Object interaction

Functions for interacting with a Seurat object

AnchorSet-class

The AnchorSet Class

Cells(<SCTModel>) Cells(<SlideSeq>) Cells(<STARmap>) Cells(<VisiumV1>)

Get Cell Names

CreateSCTAssayObject()

Create a SCT Assay object

DietSeurat()

Slim down a Seurat object

FilterSlideSeq()

Filter stray beads from Slide-seq puck

GetAssay()

Get an Assay object from a given Seurat object.

GetImage(<SlideSeq>) GetImage(<STARmap>) GetImage(<VisiumV1>)

Get Image Data

GetIntegrationData()

Get integration data

GetTissueCoordinates(<SlideSeq>) GetTissueCoordinates(<STARmap>) GetTissueCoordinates(<VisiumV1>)

Get Tissue Coordinates

IntegrationAnchorSet-class

The IntegrationAnchorSet Class

IntegrationData-class

The IntegrationData Class

ModalityWeights-class

The ModalityWeights Class

Radius(<SlideSeq>) Radius(<STARmap>) Radius(<VisiumV1>)

Get Spot Radius

RenameCells(<SCTAssay>) RenameCells(<SlideSeq>) RenameCells(<STARmap>) RenameCells(<VisiumV1>)

Rename Cells in an Object

levels(<SCTAssay>) `levels<-`(<SCTAssay>)

The SCTModel Class

SCTResults() `SCTResults<-`()

Get SCT results from an Assay

STARmap-class

The STARmap class

ScaleFactors() scalefactors()

Get image scale factors

SetIntegrationData()

Set integration data

SplitObject()

Splits object into a list of subsetted objects.

TopCells()

Find cells with highest scores for a given dimensional reduction technique

TopFeatures()

Find features with highest scores for a given dimensional reduction technique

TopNeighbors()

Get nearest neighbors for given cell

TransferAnchorSet-class

The TransferAnchorSet Class

UpdateSCTAssays()

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

VisiumV1-class

The VisiumV1 class

as.CellDataSet()

Convert objects to CellDataSet objects

as.Seurat(<CellDataSet>) as.Seurat(<SingleCellExperiment>)

Convert objects to Seurat objects

as.SingleCellExperiment()

Convert objects to SingleCellExperiment objects

as.sparse(<H5Group>) as.data.frame(<Matrix>)

Cast to Sparse

merge(<SCTAssay>)

Merge SCTAssay objects

subset(<AnchorSet>)

Subset an AnchorSet object

Preprocessing

Functions for preprocessing single-cell data

CalculateBarcodeInflections()

Calculate the Barcode Distribution Inflection

FindSpatiallyVariableFeatures()

Find spatially variable features

FindVariableFeatures()

Find variable features

GetResidual()

Calculate pearson residuals of features not in the scale.data

HTODemux()

Demultiplex samples based on data from cell 'hashing'

Load10X_Spatial()

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

LoadSTARmap()

Load STARmap data

LogNormalize()

Normalize raw data

MULTIseqDemux()

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

NormalizeData()

Normalize Data

Read10X()

Load in data from 10X

Read10X_Image()

Load a 10X Genomics Visium Image

Read10X_h5()

Read 10X hdf5 file

ReadMtx()

Load in data from remote or local mtx files

ReadSlideSeq()

Load Slide-seq spatial data

RelativeCounts()

Normalize raw data to fractions

RunMarkVario()

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

RunMoransI()

Compute Moran's I value.

SCTransform()

Use regularized negative binomial regression to normalize UMI count data

SampleUMI()

Sample UMI

ScaleData()

Scale and center the data.

SubsetByBarcodeInflections()

Subset a Seurat Object based on the Barcode Distribution Inflection Points

Differential expression

Functions for testing differential gene (feature) expression

FindAllMarkers()

Gene expression markers for all identity classes

FindConservedMarkers()

Finds markers that are conserved between the groups

FindMarkers()

Gene expression markers of identity classes

FoldChange()

Fold Change

Dimensional Reduction

Functions to reduce the dimensionality of datasets

JackStraw()

Determine statistical significance of PCA scores.

