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Seurat v5

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

We are excited to release Seurat v5! This update introduces new functionality for spatial, multimodal, and scalable single-cell analysis.
Seurat v5 is backwards-compatible with previous versions, so that users will continue to be able to re-run existing workflows.

Installation instructions, documentation, and tutorials can be found at:

https://satijalab.org/seurat

Seurat can be successfully installed in R on any system (Mac OS X, Linux, Windows).

Improvements and new features are added on a regular basis. For the most up-to-date development version, refer to the main branch. For the most recent version released on CRAN, refer to the cran branch.

Please post under Issues with any bug reports, feature requests, etc., and use Discussions to engage with the wider Seurat community on analysis questions and other topics. PRs are welcome if you would like to contribute.

For a version history/changelog, please see the NEWS file.

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Version

Install

install.packages('Seurat')

Monthly Downloads

70,361

Version

6.0.0

License

MIT + file LICENSE

Issues

Pull Requests

Stars

Forks

Repository

https://github.com/satijalab/seurat

Homepage

https://satijalab.org/seurat

Maintainer

Paul Hoffman

Last Published

November 7th, 2026

Functions in Seurat (6.0.0)

Calculate a perturbation Signature

CalculateBarcodeInflections

Calculate the Barcode Distribution Inflection

Match the case of character vectors

CreateCategoryMatrix

Create one hot matrix for a given label

CellCycleScoring

Score cell cycle phases

Color dimensional reduction plot by tree split

Scale and/or center matrix rowwise

FastRPCAIntegration

Perform integration on the joint PCA cell embeddings.

BridgeCellsRepresentation

Construct a dictionary representation for each unimodal dataset

Combine ggplot2-based plots into a single plot

Generate CountSketch random matrix

Get a vector of cell names associated with an image (or set of images)

BuildClusterTree

Phylogenetic Analysis of Identity Classes

Create a custom color palette

Visualize 'features' on a dimensional reduction plot

BridgeReferenceSet-class

The BridgeReferenceSet Class The BridgeReferenceSet is an output from PrepareBridgeReference

BuildNicheAssay

Construct an assay for spatial niche analysis

Quickly Pick Relevant Dimensions

CollapseEmbeddingOutliers

Move outliers towards center on dimension reduction plot

CollapseSpeciesExpressionMatrix

Slim down a multi-species expression matrix, when only one species is primarily of interenst.

Dimensional reduction heatmap

Dimensional reduction plot

FindBridgeIntegrationAnchors

Find integration bridge anchors between query and extended bridge-reference

Calculate the mean of logged values

DE and EnrichR pathway visualization barplot

CreateSCTAssayObject

Create a SCT Assay object

FindTransferAnchors

Find transfer anchors

FindBridgeTransferAnchors

Find bridge anchors between query and extended bridge-reference

Calculate the standard deviation of logged values

Feature expression heatmap

Dot plot visualization

Run a custom distance function on an input data matrix

Calculate the variance of logged values

Visualize features in dimensional reduction space interactively

DiscretePalette

Discrete colour palettes from pals

The DimReduc Class

ISpatialDimPlot

Visualize clusters spatially and interactively

FindVariableFeatures

Find variable features

FetchResiduals_reference

temporal function to get residuals from reference

ISpatialFeaturePlot

Visualize features spatially and interactively

Get the Pearson residuals from an sctransform-normalized dataset.

FetchResidualSCTModel

Calculate pearson residuals of features not in the scale.data This function is the secondary function under FetchResiduals

Scatter plot of single cell data

FindIntegrationAnchors

Find integration anchors

Gene expression markers of identity classes

GetIntegrationData

Get integration data

GetImage.SlideSeq

GetTransferPredictions

Get the predicted identity

Filter stray beads from Slide-seq puck

The Graph Class

Cell-cell scatter plot

Cluster Determination

Slim down a Seurat object

Find variable features based on dispersion

GetTissueCoordinates.SlideSeq

Get Tissue Coordinates

Calculate pearson residuals of features not in the scale.data

Spatial Cluster Plots

Gene expression markers for all identity classes

FindBridgeAnchor

Find bridge anchors between two unimodal datasets

FindConservedMarkers

Finds markers that are conserved between the groups

Calculate the variance to mean ratio of logged values

JackStrawData-class

The JackStrawData Class

ImageFeaturePlot

Spatial Feature Plots

Determine statistical significance of PCA scores.

Normalize Raw Data

Calculate the percentage of a vector above some threshold

PercentageFeatureSet

Calculate the percentage of all counts that belong to a given set of features

ModalityWeights-class

The ModalityWeights Class

Linear discriminant analysis on pooled CRISPR screen data.

