Learn R Programming

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 updates 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.

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 post on the github page with any questions or if you would like to contribute

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

Copy Link

Version

Install

install.packages('Seurat')

Monthly Downloads

74,423

Version

5.3.1

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

October 29th, 2025

Functions in Seurat (5.3.1)

BuildNicheAssay

Construct an assay for spatial niche analysis

BuildClusterTree

Phylogenetic Analysis of Identity Classes

Calculate a perturbation Signature

CollapseSpeciesExpressionMatrix

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

CollapseEmbeddingOutliers

Move outliers towards center on dimension reduction plot

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

Dimensional reduction heatmap

Combine ggplot2-based plots into a single plot

Dimensional reduction plot

Color dimensional reduction plot by tree split

Run a custom distance function on an input data matrix

CreateSCTAssayObject

Create a SCT Assay object

Cell-cell scatter plot

CalculateBarcodeInflections

Calculate the Barcode Distribution Inflection

Match the case of character vectors

Create a custom color palette

CellCycleScoring

Score cell cycle phases

CreateCategoryMatrix

Create one hot matrix for a given label

Calculate the mean of logged values

Quickly Pick Relevant Dimensions

Generate CountSketch random matrix

Calculate the standard deviation of logged values

The DimReduc Class

DiscretePalette

Discrete colour palettes from pals

FetchResidualSCTModel

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

Calculate the variance of logged values

Gene expression markers for all identity classes

Get the Pearson residuals from an sctransform-normalized dataset.

FindBridgeAnchor

Find bridge anchors between two unimodal datasets

FastRPCAIntegration

Perform integration on the joint PCA cell embeddings.

Scale and/or center matrix rowwise

DE and EnrichR pathway visualization barplot

Feature expression heatmap

Dot plot visualization

Scatter plot of single cell data

Visualize 'features' on a dimensional reduction plot

FindIntegrationAnchors

Find integration anchors

Cluster Determination

FindConservedMarkers

Finds markers that are conserved between the groups

Find variable features based on dispersion

Get an Assay object from a given Seurat object.

FindTransferAnchors

Find transfer anchors

FetchResiduals_reference

temporal function to get residuals from reference

FindVariableFeatures

Find variable features

Filter stray beads from Slide-seq puck

FindBridgeIntegrationAnchors

Find integration bridge anchors between query and extended bridge-reference

Slim down a Seurat object

GetIntegrationData

Get integration data

Find subclusters under one cluster

Gene expression markers of identity classes

FindSpatiallyVariableFeatures

Find spatially variable features

ISpatialFeaturePlot

Visualize features spatially and interactively

Calculate pearson residuals of features not in the scale.data

The Graph Class

Spatial Cluster Plots

FindMultiModalNeighbors

Construct weighted nearest neighbor graph

FindBridgeTransferAnchors

Find bridge anchors between query and extended bridge-reference

(Shared) Nearest-neighbor graph construction

GroupCorrelation

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

JointPCAIntegration

Seurat-Joint PCA Integration

GetTransferPredictions

Get the predicted identity

GetTissueCoordinates.SlideSeq

Get Tissue Coordinates

Leverage Score Calculation

IntegrationAnchorSet-class

The IntegrationAnchorSet Class

IntegrationData-class

The IntegrationData Class

ISpatialDimPlot

Visualize clusters spatially and interactively

Visualize features in dimensional reduction space interactively

GetImage.SlideSeq

Load10X_Spatial

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

L2-normalization

HarmonyIntegration

Harmony Integration

IntegrateLayers

Integrate Layers

L2-Normalize CCA

IntegrateEmbeddings

Integrate low dimensional embeddings

Find variable features based on mean.var.plot

Label clusters on a ggplot2-based scatter plot

Map query cells to a reference

Linear discriminant analysis on pooled CRISPR screen data.

MixscapeHeatmap

Differential expression heatmap for mixscape

Demultiplex samples based on data from cell 'hashing'

Determine statistical significance of PCA scores.

GroupCorrelationPlot

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

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

Highlight Neighbors in DimPlot

Calculates a mixing metric

ModalityWeights-class

The ModalityWeights Class

Apply a ceiling and floor to all values in a matrix

Calculate the local structure preservation metric

Add text labels to a ggplot2 plot

JackStrawData-class

The JackStrawData Class

Aggregate expression of multiple features into a single feature

Calculate the percentage of a vector above some threshold

PercentageFeatureSet

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

Metric for evaluating mapping success

Polygon DimPlot

Normalize Raw Data

PolyFeaturePlot

Polygon FeaturePlot

PseudobulkExpression

Pseudobulk Expression

Project query into UMAP coordinates of a reference

Load the Annoy index file

Calculate the variance to mean ratio of logged values

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

Convert Neighbor class to an asymmetrical Graph class

The Neighbor Class

Predict value from nearest neighbors

Read and Load Nanostring SMI data

Read output from Parse Biosciences

Function to prepare data for Linear Discriminant Analysis.

PrepSCTIntegration

Prepare an object list normalized with sctransform for integration.

