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Seurat v4.1

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

60,896

Version

4.1.1

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

May 2nd, 2022

Functions in Seurat (4.1.1)

AggregateExpression

Aggregated feature expression by identity class

The Assay Class

Automagically calculate a point size for ggplot2-based scatter plots

AnchorSet-class

The AnchorSet Class

Calculate module scores for feature expression programs in single cells

AverageExpression

Averaged feature expression by identity class

AddAzimuthResults

Add Azimuth Results

Augments ggplot2-based plot with a PNG image.

AnnotateAnchors

Add info to anchor matrix

AddAzimuthScores

Add Azimuth Scores

BuildClusterTree

Phylogenetic Analysis of Identity Classes

Determine text color based on background color

Color dimensional reduction plot by tree split

CollapseSpeciesExpressionMatrix

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

DE and EnrichR pathway visualization barplot

Slim down a Seurat object

Cell-cell scatter plot

Create a custom color palette

CellCycleScoring

Score cell cycle phases

Run a custom distance function on an input data matrix

Calculate the standard deviation of logged values

Combine ggplot2-based plots into a single plot

Calculate a perturbation Signature

Calculate the variance of logged values

Quickly Pick Relevant Dimensions

DiscretePalette

Discrete colour palettes from the pals package

BarcodeInflectionsPlot

Plot the Barcode Distribution and Calculated Inflection Points

The DimReduc Class

Match the case of character vectors

CollapseEmbeddingOutliers

Move outliers towards center on dimension reduction plot

Dimensional reduction plot

CalculateBarcodeInflections

Calculate the Barcode Distribution Inflection

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

Dimensional reduction heatmap

Scale and/or center matrix rowwise

Scatter plot of single cell data

Visualize 'features' on a dimensional reduction plot

Filter stray beads from Slide-seq puck

CreateSCTAssayObject

Create a SCT Assay object

Dot plot visualization

Cluster Determination

Gene expression markers for all identity classes

Feature expression heatmap

Gene expression markers of identity classes

FindMultiModalNeighbors

Construct weighted nearest neighbor graph

FindConservedMarkers

Finds markers that are conserved between the groups

Get an Assay object from a given Seurat object.

Calculate the mean of logged values

FindIntegrationAnchors

Find integration anchors

GetImage.SlideSeq

Calculate pearson residuals of features not in the scale.data

GetIntegrationData

Get integration data

Find subclusters under one cluster

GroupCorrelationPlot

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

FindTransferAnchors

Find transfer anchors

Demultiplex samples based on data from cell 'hashing'

GetTransferPredictions

Get the predicted identity

GetTissueCoordinates.SlideSeq

Get Tissue Coordinates

L2-Normalize CCA

Visualize features in dimensional reduction space interactively

JackStrawData-class

The JackStrawData Class

FindVariableFeatures

Find variable features

Determine statistical significance of PCA scores.

Normalize raw data

ISpatialDimPlot

Visualize clusters spatially and interactively

ISpatialFeaturePlot

Visualize features spatially and interactively

Hashtag oligo heatmap

Apply a ceiling and floor to all values in a matrix

Calculate the variance to mean ratio of logged values

Calculates a mixing metric

Aggregate expression of multiple features into a single feature

Calculate the percentage of a vector above some threshold

Metric for evaluating mapping success

Significant genes from a PCA

PercentageFeatureSet

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

PlotClusterTree

Plot clusters as a tree

L2-normalization

IntegrateEmbeddings

Integrate low dimensional embeddings

Label clusters on a ggplot2-based scatter plot

Load in data from remote or local mtx files

Read 10X hdf5 file

Load in data from 10X

Load a 10X Genomics Visium Image

Run Linear Discriminant Analysis

Run Independent Component Analysis on gene expression

Add text labels to a ggplot2 plot

MixscapeHeatmap

Differential expression heatmap for mixscape

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

Load the Annoy index file

HVFInfo.SCTAssay

Get Variable Feature Information

Load10X_Spatial

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

ModalityWeights-class

The ModalityWeights Class

Highlight Neighbors in DimPlot

Run Supervised Principal Component Analysis

Run Supervised Latent Semantic Indexing

Linear discriminant analysis on pooled CRISPR screen data.

PlotPerturbScore

Function to plot perturbation score distributions.

Project query into UMAP coordinates of a reference

Polygon DimPlot

Compute Jackstraw scores significance.

SelectIntegrationFeatures

Select integration features

The STARmap class

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

Use regularized negative binomial regression to normalize UMI count data

Radius.SlideSeq

Get Spot Radius

Normalize raw data to fractions

Predict value from nearest neighbors

PolyFeaturePlot

Polygon FeaturePlot

(Shared) Nearest-neighbor graph construction

FindSpatiallyVariableFeatures

Find spatially variable features

SeuratCommand-class

The SeuratCommand Class

The SCTModel Class

Single cell ridge plot

Perform Canonical Correlation Analysis

Visualize spatial clustering and expression data.

Seurat: Tools for Single Cell Genomics

The Seurat Class

The SlideSeq class

Function to prepare data for Linear Discriminant Analysis.

PrepSCTFindMarkers

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

RenameCells.SCTAssay

Rename Cells in an Object

Read output from STARsolo

Run t-distributed Stochastic Neighbor Embedding

Read output from Parse Biosciences

SpatialImage-class

The SpatialImage Class

UpdateSCTAssays

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

Visualize Dimensional Reduction genes

Splits object into a list of subsetted objects.

UpdateSymbolList

Get updated synonyms for gene symbols

Save the Annoy index

Single cell violin plot

cc.genes.updated.2019

Cell cycle genes: 2019 update

Cell cycle genes

Get image scale factors

A single heatmap from base R using image

Scale and center the data.

GroupCorrelation

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

The Graph Class

Plot a single expression by identity on a plot

Plot a single dimension

A single correlation plot

TransferAnchorSet-class

The TransferAnchorSet Class

SubsetByBarcodeInflections

Subset a Seurat Object based on the Barcode Distribution Inflection Points

IntegrationAnchorSet-class

The IntegrationAnchorSet Class

Load STARmap data

IntegrationData-class

The IntegrationData Class

SingleRasterMap

A single heatmap from ggplot2 using geom_raster

SetIntegrationData

Set integration data

Find the Quantile of Data

Get SCT results from an Assay

SingleSpatialPlot

Base plotting function for all Spatial plots

VariableFeaturePlot

View variable features

The VisiumV1 class

as.SingleCellExperiment

Convert objects to SingleCellExperiment objects

Find cells with highest scores for a given dimensional reduction technique

contrast-theory

Get the intensity and/or luminance of a color

Objects exported from other packages

as.sparse.H5Group

Find features with highest scores for a given dimensional reduction technique

Get nearest neighbors for given cell

subset.AnchorSet

Subset an AnchorSet object

as.Seurat.CellDataSet

Convert objects to Seurat objects

Convert objects to CellDataSet objects

Map query cells to a reference

Project Dimensional reduction onto full dataset

Calculate the local structure preservation metric

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

The Neighbor Class

PrepSCTIntegration

Prepare an object list normalized with sctransform for integration.

Merge SCTAssay objects

Regroup idents based on meta.data info

Load Slide-seq spatial data

Compute Moran's I value.

Run Principal Component Analysis