Label clusters on a ggplot2-based scatter plot

(Shared) Nearest-neighbor graph construction

FindMultiModalNeighbors

Construct weighted nearest neighbor graph

Gaussian sketching

Find Multi-Modal Nearest Neighbors

Find Single-Modality Nearest Neighbors

Add text labels to a ggplot2 plot

JointPCAIntegration

Seurat-Joint PCA Integration

LoadAteraCodewords

Load per-codeword transcript breakdowns for specific genes

HVFInfo.SCTAssay

Get Variable Feature Information

HarmonyIntegration

Harmony Integration

LoadAteraMolecules

Fetch additional Atera transcript molecules for genes not yet loaded

Function to prepare data for Linear Discriminant Analysis.

LoadCurioSeeker

Load Curio Seeker data

LoadAteraSegmentations

Add segmentation polygons to an Atera field of view, for only the cells currently present in it

GroupCorrelation

Compute the correlation of features broken down by groups with another covariate

FindSpatiallyVariableFeatures

Find spatially variable features

Demultiplex samples based on classification method from MULTI-seq (McGinnis et al., bioRxiv 2018)

Find subclusters under one cluster

PrepSCTFindMarkers

Prepare object to run differential expression on SCT assay with multiple models

GroupCorrelationPlot

Boxplot of correlation of a variable (e.g. number of UMIs) with expression data

Read 10X hdf5 file

Find variable features based on mean.var.plot

PrepSCTIntegration

Prepare an object list normalized with sctransform for integration.

The Neighbor Class

NormalizeChiSquared

Apply Chi-squared normalization to a Seurat object

Load in data from 10X

Project query into UMAP coordinates of a reference

PseudobulkExpression

Pseudobulk Expression

Read10X_probe_metadata

Read10x Probe Metadata

IntegrateEmbeddings

Integrate low dimensional embeddings

Demultiplex samples based on data from cell 'hashing'

GenerateSampleObject

Generate a sample-level count matrix based on landmark assay and its weighted.nn object

Get an Assay object from a given Seurat object.

PrepareBridgeReference

Prepare the bridge and reference datasets

Radius.SlideSeq

Get Spot Radius

Run t-distributed Stochastic Neighbor Embedding

Aggregate expression of multiple features into a single feature

Apply a ceiling and floor to all values in a matrix

Hashtag oligo heatmap

Read10X_Segmentations

Load 10X Genomics Visium Cell Segmentations

Highlight Neighbors in DimPlot

IntegrateLayers

Integrate Layers

Read and Load Akoya CODEX data

ProjectDimReduc

Project query data to reference dimensional reduction

Convert Neighbor class to an asymmetrical Graph class

Read Data From Vitessce

Read and Load MERFISH Input from Vizgen

IntegrationAnchorSet-class

The IntegrationAnchorSet Class

Read output from STARsolo

Run Leiden clustering algorithm

Visualize spatial and clustering (dimensional reduction) data in a linked, interactive framework

InteractiveSpatialPlot

Interactive Spatial Cell Selection Tool

L2-Normalize CCA

IntegrationData-class

The IntegrationData Class

ProjectIntegration

Integrate embeddings from the integrated sketched.assay

Leverage Score Calculation

PlotPerturbScore

Function to plot perturbation score distributions.

Read10X_HD_GeoJson

Load 10X Genomics GeoJson

Polygon DimPlot

Read10X_Coordinates

Load 10X Genomics Visium Tissue Positions

as.sparse.H5Group

Find the Quantile of Data

Project full data to the sketch assay

L2-normalization

Project Dimensional reduction onto full dataset

Read10X_ScaleFactors

Load 10X Genomics Visium Scale Factors

Run Partial Least Squares (PLS) on Seurat Objects

Run Principal Component Analysis

subset.AnchorSet

Subset an AnchorSet object

SetIntegrationData

Set integration data

Load Slide-seq spatial data

A single correlation plot

Plot a single dimension

SelectIntegrationFeatures

Select integration features

SpatialImage-class

The SpatialImage Class

RunGraphLaplacian

Run Graph Laplacian Eigendecomposition

Load STARmap data

VariableFeaturePlot

View variable features

Visualize spatial clustering and expression data.

Variance Stabilizing Transformation

Load a 10X Genomics Visium Image

RunDiffusionMap

Run Diffusion Map

Compute Jackstraw scores significance.

Run the mark variogram computation on a given position matrix and expression matrix.