PrepSCTFindMarkers

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

Hashtag oligo heatmap

HVFInfo.SCTAssay

Get Variable Feature Information

Gaussian sketching

ImageFeaturePlot

Spatial Feature Plots

PlotClusterTree

Plot clusters as a tree

PlotPerturbScore

Function to plot perturbation score distributions.

Run Independent Component Analysis on gene expression

RunGraphLaplacian

Run Graph Laplacian Eigendecomposition

Read output from STARsolo

Load Slide-seq spatial data

ProjectDimReduc

Project query data to reference dimensional reduction

ProjectIntegration

Integrate embeddings from the integrated sketched.assay

Read and Load MERFISH Input from Vizgen

Read Data From Vitessce

Read and Load Akoya CODEX data

Project Dimensional reduction onto full dataset

Project full data to the sketch assay

Load in data from remote or local mtx files

RPCAIntegration

Seurat-RPCA Integration

Run t-distributed Stochastic Neighbor Embedding

Run Leiden clustering algorithm

Run Linear Discriminant Analysis

Radius.SlideSeq

Get Spot Radius

SelectIntegrationFeatures

Select integration features

Compute Jackstraw scores significance.

Perform sctransform-based normalization

Normalize raw data to fractions

Run Principal Component Analysis

RenameCells.SCTAssay

Rename Cells in an Object

Compute Moran's I value.

The SCTModel Class

Get SCT results from an Assay

The Seurat Class

Seurat: Tools for Single Cell Genomics

Save the Annoy index

The STARmap class

Read and Load 10x Genomics Xenium in-situ data

Load a 10X Genomics Visium Image

Regroup idents based on meta.data info

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

Read10X_ScaleFactors

Load 10X Genomics Visium Scale Factors

Plot a single dimension

A single correlation plot

SeuratCommand-class

The SeuratCommand Class

A single heatmap from base R using image

Plot a single expression by identity on a plot

SelectIntegrationFeatures5

Select integration features

SelectSCTIntegrationFeatures

Select SCT integration features

Get nearest neighbors for given cell

SingleSpatialPlot

Base plotting function for all Spatial plots

Find features with highest scores for a given dimensional reduction technique

Load STARmap data

LoadCurioSeeker

Load Curio Seeker data

as.SingleCellExperiment

Convert objects to SingleCellExperiment objects

as.sparse.H5Group

TransferAnchorSet-class

The TransferAnchorSet Class

contrast-theory

Get the intensity and/or luminance of a color

SubsetByBarcodeInflections

Subset a Seurat Object based on the Barcode Distribution Inflection Points

Find cells with highest scores for a given dimensional reduction technique

SingleRasterMap

A single heatmap from ggplot2 using geom_raster

Visualize Dimensional Reduction genes

Single cell violin plot

The SlideSeq class

fortify-Spatial

Prepare Coordinates for Spatial Plots

SingleImagePlot

Single Spatial Plot

SpatialImage-class

The SpatialImage Class

The VisiumV1 class

The VisiumV2 class

subset.AnchorSet

Subset an AnchorSet object

writing-integration

Writing Integration Method Functions

UnSketchEmbeddings

Transfer embeddings from sketched cells to the full data

TransferSketchLabels

Transfer data from sketch data to full data

Merge SCTAssay objects

VariableFeaturePlot

View variable features

Variance Stabilizing Transformation

Load in data from 10X

Significant genes from a PCA

Read10X_Coordinates

Load 10X Genomics Visium Tissue Positions

PrepareBridgeReference

Prepare the bridge and reference datasets

ProjectCellEmbeddings

Project query data to the reference dimensional reduction

Read 10X hdf5 file

Perform Canonical Correlation Analysis

Single cell ridge plot

Run Supervised Latent Semantic Indexing

Read10X_probe_metadata

Read10x Probe Metadata

Objects exported from other packages

Run Supervised Principal Component Analysis

Visualize spatial clustering and expression data.

Scale and center the data.

Find the Quantile of Data

SetIntegrationData

Set integration data

Get image scale factors

UpdateSCTAssays

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

cc.genes.updated.2019

Cell cycle genes: 2019 update

as.Seurat.CellDataSet

Convert objects to Seurat objects

UpdateSymbolList

Get updated synonyms for gene symbols

Splits object into a list of subsetted objects.

Convert objects to CellDataSet objects

Cell cycle genes

The Assay Class

AnchorSet-class

The AnchorSet Class

Calculate module scores for feature expression programs in single cells

Augments ggplot2-based plot with a PNG image.

Automagically calculate a point size for ggplot2-based scatter plots

AddAzimuthResults

Add Azimuth Results

AnnotateAnchors

Add info to anchor matrix

AggregateExpression

Aggregated feature expression by identity class

AverageExpression

Averaged feature expression by identity class

AddAzimuthScores

Add Azimuth Scores

BridgeReferenceSet-class

The BridgeReferenceSet Class The BridgeReferenceSet is an output from PrepareBridgeReference

Seurat-CCA Integration

BridgeCellsRepresentation

Construct a dictionary representation for each unimodal dataset

Determine text color based on background color

BarcodeInflectionsPlot

Plot the Barcode Distribution and Calculated Inflection Points

Calculate dispersion of features