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Seurat v4.0

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:

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

68,863

Version

4.0.6

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 16th, 2021

Functions in Seurat (4.0.6)

The Assay Class

AnnotateAnchors

Add info to anchor matrix

Automagically calculate a point size for ggplot2-based scatter plots

AddAzimuthResults

Add Azimuth Results

Calculate module scores for feature expression programs in single cells

AddAzimuthScores

Add Azimuth Scores

AverageExpression

Averaged feature expression by identity class

Augments ggplot2-based plot with a PNG image.

AnchorSet-class

The AnchorSet Class

AggregateExpression

Aggregated feature expression by identity class

Calculate a perturbation Signature

BuildClusterTree

Phylogenetic Analysis of Identity Classes

DE and EnrichR pathway visualization barplot

Combine ggplot2-based plots into a single plot

CreateSCTAssayObject

Create a SCT Assay object

Slim down a Seurat object

Run a custom distance function on an input data matrix

Create a custom color palette

Cell-cell scatter plot

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

CellCycleScoring

Score cell cycle phases

Feature expression heatmap

Calculate the variance of logged values

CollapseEmbeddingOutliers

Move outliers towards center on dimension reduction plot

Calculate the standard deviation of logged values

DiscretePalette

Discrete colour palettes from the pals package

The DimReduc Class

CollapseSpeciesExpressionMatrix

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

Quickly Pick Relevant Dimensions

CalculateBarcodeInflections

Calculate the Barcode Distribution Inflection

Calculate the mean of logged values

Match the case of character vectors

Color dimensional reduction plot by tree split

Determine text color based on background color

Dimensional reduction plot

BarcodeInflectionsPlot

Plot the Barcode Distribution and Calculated Inflection Points

Dimensional reduction heatmap

Scatter plot of single cell data

FindIntegrationAnchors

Find integration anchors

FindConservedMarkers

Finds markers that are conserved between the groups

Find subclusters under one cluster

FindMultiModalNeighbors

Construct weighted nearest neighbor graph

FindTransferAnchors

Find transfer anchors

Gene expression markers for all identity classes

Dot plot visualization

Cluster Determination

Gene expression markers of identity classes

GetIntegrationData

Get integration data

Calculate pearson residuals of features not in the scale.data

Hashtag oligo heatmap

The Graph Class

Scale and/or center matrix rowwise

Demultiplex samples based on data from cell 'hashing'

GroupCorrelationPlot

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

Get an Assay object from a given Seurat object.

Visualize 'features' on a dimensional reduction plot

Load10X_Spatial

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

IntegrationAnchorSet-class

The IntegrationAnchorSet Class

IntegrationData-class

The IntegrationData Class

GroupCorrelation

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

Filter stray beads from Slide-seq puck

FindVariableFeatures

Find variable features

(Shared) Nearest-neighbor graph construction

GetTissueCoordinates.SlideSeq

Get Tissue Coordinates

Load STARmap data

Metric for evaluating mapping success

Calculate the local structure preservation metric

GetTransferPredictions

Get the predicted identity

Aggregate expression of multiple features into a single feature

Add text labels to a ggplot2 plot

HVFInfo.SCTAssay

Get Variable Feature Information

IntegrateEmbeddings

Integrate low dimensional embeddings

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

PlotPerturbScore

Function to plot perturbation score distributions.

GetImage.SlideSeq

L2-Normalize CCA

Polygon DimPlot

ModalityWeights-class

The ModalityWeights Class

Load a 10X Genomics Visium Image

Highlight Neighbors in DimPlot

Load the Annoy index file

Apply a ceiling and floor to all values in a matrix

Radius.SlideSeq

Get Spot Radius

PercentageFeatureSet

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

Calculates a mixing metric

PlotClusterTree

Plot clusters as a tree

Read 10X hdf5 file

Load Slide-seq spatial data

Read output from STARsolo

L2-normalization

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

The Neighbor Class

Determine statistical significance of PCA scores.

Map query cells to a reference

Label clusters on a ggplot2-based scatter plot

JackStrawData-class

The JackStrawData Class

Load in data from 10X

Load in data from remote or local mtx files

Read output from Parse Biosciences

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

Compute Moran's I value.

Run Linear Discriminant Analysis

Calculate the percentage of a vector above some threshold

Project query into UMAP coordinates of a reference

Significant genes from a PCA

Perform Canonical Correlation Analysis

Project Dimensional reduction onto full dataset

Run Principal Component Analysis

RenameCells.SCTAssay

Rename Cells in an Object

SelectIntegrationFeatures

Select integration features

The SCTModel Class

Run Independent Component Analysis on gene expression

Scale and center the data.

Save the Annoy index

Run Supervised Latent Semantic Indexing

SingleRasterMap

A single heatmap from ggplot2 using geom_raster

The STARmap class

FindSpatiallyVariableFeatures

Find spatially variable features

A single heatmap from base R using image

Find the Quantile of Data

ISpatialDimPlot

Visualize clusters spatially and interactively

Visualize features in dimensional reduction space interactively

ISpatialFeaturePlot

Visualize features spatially and interactively

Seurat: Tools for Single Cell Genomics

SetIntegrationData

Set integration data

SeuratCommand-class

The SeuratCommand Class

The Seurat Class

Splits object into a list of subsetted objects.

as.SingleCellExperiment

Convert objects to SingleCellExperiment objects

as.Seurat.CellDataSet

Convert objects to Seurat objects

Find cells with highest scores for a given dimensional reduction technique

Single cell violin plot

Find features with highest scores for a given dimensional reduction technique

Convert objects to CellDataSet objects

cc.genes.updated.2019

Cell cycle genes: 2019 update

UpdateSymbolList

Get updated synonyms for gene symbols

contrast-theory

Get the intensity and/or luminance of a color

SubsetByBarcodeInflections

Subset a Seurat Object based on the Barcode Distribution Inflection Points

VariableFeaturePlot

View variable features

A single correlation plot

UpdateSCTAssays

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

Visualize Dimensional Reduction genes

The VisiumV1 class

Single cell ridge plot

Run Supervised Principal Component Analysis

SingleSpatialPlot

Base plotting function for all Spatial plots

Run t-distributed Stochastic Neighbor Embedding

The SlideSeq class

Calculate the variance to mean ratio of logged values

MixscapeHeatmap

Differential expression heatmap for mixscape

Normalize raw data

Predict value from nearest neighbors

PolyFeaturePlot

Polygon FeaturePlot

Linear discriminant analysis on pooled CRISPR screen data.

SpatialImage-class

The SpatialImage Class

PrepSCTIntegration

Prepare an object list normalized with sctransform for integration.

Function to prepare data for Linear Discriminant Analysis.

Regroup idents based on meta.data info

Get SCT results from an Assay

Normalize raw data to fractions

Use regularized negative binomial regression to normalize UMI count data

as.sparse.H5Group

Visualize spatial clustering and expression data.

Cell cycle genes

Compute Jackstraw scores significance.

Get image scale factors

Plot a single dimension

Plot a single expression by identity on a plot

TransferAnchorSet-class

The TransferAnchorSet Class

Get nearest neighbors for given cell

Merge SCTAssay objects

subset.AnchorSet

Subset an AnchorSet object

Objects exported from other packages