Seurat: Tools for Single Cell Genomics | Seurat-package Seurat |
Add Azimuth Results | AddAzimuthResults |
Add Azimuth Scores | AddAzimuthScores |
Calculate module scores for feature expression programs in single cells | AddModuleScore |
Aggregated feature expression by identity class | AggregateExpression |
The AnchorSet Class | AnchorSet AnchorSet-class |
Add info to anchor matrix | AnnotateAnchors AnnotateAnchors.default AnnotateAnchors.IntegrationAnchorSet AnnotateAnchors.TransferAnchorSet |
Convert objects to CellDataSet objects | as.CellDataSet as.CellDataSet.Seurat |
Convert objects to 'Seurat' objects | as.Seurat.CellDataSet as.Seurat.SingleCellExperiment |
Convert objects to SingleCellExperiment objects | as.SingleCellExperiment as.SingleCellExperiment.Seurat |
Cast to Sparse | as.data.frame.Matrix as.sparse.H5Group |
The Assay Class | Assay-class |
Augments ggplot2-based plot with a PNG image. | AugmentPlot |
Automagically calculate a point size for ggplot2-based scatter plots | AutoPointSize |
Averaged feature expression by identity class | AverageExpression |
Plot the Barcode Distribution and Calculated Inflection Points | BarcodeInflectionsPlot |
Determine text color based on background color | BGTextColor |
Create a custom color palette | BlackAndWhite BlueAndRed CustomPalette PurpleAndYellow |
Phylogenetic Analysis of Identity Classes | BuildClusterTree |
Calculate a perturbation Signature | CalcPerturbSig |
Calculate the Barcode Distribution Inflection | CalculateBarcodeInflections |
Match the case of character vectors | CaseMatch |
Cell cycle genes | cc.genes |
Cell cycle genes: 2019 update | cc.genes.updated.2019 |
Score cell cycle phases | CellCycleScoring |
Get Cell Names | Cells.SCTModel Cells.SlideSeq Cells.STARmap Cells.VisiumV1 |
Get a vector of cell names associated with an image (or set of images) | CellsByImage |
Cell-cell scatter plot | CellPlot CellScatter |
Cell Selector | CellSelector FeatureLocator |
Move outliers towards center on dimension reduction plot | CollapseEmbeddingOutliers |
Slim down a multi-species expression matrix, when only one species is primarily of interenst. | CollapseSpeciesExpressionMatrix |
Color dimensional reduction plot by tree split | ColorDimSplit |
Combine ggplot2-based plots into a single plot | CombinePlots |
Get the intensity and/or luminance of a color | contrast-theory Intensity Luminance |
Create a SCT Assay object | CreateSCTAssayObject |
Run a custom distance function on an input data matrix | CustomDistance |
DE and EnrichR pathway visualization barplot | DEenrichRPlot |
Slim down a Seurat object | DietSeurat |
Dimensional reduction heatmap | DimHeatmap PCHeatmap |
Dimensional reduction plot | DimPlot ICAPlot PCAPlot TSNEPlot UMAPPlot |
The DimReduc Class | DimReduc-class |
Discrete colour palettes from pals | DiscretePalette |
Feature expression heatmap | DoHeatmap |
Dot plot visualization | DotPlot SplitDotPlotGG |
Quickly Pick Relevant Dimensions | ElbowPlot |
Calculate the mean of logged values | ExpMean |
Calculate the standard deviation of logged values | ExpSD |
Calculate the variance of logged values | ExpVar |
Scale and/or center matrix rowwise | FastRowScale |
Visualize 'features' on a dimensional reduction plot | FeatureHeatmap FeaturePlot |
Scatter plot of single cell data | FeatureScatter GenePlot |
Filter stray beads from Slide-seq puck | FilterSlideSeq |
Gene expression markers for all identity classes | FindAllMarkers FindAllMarkersNode |
Cluster Determination | FindClusters FindClusters.default FindClusters.Seurat |
Finds markers that are conserved between the groups | FindConservedMarkers |
Find integration anchors | FindIntegrationAnchors |
Gene expression markers of identity classes | FindMarkers FindMarkers.Assay FindMarkers.default FindMarkers.DimReduc FindMarkers.SCTAssay FindMarkers.Seurat FindMarkersNode |
Construct weighted nearest neighbor graph | FindMultiModalNeighbors |
(Shared) Nearest-neighbor graph construction | FindNeighbors FindNeighbors.Assay FindNeighbors.default FindNeighbors.dist FindNeighbors.Seurat |
Find spatially variable features | FindSpatiallyVariableFeatures FindSpatiallyVariableFeatures.Assay FindSpatiallyVariableFeatures.default FindSpatiallyVariableFeatures.Seurat |
Find subclusters under one cluster | FindSubCluster |
Find transfer anchors | FindTransferAnchors |
