuring
New methods for scoring gene expression and cell-cycle phases
New visualization features (do.hover, do.identify)