Learn R Programming

⚠️There's a newer version (5.2.1) of this package.Take me there.

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

63,510

Version

5.0.0

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 4th, 2023

Functions in Seurat (5.0.0)

CollapseSpeciesExpressionMatrix

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

FastRPCAIntegration

Perform integration on the joint PCA cell embeddings.

CollapseEmbeddingOutliers

Move outliers towards center on dimension reduction plot

Calculate dispersion of features

Scale and/or center matrix rowwise

Visualize 'features' on a dimensional reduction plot

Scatter plot of single cell data

Combine ggplot2-based plots into a single plot

Dimensional reduction heatmap

Dimensional reduction plot

CreateSCTAssayObject

Create a SCT Assay object

AverageExpression

Averaged feature expression by identity class

Create a custom color palette

BuildClusterTree

Phylogenetic Analysis of Identity Classes

BuildNicheAssay

Construct an assay for spatial niche analysis

DE and EnrichR pathway visualization barplot

Feature expression heatmap

FetchResidualSCTModel

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

Calculate pearson residuals of features not in the scale.data

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

Dot plot visualization

Run a custom distance function on an input data matrix

FindConservedMarkers

Finds markers that are conserved between the groups

Cluster Determination

GetIntegrationData

Get integration data

FindIntegrationAnchors

Find integration anchors

Calculate pearson residuals of features not in the scale.data

Gene expression markers of identity classes

Calculate module scores for feature expression programs in single cells

FindMultiModalNeighbors

Construct weighted nearest neighbor graph

Get an Assay object from a given Seurat object.

(Shared) Nearest-neighbor graph construction

GetImage.SlideSeq

AggregateExpression

Aggregated feature expression by identity class

HarmonyIntegration

Harmony Integration

JointPCAIntegration

Seurat-Joint PCA Integration

L2-Normalize CCA

Calculate the local structure preservation metric

L2-normalization

Map query cells to a reference

ISpatialDimPlot

Visualize clusters spatially and interactively

Label clusters on a ggplot2-based scatter plot

Find variable features based on mean.var.plot

Visualize features in dimensional reduction space interactively

Add text labels to a ggplot2 plot

Calculate the standard deviation of logged values

Match the case of character vectors

Find variable features based on dispersion

Determine text color based on background color

BarcodeInflectionsPlot

Plot the Barcode Distribution and Calculated Inflection Points

Slim down a Seurat object

CellCycleScoring

Score cell cycle phases

The DimReduc Class

DiscretePalette

Discrete colour palettes from pals

GetTissueCoordinates.SlideSeq

Get Tissue Coordinates

GetTransferPredictions

Get the predicted identity

ModalityWeights-class

The ModalityWeights Class

Gene expression markers for all identity classes

FindVariableFeatures

Find variable features

FindBridgeAnchor

Find bridge anchors between two unimodal datasets

FindTransferAnchors

Find transfer anchors

Normalize Raw Data

JackStrawData-class

The JackStrawData Class

Determine statistical significance of PCA scores.

ProjectDimReduc

Project query data to reference dimensional reduction

Highlight Neighbors in DimPlot

PlotPerturbScore

Function to plot perturbation score distributions.

Read 10X hdf5 file

PlotClusterTree

Plot clusters as a tree

ProjectIntegration

Integrate embeddings from the integrated sketched.assay

Calculate the variance of logged values

Read10X_probe_metadata

Read10x Probe Metadata

Generate CountSketch random matrix

RenameCells.SCTAssay

Rename Cells in an Object

Normalize raw data to fractions

FindBridgeIntegrationAnchors

Find integration bridge anchors between query and extended bridge-reference

IntegrationAnchorSet-class

The IntegrationAnchorSet Class

GroupCorrelationPlot

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

Gaussian sketching

FindBridgeTransferAnchors

Find bridge anchors between query and extended bridge-reference

Demultiplex samples based on data from cell 'hashing'

Calculate the percentage of a vector above some threshold

Get SCT results from an Assay

Save the Annoy index

Perform sctransform-based normalization

PercentageFeatureSet

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

PrepSCTFindMarkers

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

PrepSCTIntegration

Prepare an object list normalized with sctransform for integration.

CreateCategoryMatrix

Create one hot matrix for a given label

FindSpatiallyVariableFeatures

Find spatially variable features

Project full data to the sketch assay

Scale and center the data.

Load STARmap data

The Seurat Class

LoadCurioSeeker

Load Curio Seeker data

Find the Quantile of Data

SpatialImage-class

The SpatialImage Class

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

Run Linear Discriminant Analysis

Project Dimensional reduction onto full dataset

Read and Load Akoya CODEX data

Compute Jackstraw scores significance.

Get image scale factors

Load in data from remote or local mtx files

IntegrationData-class

The IntegrationData Class

Plot a single dimension

Visualize spatial clustering and expression data.