Find variable features | FindVariableFeatures FindVariableFeatures.Assay FindVariableFeatures.default FindVariableFeatures.SCTAssay FindVariableFeatures.Seurat FindVariableGenes |
Fold Change | FoldChange FoldChange.Assay FoldChange.default FoldChange.DimReduc FoldChange.SCTAssay FoldChange.Seurat |
Get an Assay object from a given Seurat object. | GetAssay GetAssay.Seurat |
Get Image Data | GetImage.SlideSeq GetImage.STARmap GetImage.VisiumV1 |
Get integration data | GetIntegrationData |
Calculate pearson residuals of features not in the scale.data | GetResidual |
Get Tissue Coordinates | GetTissueCoordinates.SlideSeq GetTissueCoordinates.STARmap GetTissueCoordinates.VisiumV1 |
Get the predicted identity | GetTransferPredictions |
The Graph Class | Graph-class |
Compute the correlation of features broken down by groups with another covariate | GroupCorrelation |
Boxplot of correlation of a variable (e.g. number of UMIs) with expression data | GroupCorrelationPlot |
Hover Locator | HoverLocator |
Demultiplex samples based on data from cell 'hashing' | HTODemux |
Hashtag oligo heatmap | HTOHeatmap |
Get Variable Feature Information | HVFInfo.SCTAssay |
Visualize features in dimensional reduction space interactively | IFeaturePlot |
Spatial Cluster Plots | ImageDimPlot |
Spatial Feature Plots | ImageFeaturePlot |
Integrate data | IntegrateData |
Integrate low dimensional embeddings | IntegrateEmbeddings IntegrateEmbeddings.IntegrationAnchorSet IntegrateEmbeddings.TransferAnchorSet |
The IntegrationAnchorSet Class | IntegrationAnchorSet IntegrationAnchorSet-class |
The IntegrationData Class | IntegrationData IntegrationData-class |
Visualize clusters spatially and interactively | ISpatialDimPlot |
Visualize features spatially and interactively | ISpatialFeaturePlot |
Determine statistical significance of PCA scores. | JackStraw |
The JackStrawData Class | JackStrawData-class |
JackStraw Plot | JackStrawPlot |
L2-Normalize CCA | L2CCA |
L2-normalization | L2Dim |
Label clusters on a ggplot2-based scatter plot | LabelClusters |
Add text labels to a ggplot2 plot | Labeler LabelPoints |
Visualize spatial and clustering (dimensional reduction) data in a linked, interactive framework | LinkedDimPlot LinkedFeaturePlot LinkedPlot LinkedPlots |
Load a 10x Genomics Visium Spatial Experiment into a 'Seurat' object | Load10X_Spatial |
Load the Annoy index file | LoadAnnoyIndex |
Load Curio Seeker data | LoadCurioSeeker |
Load STARmap data | LoadSTARmap |
Read and Load 10x Genomics Xenium in-situ data | LoadXenium ReadXenium |
Calculate the local structure preservation metric | LocalStruct |
Normalize raw data | LogNormalize |
Calculate the variance to mean ratio of logged values | LogVMR |
Metric for evaluating mapping success | MappingScore MappingScore.AnchorSet MappingScore.default |
Map query cells to a reference | MapQuery |
Merge SCTAssay objects | merge.SCTAssay |
Aggregate expression of multiple features into a single feature | MetaFeature |
Apply a ceiling and floor to all values in a matrix | MinMax |
Calculates a mixing metric | MixingMetric |
Differential expression heatmap for mixscape | MixscapeHeatmap |
Linear discriminant analysis on pooled CRISPR screen data. | MixscapeLDA |
The ModalityWeights Class | ModalityWeights ModalityWeights-class |
Demultiplex samples based on classification method from MULTI-seq (McGinnis et al., bioRxiv 2018) | MULTIseqDemux |
The Neighbor Class | Neighbor-class |
Highlight Neighbors in DimPlot | NNPlot |
Normalize Data | NormalizeData NormalizeData.Assay NormalizeData.default NormalizeData.Seurat |
Significant genes from a PCA | PCASigGenes |
Calculate the percentage of a vector above some threshold | PercentAbove |
Calculate the percentage of all counts that belong to a given set of features | PercentageFeatureSet |
Plot clusters as a tree | PlotClusterTree |
Function to plot perturbation score distributions. | PlotPerturbScore |
Polygon DimPlot | PolyDimPlot |
Polygon FeaturePlot | PolyFeaturePlot |
Predict value from nearest neighbors | PredictAssay |
Function to prepare data for Linear Discriminant Analysis. | PrepLDA |
Prepare object to run differential expression on SCT assay with multiple models | PrepSCTFindMarkers |
Prepare an object list normalized with sctransform for integration. | PrepSCTIntegration |