The Seurat Class

Load10X_Spatial

Load a 10x Genomics Visium Spatial Experiment into a Seurat object

writing-integration

Writing Integration Method Functions

Load the Annoy index file

Calculate the local structure preservation metric

Map query cells to a reference

Read output from Parse Biosciences

Read and Load Nanostring SMI data

SketchDataByGroup

Sketch Data by Group

The SCTModel Class

Significant genes from a PCA

Metric for evaluating mapping success

ProjectCellEmbeddings

Project query data to the reference dimensional reduction

Normalize raw data to fractions

Load Atera spatial data

PlotClusterTree

Plot clusters as a tree

TransferAnchorSet-class

The TransferAnchorSet Class

Seurat: Tools for Single Cell Genomics

Find cells with highest scores for a given dimensional reduction technique

Get SCT results from an Assay

Kernel Partial Least Squares

Find features with highest scores for a given dimensional reduction technique

Convert objects to CellDataSet objects

as.Seurat.CellDataSet

Convert objects to Seurat objects

Calculates a mixing metric

Compute Moran's I value.

Merge SCTAssay objects

Plot a single expression by identity on a plot

SelectIntegrationFeatures5

Select integration features

MixscapeHeatmap

Differential expression heatmap for mixscape

RPCAIntegration

Seurat-RPCA Integration

SubsetByBarcodeInflections

Subset a Seurat Object based on the Barcode Distribution Inflection Points

UnSketchEmbeddings

Transfer embeddings from sketched cells to the full data

Load in data from remote or local mtx files

PrepareSampleObject

Perform preprocessing procedures for a Seurat object to prepare for the sample-level analysis

Perform sctransform-based normalization

Predict value from nearest neighbors

PlotAnnotatedHeatmap

Plot an annotated expression heatmap of features across cells

Perform cor.test between each gene and a response variable given a Seurat object

PolyFeaturePlot

Polygon FeaturePlot

Perform Canonical Correlation Analysis

SelectSCTIntegrationFeatures

Select SCT integration features

Splits object into a list of subsetted objects.

RenameCells.SCTAssay

Rename Cells in an Object

Single cell ridge plot

Run Independent Component Analysis on gene expression

TransferSketchLabels

Transfer data from sketch data to full data

Run Linear Discriminant Analysis

Read and Load 10x Genomics Xenium in-situ data

Run Supervised Latent Semantic Indexing

Regroup idents based on meta.data info

The STARmap class

as.SingleCellExperiment

Convert objects to SingleCellExperiment objects

Run Supervised Principal Component Analysis

Get image scale factors

Scale and center the data.

Set the number of threads to use for parallel processing in Seurat

SeuratCommand-class

The SeuratCommand Class

cc.genes.updated.2019

Cell cycle genes: 2019 update

SingleImagePlot

Single Spatial Plot

Get nearest neighbors for given cell

Get the number of threads being used for parallel processing in Seurat

The SlideSeq class

The VisiumV2 class

The VisiumV1 class

A single heatmap from base R using image

Objects exported from other packages

Trajectory Differential Expression Test

Cell cycle genes

Save the Annoy index

UpdateSCTAssays

Update pre-V4 Assays generated with SCTransform in the Seurat to the new SCTAssay class

SingleRasterMap

A single heatmap from ggplot2 using geom_raster

kernelpls.IterableMatrix

Kernel Partial Least Squares for IterableMatrix

SingleSpatialPlot

Base plotting function for all Spatial plots

Single cell violin plot

cppls_ondisk.IterableMatrix

CPLS (Canonical PLS) for IterableMatrix

contrast-theory

Get the intensity and/or luminance of a color

UpdateSymbolList

Get updated synonyms for gene symbols

Visualize Dimensional Reduction genes

fortify-Spatial

Prepare Coordinates for Spatial Plots

CPLS (Canonical PLS) for On-Disk Matrices

AddAzimuthResults

Add Azimuth Results

Calculate module scores for feature expression programs in single cells

AggregateExpression

Aggregated feature expression by identity class

Augments ggplot2-based plot with a PNG image.

The Assay Class

Automagically calculate a point size for ggplot2-based scatter plots

AverageExpression

Averaged feature expression by identity class

Seurat-CCA Integration

AddAzimuthScores

Add Azimuth Scores

Calculate dispersion of features

AnchorSet-class

The AnchorSet Class

BarcodeInflectionsPlot

Plot the Barcode Distribution and Calculated Inflection Points

Determine text color based on background color

AnnotateAnchors

Add info to anchor matrix