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Seurat v4.3.0

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

47,332

Version

4.3.0.1

License

MIT + file LICENSE

Issues

Pull Requests

Stars

Forks

Repository

https://github.com/satijalab/seurat

Homepage

https://satijalab.org/seurat

Maintainer

Last Published

June 22nd, 2023

Functions in Seurat (4.3.0.1)

The Assay Class

AnchorSet-class

The AnchorSet Class

Augments ggplot2-based plot with a PNG image.

Determine text color based on background color

BarcodeInflectionsPlot

Plot the Barcode Distribution and Calculated Inflection Points

Combine ggplot2-based plots into a single plot

AddAzimuthResults

Add Azimuth Results

AnnotateAnchors

Add info to anchor matrix

CollapseSpeciesExpressionMatrix

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

CreateSCTAssayObject

Create a SCT Assay object

AddAzimuthScores

Add Azimuth Scores

Color dimensional reduction plot by tree split

Dimensional reduction heatmap

Dimensional reduction plot

Calculate module scores for feature expression programs in single cells

Feature expression heatmap

AggregateExpression

Aggregated feature expression by identity class

DE and EnrichR pathway visualization barplot

Scatter plot of single cell data

AverageExpression

Averaged feature expression by identity class

Dot plot visualization

Filter stray beads from Slide-seq puck

CalculateBarcodeInflections

Calculate the Barcode Distribution Inflection

Match the case of character vectors

Gene expression markers of identity classes

Get an Assay object from a given Seurat object.

Slim down a Seurat object

CellCycleScoring

Score cell cycle phases

Run a custom distance function on an input data matrix

GetImage.SlideSeq

GetTissueCoordinates.SlideSeq

Get Tissue Coordinates

GetTransferPredictions

Get the predicted identity

Load STARmap data

Create a custom color palette

FindMultiModalNeighbors

Construct weighted nearest neighbor graph

Cell-cell scatter plot

Calculate the standard deviation of logged values

BuildClusterTree

Phylogenetic Analysis of Identity Classes

Quickly Pick Relevant Dimensions

Calculate a perturbation Signature

Calculate the local structure preservation metric

Calculate the mean of logged values

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

Metric for evaluating mapping success

Calculate the variance of logged values

Aggregate expression of multiple features into a single feature

Significant genes from a PCA

Calculate the percentage of a vector above some threshold

Gene expression markers for all identity classes

Project query into UMAP coordinates of a reference

Cluster Determination

Radius.SlideSeq

Get Spot Radius

(Shared) Nearest-neighbor graph construction

CollapseEmbeddingOutliers

Move outliers towards center on dimension reduction plot

The DimReduc Class

FindVariableFeatures

Find variable features

Scale and/or center matrix rowwise

Visualize 'features' on a dimensional reduction plot

DiscretePalette

Discrete colour palettes from pals

FindSpatiallyVariableFeatures

Find spatially variable features

Read and Load MERFISH Input from Vizgen

GroupCorrelationPlot

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

Read and Load 10x Genomics Xenium in-situ data

RenameCells.SCTAssay

Rename Cells in an Object

GetIntegrationData

Get integration data

Find subclusters under one cluster

FindTransferAnchors

Find transfer anchors

Hashtag oligo heatmap

FindConservedMarkers

Finds markers that are conserved between the groups

FindIntegrationAnchors

Find integration anchors

Calculate pearson residuals of features not in the scale.data

The Graph Class

Demultiplex samples based on data from cell 'hashing'

HVFInfo.SCTAssay

Get Variable Feature Information

IntegrateEmbeddings

Integrate low dimensional embeddings

Single cell ridge plot

GroupCorrelation

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

IntegrationAnchorSet-class

The IntegrationAnchorSet Class

MixscapeHeatmap

Differential expression heatmap for mixscape

Determine statistical significance of PCA scores.

SelectIntegrationFeatures

Select integration features

Linear discriminant analysis on pooled CRISPR screen data.