L2CCA()

L2-Normalize CCA

L2Dim()

L2-normalization

PCASigGenes()

Significant genes from a PCA

ProjectDim()

Project Dimensional reduction onto full dataset

ProjectUMAP()

Project query into UMAP coordinates of a reference

RunCCA()

Perform Canonical Correlation Analysis

RunICA()

Run Independent Component Analysis on gene expression

RunPCA()

Run Principal Component Analysis

RunTSNE()

Run t-distributed Stochastic Neighbor Embedding

RunUMAP()

Run UMAP

ScoreJackStraw()

Compute Jackstraw scores significance.

Clustering

Functions to cluster single-cell data

FindClusters()

Cluster Determination

FindMultiModalNeighbors()

Construct weighted nearest neighbor graph

FindNeighbors()

(Shared) Nearest-neighbor graph construction

FindSubCluster()

Find subclusters under one cluster

Integration

Functions related to the Seurat v3 integration and label transfer algorithms

AnnotateAnchors()

Add info to anchor matrix

FindIntegrationAnchors()

Find integration anchors

FindTransferAnchors()

Find transfer anchors

GetTransferPredictions()

Get the predicted identity

IntegrateData()

Integrate data

IntegrateEmbeddings()

Integrate low dimensional embeddings

LocalStruct()

Calculate the local structure preservation metric

MapQuery()

Map query cells to a reference

MappingScore()

Metric for evaluating mapping success

MixingMetric()

Calculates a mixing metric

PredictAssay()

Predict value from nearest neighbors

PrepSCTIntegration()

Prepare an object list normalized with sctransform for integration.

SelectIntegrationFeatures()

Select integration features

TransferData()

Transfer data

Spatial

Functions related to the analysis of spatially-resolved single-cell data

Cells(<SCTModel>) Cells(<SlideSeq>) Cells(<STARmap>) Cells(<VisiumV1>)

Get Cell Names

FilterSlideSeq()

Filter stray beads from Slide-seq puck

FindSpatiallyVariableFeatures()

Find spatially variable features

GetImage(<SlideSeq>) GetImage(<STARmap>) GetImage(<VisiumV1>)

Get Image Data

GetTissueCoordinates(<SlideSeq>) GetTissueCoordinates(<STARmap>) GetTissueCoordinates(<VisiumV1>)

Get Tissue Coordinates

ISpatialDimPlot()

Visualize clusters spatially and interactively

ISpatialFeaturePlot()

Visualize features spatially and interactively

LinkedDimPlot() LinkedFeaturePlot()

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

PolyFeaturePlot()

Polygon FeaturePlot

Radius(<SlideSeq>) Radius(<STARmap>) Radius(<VisiumV1>)

Get Spot Radius

STARmap-class

The STARmap class

ScaleFactors() scalefactors()

Get image scale factors

SlideSeq-class

The SlideSeq class

SpatialPlot() SpatialDimPlot() SpatialFeaturePlot()

Visualize spatial clustering and expression data.

VisiumV1-class

The VisiumV1 class

Mixscape

Functions related to the mixscape algorithm

CalcPerturbSig()

Calculate a perturbation Signature

DEenrichRPlot()

DE and EnrichR pathway visualization barplot

MixscapeHeatmap()

Differential expression heatmap for mixscape

MixscapeLDA()

Linear discriminant analysis on pooled CRISPR screen data.

PlotPerturbScore()

Function to plot perturbation score distributions.

PrepLDA()

Function to prepare data for Linear Discriminant Analysis.

RunLDA()

Run Linear Discriminant Analysis

RunMixscape()

Run Mixscape

Visualization

Functions for plotting data and adjusting

AugmentPlot()

Augments ggplot2-based plot with a PNG image.