Aggregate expression of multiple features into a single feature

Convert Neighbor class to an asymmetrical Graph class

Metric for evaluating mapping success

Plot a single expression by identity on a plot

SingleRasterMap

A single heatmap from ggplot2 using geom_raster

Get nearest neighbors for given cell

TransferAnchorSet-class

The TransferAnchorSet Class

Quickly Pick Relevant Dimensions

Find subclusters under one cluster

GroupCorrelation

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

The Graph Class

Merge SCTAssay objects

Visualize Dimensional Reduction genes

fortify-Spatial

Prepare Coordinates for Spatial Plots

contrast-theory

Get the intensity and/or luminance of a color

The Neighbor Class

Load in data from 10X

SingleSpatialPlot

Base plotting function for all Spatial plots

Single cell violin plot

The VisiumV1 class

VariableFeaturePlot

View variable features

Objects exported from other packages

Load a 10X Genomics Visium Image

Apply a ceiling and floor to all values in a matrix

FetchResiduals_reference

temporal function to get residuals from reference

Calculate the mean of logged values

ISpatialFeaturePlot

Visualize features spatially and interactively

Read Data From Vitessce

Read and Load MERFISH Input from Vizgen

Single cell ridge plot

Filter stray beads from Slide-seq puck

Run Principal Component Analysis

Perform Canonical Correlation Analysis

Run Supervised Latent Semantic Indexing

The STARmap class

A single correlation plot

The SlideSeq class

Calculates a mixing metric

TransferSketchLabels

Transfer data from sketch data to full data

Hashtag oligo heatmap

HVFInfo.SCTAssay

Get Variable Feature Information

Spatial Cluster Plots

Leverage Score Calculation

IntegrateEmbeddings

Integrate low dimensional embeddings

IntegrateLayers

Integrate Layers

ImageFeaturePlot

Spatial Feature Plots

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

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

Predict value from nearest neighbors

Calculate the variance to mean ratio of logged values

MixscapeHeatmap

Differential expression heatmap for mixscape

Linear discriminant analysis on pooled CRISPR screen data.

Polygon DimPlot

Load10X_Spatial

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

Load the Annoy index file

Significant genes from a PCA

Function to prepare data for Linear Discriminant Analysis.

PolyFeaturePlot

Polygon FeaturePlot

PseudobulkExpression

Pseudobulk Expression

Run Independent Component Analysis on gene expression

Project query into UMAP coordinates of a reference

RunGraphLaplacian

Run Graph Laplacian Eigendecomposition

ProjectCellEmbeddings

Project query data to the reference dimensional reduction

PrepareBridgeReference

Prepare the bridge and reference datasets

Read and Load Nanostring SMI data

Read output from Parse Biosciences

Read output from STARsolo

The SCTModel Class

Radius.SlideSeq

Get Spot Radius

RPCAIntegration

Seurat-RPCA Integration

SingleImagePlot

Single Spatial Plot

A single heatmap from base R using image

Read and Load 10x Genomics Xenium in-situ data

Load Slide-seq spatial data

Cell cycle genes

cc.genes.updated.2019

Cell cycle genes: 2019 update

Regroup idents based on meta.data info

Compute Moran's I value.

SelectIntegrationFeatures

Select integration features

SelectIntegrationFeatures5

Select integration features

Splits object into a list of subsetted objects.

SubsetByBarcodeInflections

Subset a Seurat Object based on the Barcode Distribution Inflection Points

UpdateSCTAssays

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

UnSketchEmbeddings

Transfer embeddings from sketched cells to the full data

as.SingleCellExperiment

Convert objects to SingleCellExperiment objects

as.sparse.H5Group

subset.AnchorSet

Subset an AnchorSet object

writing-integration

Writing Integration Method Functions

Run t-distributed Stochastic Neighbor Embedding

Seurat: Tools for Single Cell Genomics

SelectSCTIntegrationFeatures

Select SCT integration features

SetIntegrationData

Set integration data

Run Supervised Principal Component Analysis

SeuratCommand-class

The SeuratCommand Class

Find features with highest scores for a given dimensional reduction technique

Variance Stabilizing Transformation

UpdateSymbolList

Get updated synonyms for gene symbols

Find cells with highest scores for a given dimensional reduction technique

Convert objects to CellDataSet objects

as.Seurat.CellDataSet

Convert objects to Seurat objects

Augments ggplot2-based plot with a PNG image.

The Assay Class

AddAzimuthScores

Add Azimuth Scores

AnnotateAnchors

Add info to anchor matrix

AddAzimuthResults

Add Azimuth Results

Automagically calculate a point size for ggplot2-based scatter plots

AnchorSet-class

The AnchorSet Class

BridgeCellsRepresentation

Construct a dictionary representation for each unimodal dataset

Calculate a perturbation Signature

Seurat-CCA Integration

CalculateBarcodeInflections

Calculate the Barcode Distribution Inflection

BridgeReferenceSet-class

The BridgeReferenceSet Class The BridgeReferenceSet is an output from PrepareBridgeReference

Cell-cell scatter plot

Color dimensional reduction plot by tree split