Object interactionFunctions for interacting with a Seurat object | |
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The AnchorSet Class | |
| Get Cell Names |
Get a vector of cell names associated with an image (or set of images) | |
Slim down a Seurat object | |
Filter stray beads from Slide-seq puck | |
Get an Assay object from a given Seurat object. | |
| Get Image Data |
Get integration data | |
| Get Tissue Coordinates |
The IntegrationAnchorSet Class | |
The IntegrationData Class | |
The ModalityWeights Class | |
Get Spot Radius | |
Get image scale factors | |
Set integration data | |
Splits object into a list of subsetted objects. | |
Find cells with highest scores for a given dimensional reduction technique | |
Find features with highest scores for a given dimensional reduction technique | |
Get nearest neighbors for given cell | |
The TransferAnchorSet Class | |
The VisiumV1 class | |
Convert objects to CellDataSet objects | |
Convert objects to | |
Convert objects to SingleCellExperiment objects | |
Cast to Sparse | |
PreprocessingFunctions for preprocessing single-cell data | |
Calculate the Barcode Distribution Inflection | |
Find spatially variable features | |
Find variable features | |
Calculate pearson residuals of features not in the scale.data | |
Demultiplex samples based on data from cell 'hashing' | |
Load a 10x Genomics Visium Spatial Experiment into a | |
Load STARmap data | |
Normalize raw data | |
Demultiplex samples based on classification method from MULTI-seq (McGinnis et al., bioRxiv 2018) | |
Normalize Data | |
Load in data from 10X | |
Load a 10X Genomics Visium Image | |
Read 10X hdf5 file | |
Load Slide-seq spatial data | |
Normalize raw data to fractions | |
Run the mark variogram computation on a given position matrix and expression matrix. | |
Compute Moran's I value. | |
Use regularized negative binomial regression to normalize UMI count data | |
Sample UMI | |
Scale and center the data. | |
Subset a Seurat Object based on the Barcode Distribution Inflection Points | |
Differential expressionFunctions for testing differential gene (feature) expression | |
Gene expression markers for all identity classes | |
Finds markers that are conserved between the groups | |
Gene expression markers of identity classes | |
Fold Change | |
Dimensional ReductionFunctions to reduce the dimensionality of datasets | |
Determine statistical significance of PCA scores. | |
L2-Normalize CCA | |
L2-normalization | |
Significant genes from a PCA | |
Project Dimensional reduction onto full dataset | |
Project query into UMAP coordinates of a reference | |
Perform Canonical Correlation Analysis | |
Run Independent Component Analysis on gene expression | |
Run Principal Component Analysis | |
Run t-distributed Stochastic Neighbor Embedding | |
Run UMAP | |
Compute Jackstraw scores significance. | |
ClusteringFunctions to cluster single-cell data | |
Cluster Determination | |
Construct weighted nearest neighbor graph | |
(Shared) Nearest-neighbor graph construction | |
Find subclusters under one cluster | |
IntegrationFunctions related to the Seurat v3 integration and label transfer algorithms | |
Find integration anchors | |
Find transfer anchors | |
Get the predicted identity | |
Integrate data | |
Integrate low dimensional embeddings | |
Calculate the local structure preservation metric | |
Map query cells to a reference | |
Metric for evaluating mapping success | |
Calculates a mixing metric | |
Predict value from nearest neighbors | |
Prepare an object list normalized with sctransform for integration. | |
Select integration features | |
Transfer data | |
MixscapeFunctions related to the mixscape algorithm | |
Calculate a perturbation Signature | |
DE and EnrichR pathway visualization barplot | |
Differential expression heatmap for mixscape | |
Linear discriminant analysis on pooled CRISPR screen data. | |
Function to plot perturbation score distributions. | |
Function to prepare data for Linear Discriminant Analysis. | |
Run Linear Discriminant Analysis | |
Run Mixscape | |
VisualizationFunctions for plotting data and adjusting | |
Augments ggplot2-based plot with a PNG image. | |
Determine text color based on background color | |
Plot the Barcode Distribution and Calculated Inflection Points | |
Cell-cell scatter plot | |
Cell Selector | |
Move outliers towards center on dimension reduction plot | |
Color dimensional reduction plot by tree split | |
Combine ggplot2-based plots into a single plot | |
| Create a custom color palette |
Dimensional reduction heatmap | |
Dimensional reduction plot | |
Discrete colour palettes from the pals package | |
Feature expression heatmap | |
Dot plot visualization | |
Quickly Pick Relevant Dimensions | |
Visualize 'features' on a dimensional reduction plot | |
Scatter plot of single cell data | |
Boxplot of correlation of a variable (e.g. number of UMIs) with expression data | |
Hashtag oligo heatmap | |
Hover Locator | |
Visualize features in dimensional reduction space interactively | |
Visualize clusters spatially and interactively | |
Visualize features spatially and interactively | |
JackStraw Plot | |
Label clusters on a ggplot2-based scatter plot | |
Add text labels to a ggplot2 plot | |
Visualize spatial and clustering (dimensional reduction) data in a linked, interactive framework | |
Highlight Neighbors in DimPlot | |
Plot clusters as a tree | |
Polygon DimPlot | |
Polygon FeaturePlot | |
Single cell ridge plot | |
| Seurat Themes |
Visualize spatial clustering and expression data. | |
View variable features | |
Visualize Dimensional Reduction genes | |
Single cell violin plot | |
Get the intensity and/or luminance of a color | |
Tree-related functionsFunction related to tree-based analysis of identity classes | |
Phylogenetic Analysis of Identity Classes | |
Utility functionsUseful functions to help with a variety of tasks | |
Calculate module scores for feature expression programs in single cells | |
Aggregated feature expression by identity class | |
Averaged feature expression by identity class | |
Match the case of character vectors | |
Score cell cycle phases | |
Slim down a multi-species expression matrix, when only one species is primarily of interenst. | |
Run a custom distance function on an input data matrix | |
Calculate the mean of logged values | |
Calculate the standard deviation of logged values | |
Calculate the variance of logged values | |
Scale and/or center matrix rowwise | |
Compute the correlation of features broken down by groups with another covariate | |
Load the Annoy index file | |
Calculate the variance to mean ratio of logged values | |
Aggregate expression of multiple features into a single feature | |
Apply a ceiling and floor to all values in a matrix | |
Calculate the percentage of all counts that belong to a given set of features | |
Regroup idents based on meta.data info | |
Save the Annoy index | |
Get updated synonyms for gene symbols | |
Cast to Sparse | |
DataDescriptions of data included with Seurat | |
Cell cycle genes | |
Cell cycle genes: 2019 update | |
Convenience functionsFunctions included for user convenience and to keep maintain backwards compatability | |
Dimensional reduction heatmap | |
Dimensional reduction plot | |
Visualize spatial clustering and expression data. |