BGTextColor()

Determine text color based on background color

BarcodeInflectionsPlot()

Plot the Barcode Distribution and Calculated Inflection Points

CellScatter()

Cell-cell scatter plot

CellSelector() FeatureLocator()

Cell Selector

CollapseEmbeddingOutliers()

Move outliers towards center on dimension reduction plot

ColorDimSplit()

Color dimensional reduction plot by tree split

CombinePlots()

Combine ggplot2-based plots into a single plot

BlackAndWhite() BlueAndRed() CustomPalette() PurpleAndYellow()

Create a custom color palette

DimHeatmap() PCHeatmap()

Dimensional reduction heatmap

DimPlot() PCAPlot() TSNEPlot() UMAPPlot()

Dimensional reduction plot

DiscretePalette()

Discrete colour palettes from the pals package

DoHeatmap()

Feature expression heatmap

DotPlot()

Dot plot visualization

ElbowPlot()

Quickly Pick Relevant Dimensions

FeaturePlot()

Visualize 'features' on a dimensional reduction plot

FeatureScatter()

Scatter plot of single cell data

GroupCorrelationPlot()

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

HTOHeatmap()

Hashtag oligo heatmap

HoverLocator()

Hover Locator

IFeaturePlot()

Visualize features in dimensional reduction space interactively

ISpatialDimPlot()

Visualize clusters spatially and interactively

ISpatialFeaturePlot()

Visualize features spatially and interactively

JackStrawPlot()

JackStraw Plot

LabelClusters()

Label clusters on a ggplot2-based scatter plot

LabelPoints()

Add text labels to a ggplot2 plot

LinkedDimPlot() LinkedFeaturePlot()

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

NNPlot()

Highlight Neighbors in DimPlot

PlotClusterTree()

Plot clusters as a tree

PolyDimPlot()

Polygon DimPlot

PolyFeaturePlot()

Polygon FeaturePlot

RidgePlot()

Single cell ridge plot

SeuratTheme() CenterTitle() DarkTheme() FontSize() NoAxes() NoLegend() NoGrid() SeuratAxes() SpatialTheme() RestoreLegend() RotatedAxis() BoldTitle() WhiteBackground()

Seurat Themes

SpatialPlot() SpatialDimPlot() SpatialFeaturePlot()

Visualize spatial clustering and expression data.

VariableFeaturePlot()

View variable features

VizDimLoadings()

Visualize Dimensional Reduction genes

VlnPlot()

Single cell violin plot

Intensity() Luminance()

Get the intensity and/or luminance of a color

Function related to tree-based analysis of identity classes

BuildClusterTree()

Phylogenetic Analysis of Identity Classes

Utility functions

Useful functions to help with a variety of tasks

AddModuleScore()

Calculate module scores for feature expression programs in single cells

AggregateExpression()

Aggregated feature expression by identity class

AverageExpression()

Averaged feature expression by identity class

CaseMatch()

Match the case of character vectors

CellCycleScoring()

Score cell cycle phases

CollapseSpeciesExpressionMatrix()

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

CustomDistance()

Run a custom distance function on an input data matrix

ExpMean()

Calculate the mean of logged values

ExpSD()

Calculate the standard deviation of logged values

ExpVar()

Calculate the variance of logged values

FastRowScale()

Scale and/or center matrix rowwise

GroupCorrelation()

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

LoadAnnoyIndex()

Load the Annoy index file

LogVMR()

Calculate the variance to mean ratio of logged values

MetaFeature()

Aggregate expression of multiple features into a single feature

MinMax()

Apply a ceiling and floor to all values in a matrix

PercentageFeatureSet()

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

RegroupIdents()

Regroup idents based on meta.data info

SaveAnnoyIndex()

Save the Annoy index

GeneSymbolThesarus() UpdateSymbolList()

Get updated synonyms for gene symbols

as.sparse(<H5Group>) as.data.frame(<Matrix>)

Cast to Sparse

Data

Descriptions of data included with Seurat

cc.genes

Cell cycle genes

cc.genes.updated.2019

Cell cycle genes: 2019 update

Convenience functions

Functions included for user convenience and to keep maintain backwards compatability

DimHeatmap() PCHeatmap()

Dimensional reduction heatmap

DimPlot() PCAPlot() TSNEPlot() UMAPPlot()

Dimensional reduction plot

ReadParseBio()

Read output from Parse Biosciences

ReadSTARsolo()

Read output from STARsolo

SpatialPlot() SpatialDimPlot() SpatialFeaturePlot()

Visualize spatial clustering and expression data.