ISpatialDimPlot

Visualize clusters spatially and interactively

SetIntegrationData

Set integration data

Visualize features in dimensional reduction space interactively

IntegrationData-class

The IntegrationData Class

Add text labels to a ggplot2 plot

JackStrawData-class

The JackStrawData Class

Load10X_Spatial

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

ISpatialFeaturePlot

Visualize features spatially and interactively

PolyFeaturePlot

Polygon FeaturePlot

The SlideSeq class

L2-Normalize CCA

Normalize raw data

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

Predict value from nearest neighbors

Read output from Parse Biosciences

SpatialImage-class

The SpatialImage Class

TransferAnchorSet-class

The TransferAnchorSet Class

Load the Annoy index file

Apply a ceiling and floor to all values in a matrix

Read output from STARsolo

Calculates a mixing metric

Visualize Dimensional Reduction genes

Get SCT results from an Assay

Calculate the variance to mean ratio of logged values

ModalityWeights-class

The ModalityWeights Class

Use regularized negative binomial regression to normalize UMI count data

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

Map query cells to a reference

Highlight Neighbors in DimPlot

PlotPerturbScore

Function to plot perturbation score distributions.

Spatial Cluster Plots

ImageFeaturePlot

Spatial Feature Plots

Function to prepare data for Linear Discriminant Analysis.

Polygon DimPlot

Single cell violin plot

Load Slide-seq spatial data

L2-normalization

Read Data From Vitessce

contrast-theory

Get the intensity and/or luminance of a color

The Neighbor Class

fortify-Spatial

Prepare Coordinates for Spatial Plots

Seurat: Tools for Single Cell Genomics

SeuratCommand-class

The SeuratCommand Class

PrepSCTFindMarkers

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

Label clusters on a ggplot2-based scatter plot

Load in data from remote or local mtx files

PercentageFeatureSet

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

Load in data from 10X

PlotClusterTree

Plot clusters as a tree

Plot a single dimension

Load a 10X Genomics Visium Image

Read and Load Nanostring SMI data

Compute Moran's I value.

Run Linear Discriminant Analysis

Perform Canonical Correlation Analysis

Plot a single expression by identity on a plot

Run Supervised Principal Component Analysis

Visualize spatial clustering and expression data.

Run Independent Component Analysis on gene expression

Splits object into a list of subsetted objects.

Run Principal Component Analysis

Run Supervised Latent Semantic Indexing

Run t-distributed Stochastic Neighbor Embedding

Find the Quantile of Data

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

A single heatmap from base R using image

PrepSCTIntegration

Prepare an object list normalized with sctransform for integration.

The STARmap class

Convert objects to CellDataSet objects

Project Dimensional reduction onto full dataset

as.Seurat.CellDataSet

Convert objects to Seurat objects

Read 10X hdf5 file

SingleImagePlot

Single Spatial Plot

Read and Load Akoya CODEX data

Get image scale factors

Regroup idents based on meta.data info

Normalize raw data to fractions

Find features with highest scores for a given dimensional reduction technique

The SCTModel Class

The Seurat Class

Merge SCTAssay objects

Objects exported from other packages

Save the Annoy index

Compute Jackstraw scores significance.

Get nearest neighbors for given cell

Scale and center the data.

SingleRasterMap

A single heatmap from ggplot2 using geom_raster

A single correlation plot

VariableFeaturePlot

View variable features

SingleSpatialPlot

Base plotting function for all Spatial plots

The VisiumV1 class

UpdateSCTAssays

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

subset.AnchorSet

Subset an AnchorSet object

SubsetByBarcodeInflections

Subset a Seurat Object based on the Barcode Distribution Inflection Points

Find cells with highest scores for a given dimensional reduction technique

UpdateSymbolList

Get updated synonyms for gene symbols

as.SingleCellExperiment

Convert objects to SingleCellExperiment objects

as.sparse.H5Group

Cell cycle genes

cc.genes.updated.2019

Cell cycle genes: 2019 update

Automagically calculate a point size for ggplot2-based scatter plots