Project Dimensional reduction onto full dataset | ProjectDim |
Project query into UMAP coordinates of a reference | ProjectUMAP ProjectUMAP.default ProjectUMAP.DimReduc ProjectUMAP.Seurat |
Get Spot Radius | Radius.SlideSeq Radius.STARmap Radius.VisiumV1 |
Load in data from 10X | Read10X |
Read 10X hdf5 file | Read10X_h5 |
Load a 10X Genomics Visium Image | Read10X_Image |
Read10x Probe Metadata | Read10X_probe_metadata |
Read and Load Akoya CODEX data | LoadAkoya ReadAkoya |
Load in data from remote or local mtx files | ReadMtx |
Read and Load Nanostring SMI data | LoadNanostring ReadNanostring |
Read output from Parse Biosciences | ReadParseBio |
Load Slide-seq spatial data | ReadSlideSeq |
Read output from STARsolo | ReadSTARsolo |
Read Data From Vitessce | LoadHuBMAPCODEX ReadVitessce |
Read and Load MERFISH Input from Vizgen | LoadVizgen ReadVizgen |
Regroup idents based on meta.data info | RegroupIdents |
Normalize raw data to fractions | RelativeCounts |
Rename Cells in an Object | RenameCells.SCTAssay RenameCells.SlideSeq RenameCells.STARmap RenameCells.VisiumV1 |
Single cell ridge plot | RidgePlot |
Perform Canonical Correlation Analysis | RunCCA RunCCA.default RunCCA.Seurat |
Run Independent Component Analysis on gene expression | RunICA RunICA.Assay RunICA.default RunICA.Seurat |
Run Linear Discriminant Analysis | RunLDA RunLDA.Assay RunLDA.default RunLDA.Seurat |
Run the mark variogram computation on a given position matrix and expression matrix. | RunMarkVario |
Run Mixscape | RunMixscape |
Compute Moran's I value. | RunMoransI |
Run Principal Component Analysis | RunPCA RunPCA.Assay RunPCA.default RunPCA.Seurat |
Run Supervised Latent Semantic Indexing | RunSLSI RunSLSI.Assay RunSLSI.default RunSLSI.Seurat |
Run Supervised Principal Component Analysis | RunSPCA RunSPCA.Assay RunSPCA.default RunSPCA.Seurat |
Run t-distributed Stochastic Neighbor Embedding | RunTSNE RunTSNE.DimReduc RunTSNE.dist RunTSNE.matrix RunTSNE.Seurat |
Run UMAP | RunUMAP RunUMAP.default RunUMAP.Graph RunUMAP.Neighbor RunUMAP.Seurat |
Sample UMI | SampleUMI |
Save the Annoy index | SaveAnnoyIndex |
Scale and center the data. | ScaleData ScaleData.Assay ScaleData.default ScaleData.Seurat |
Get image scale factors | ScaleFactors scalefactors ScaleFactors.VisiumV1 |
Compute Jackstraw scores significance. | ScoreJackStraw ScoreJackStraw.DimReduc ScoreJackStraw.JackStrawData ScoreJackStraw.Seurat |
The SCTModel Class | levels.SCTAssay levels<-.SCTAssay SCTAssay SCTAssay-class SCTModel |
Use regularized negative binomial regression to normalize UMI count data | SCTransform |
Get SCT results from an Assay | SCTResults SCTResults.SCTAssay SCTResults.SCTModel SCTResults.Seurat SCTResults<- SCTResults<-.SCTAssay SCTResults<-.SCTModel |
Select integration features | SelectIntegrationFeatures |
Set integration data | SetIntegrationData |
Find the Quantile of Data | SetQuantile |
The Seurat Class | Seurat-class |
The SeuratCommand Class | SeuratCommand-class |
Seurat Themes | BoldTitle CenterTitle DarkTheme FontSize NoAxes NoGrid NoLegend RestoreLegend RotatedAxis SeuratAxes SeuratTheme SpatialTheme WhiteBackground |
The SlideSeq class | SlideSeq SlideSeq-class |
The SpatialImage Class | SpatialImage-class |
Visualize spatial clustering and expression data. | SpatialDimPlot SpatialFeaturePlot SpatialPlot |
Splits object into a list of subsetted objects. | SplitObject |
The STARmap class | STARmap STARmap-class |
Subset an AnchorSet object | subset.AnchorSet |
Subset a Seurat Object based on the Barcode Distribution Inflection Points | SubsetByBarcodeInflections |
Find cells with highest scores for a given dimensional reduction technique | TopCells |
Find features with highest scores for a given dimensional reduction technique | TopFeatures |
Get nearest neighbors for given cell | TopNeighbors |
The TransferAnchorSet Class | TransferAnchorSet TransferAnchorSet-class |
Transfer data | TransferData |
Update pre-V4 Assays generated with SCTransform in the Seurat to the new SCTAssay class | UpdateSCTAssays |
Get updated synonyms for gene symbols | GeneSymbolThesarus UpdateSymbolList |
View variable features | MeanVarPlot VariableFeaturePlot VariableGenePlot |
The VisiumV1 class | VisiumV1 VisiumV1-class |
Visualize Dimensional Reduction genes | VizDimLoadings |
Single cell violin plot | VlnPlot |