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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 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.

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Version

Install

install.packages('Seurat')

Monthly Downloads

77,910

Version

5.4.0

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

December 14th, 2025

Functions in Seurat (5.4.0)

Determine text color based on background color

BarcodeInflectionsPlot

Plot the Barcode Distribution and Calculated Inflection Points

Calculate dispersion of features

Seurat-CCA Integration

CalculateBarcodeInflections

Calculate the Barcode Distribution Inflection

BridgeCellsRepresentation

Construct a dictionary representation for each unimodal dataset

BuildClusterTree

Phylogenetic Analysis of Identity Classes

BuildNicheAssay

Construct an assay for spatial niche analysis

Match the case of character vectors

Color dimensional reduction plot by tree split

CellCycleScoring

Score cell cycle phases

Calculate a perturbation Signature

Cell-cell scatter plot

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

Slim down a Seurat object

BridgeReferenceSet-class

The BridgeReferenceSet Class The BridgeReferenceSet is an output from PrepareBridgeReference

Find variable features based on dispersion

Combine ggplot2-based plots into a single plot

DE and EnrichR pathway visualization barplot

FastRPCAIntegration

Perform integration on the joint PCA cell embeddings.

Create a custom color palette

Dot plot visualization

Feature expression heatmap

Generate CountSketch random matrix

CreateCategoryMatrix

Create one hot matrix for a given label

Scale and/or center matrix rowwise

The DimReduc Class

Gene expression markers for all identity classes

FindBridgeIntegrationAnchors

Find integration bridge anchors between query and extended bridge-reference

DiscretePalette

Discrete colour palettes from pals

FindBridgeAnchor

Find bridge anchors between two unimodal datasets

Quickly Pick Relevant Dimensions

CollapseEmbeddingOutliers

Move outliers towards center on dimension reduction plot

Dimensional reduction heatmap

CollapseSpeciesExpressionMatrix

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

CreateSCTAssayObject

Create a SCT Assay object

Scatter plot of single cell data

Visualize 'features' on a dimensional reduction plot

Calculate the standard deviation of logged values

Run a custom distance function on an input data matrix

Calculate the variance of logged values

FetchResidualSCTModel

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

Get the Pearson residuals from an sctransform-normalized dataset.

Calculate the mean of logged values

Dimensional reduction plot

FindBridgeTransferAnchors

Find bridge anchors between query and extended bridge-reference

FindConservedMarkers

Finds markers that are conserved between the groups

Cluster Determination

FindTransferAnchors

Find transfer anchors

FindVariableFeatures

Find variable features

FindMultiModalNeighbors

Construct weighted nearest neighbor graph

(Shared) Nearest-neighbor graph construction

GetImage.SlideSeq

Find subclusters under one cluster

FindSpatiallyVariableFeatures

Find spatially variable features

FetchResiduals_reference

temporal function to get residuals from reference

GetIntegrationData

Get integration data

Filter stray beads from Slide-seq puck

Format10X_GeoJson_CellID

Format 10X Genomics GeoJson cell IDs

Gaussian sketching

Get an Assay object from a given Seurat object.

Calculate pearson residuals of features not in the scale.data

Visualize features in dimensional reduction space interactively

Demultiplex samples based on data from cell 'hashing'

GetTransferPredictions

Get the predicted identity

The Graph Class

GroupCorrelation

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

GroupCorrelationPlot

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

ImageFeaturePlot

Spatial Feature Plots

Spatial Cluster Plots

GetTissueCoordinates.SlideSeq

Get Tissue Coordinates

JackStrawData-class

The JackStrawData Class

ISpatialFeaturePlot

Visualize features spatially and interactively

Determine statistical significance of PCA scores.

ISpatialDimPlot

Visualize clusters spatially and interactively

FindIntegrationAnchors

Find integration anchors

Gene expression markers of identity classes

JointPCAIntegration

Seurat-Joint PCA Integration

Load10X_Spatial

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

IntegrationAnchorSet-class

The IntegrationAnchorSet Class

IntegrateLayers

Integrate Layers

InteractiveSpatialPlot

Interactive Spatial Cell Selection Tool

IntegrationData-class

The IntegrationData Class

Label clusters on a ggplot2-based scatter plot

Hashtag oligo heatmap

Add text labels to a ggplot2 plot

L2-Normalize CCA

LoadCurioSeeker

Load Curio Seeker data

Load STARmap data

Normalize Raw Data

Calculate the local structure preservation metric

L2-normalization

Metric for evaluating mapping success

Aggregate expression of multiple features into a single feature

Highlight Neighbors in DimPlot

ModalityWeights-class

The ModalityWeights Class

Calculates a mixing metric

Apply a ceiling and floor to all values in a matrix

HVFInfo.SCTAssay

Get Variable Feature Information

HarmonyIntegration

Harmony Integration

Leverage Score Calculation

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

IntegrateEmbeddings

Integrate low dimensional embeddings

Convert Neighbor class to an asymmetrical Graph class

The Neighbor Class

Calculate the percentage of a vector above some threshold

Load the Annoy index file

Function to prepare data for Linear Discriminant Analysis.

Predict value from nearest neighbors

PlotClusterTree

Plot clusters as a tree

PlotPerturbScore

Function to plot perturbation score distributions.

Map query cells to a reference

Find variable features based on mean.var.plot

Significant genes from a PCA

Polygon DimPlot

PolyFeaturePlot

Polygon FeaturePlot

MixscapeHeatmap

Differential expression heatmap for mixscape

Calculate the variance to mean ratio of logged values

Linear discriminant analysis on pooled CRISPR screen data.

PseudobulkExpression

Pseudobulk Expression

PercentageFeatureSet

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

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

Project full data to the sketch assay

Project Dimensional reduction onto full dataset

Load in data from remote or local mtx files

Read and Load Akoya CODEX data

Project query into UMAP coordinates of a reference

ProjectCellEmbeddings

Project query data to the reference dimensional reduction

Read10X_ScaleFactors

Load 10X Genomics Visium Scale Factors

PrepareBridgeReference

Prepare the bridge and reference datasets

Load in data from 10X

Read 10X hdf5 file

Read10X_probe_metadata

Read10x Probe Metadata

ProjectDimReduc

Project query data to reference dimensional reduction

PrepSCTFindMarkers

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

PrepSCTIntegration

Prepare an object list normalized with sctransform for integration.

ProjectIntegration

Integrate embeddings from the integrated sketched.assay

RPCAIntegration

Seurat-RPCA Integration

Read10X_Coordinates

Load 10X Genomics Visium Tissue Positions

Read Data From Vitessce

Read10X_HD_GeoJson

Load 10X Genomics GeoJson

Read and Load MERFISH Input from Vizgen

Read output from Parse Biosciences

Radius.SlideSeq

Get Spot Radius

Run Linear Discriminant Analysis

Read and Load Nanostring SMI data

Run Leiden clustering algorithm

RunGraphLaplacian

Run Graph Laplacian Eigendecomposition

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

Read output from STARsolo

Load a 10X Genomics Visium Image

Normalize raw data to fractions

Read10X_Segmentations

Load 10X Genomics Visium Cell Segmentations

Run Supervised Latent Semantic Indexing

Run Independent Component Analysis on gene expression

Run Supervised Principal Component Analysis

Save the Annoy index

Compute Moran's I value.

RenameCells.SCTAssay

Rename Cells in an Object

Scale and center the data.

Get image scale factors

SetIntegrationData

Set integration data

Find the Quantile of Data

SingleImagePlot

Single Spatial Plot

Run Principal Component Analysis

Run t-distributed Stochastic Neighbor Embedding

The Seurat Class

Seurat: Tools for Single Cell Genomics

Plot a single dimension

The STARmap class

A single correlation plot

SeuratCommand-class

The SeuratCommand Class

Read and Load 10x Genomics Xenium in-situ data

Regroup idents based on meta.data info

Perform sctransform-based normalization

Compute Jackstraw scores significance.

Load Slide-seq spatial data

SingleRasterMap

A single heatmap from ggplot2 using geom_raster

Single cell ridge plot

Splits object into a list of subsetted objects.

Visualize spatial clustering and expression data.

SelectIntegrationFeatures

Select integration features

The VisiumV1 class

Visualize Dimensional Reduction genes

Single cell violin plot

Find features with highest scores for a given dimensional reduction technique

Get nearest neighbors for given cell

UpdateSCTAssays

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

TransferAnchorSet-class

The TransferAnchorSet Class

fortify-Spatial

Prepare Coordinates for Spatial Plots

contrast-theory

Get the intensity and/or luminance of a color

Convert objects to CellDataSet objects

The VisiumV2 class

Perform Canonical Correlation Analysis

Plot a single expression by identity on a plot

Get SCT results from an Assay

The SCTModel Class

SelectSCTIntegrationFeatures

Select SCT integration features

SelectIntegrationFeatures5

Select integration features

SubsetByBarcodeInflections

Subset a Seurat Object based on the Barcode Distribution Inflection Points

SingleSpatialPlot

Base plotting function for all Spatial plots

A single heatmap from base R using image

TransferSketchLabels

Transfer data from sketch data to full data

as.sparse.H5Group

as.SingleCellExperiment

Convert objects to SingleCellExperiment objects

Find cells with highest scores for a given dimensional reduction technique

UnSketchEmbeddings

Transfer embeddings from sketched cells to the full data

UpdateSymbolList

Get updated synonyms for gene symbols

SpatialImage-class

The SpatialImage Class

The SlideSeq class

Variance Stabilizing Transformation

as.Seurat.CellDataSet

Convert objects to Seurat objects

Merge SCTAssay objects

Objects exported from other packages

subset.AnchorSet

Subset an AnchorSet object

VariableFeaturePlot

View variable features

Cell cycle genes

cc.genes.updated.2019

Cell cycle genes: 2019 update

writing-integration

Writing Integration Method Functions

Augments ggplot2-based plot with a PNG image.

Automagically calculate a point size for ggplot2-based scatter plots

Calculate module scores for feature expression programs in single cells

AnchorSet-class

The AnchorSet Class

AddAzimuthScores

Add Azimuth Scores

AverageExpression

Averaged feature expression by identity class

AddAzimuthResults

Add Azimuth Results

AggregateExpression

Aggregated feature expression by identity class

AnnotateAnchors

Add info to anchor matrix

The Assay Class