Classify New Data
Likelihood ratio test for zero-inflated data
Color tSNE Plot Based on Split
Calculate the standard deviation of logged values
Normalize raw data
CollapseSpeciesExpressionMatrix
Slim down a multi-species expression matrix, when only one species is primarily of interenst.
Calculate the variance of logged values
Run a custom distance function on an input data matrix
Gene expression markers of identity classes
Dimensional reduction heatmap
Determine statistical significance of PCA scores.
Finds markers that are conserved between the two groups
Dimensional reduction plot
Print AlignSubspace Calculation Parameters
Initialize and setup the Seurat object
Find cells with highest scores for a given dimensional reduction technique
Quickly Pick Relevant Dimensions
Calculate the mean of logged values
ICA Gene Loadings Accessor Function
Old Dot plot visualization (pre-ggplot implementation)
Intuitive way of visualizing how gene expression changes across different identity classes (clusters).
The size of the dot encodes the percentage of cells within a class, while the color encodes the
AverageExpression level of 'expressing' cells (green is high).
Return a subset of the Seurat object
Find all markers for a node
A black and white color palette
Get cell centroids
Vizualization of multiple features
Find cells with highest ICA scores
K-Means Clustering
Independent component heatmap
Differential expression testing using Student's t-test
Dimensional Reduction Cell Embeddings Accessor Function
Convert Seurat objects to other classes and vice versa
Run Principal Component Analysis on gene expression using IRLBA
Find genes with highest scores for a given dimensional reduction technique
Dimensional Reduction Gene Loadings Accessor Function
Phylogenetic Analysis of Identity Classes
Gene expression heatmap
Sets identity class information to be a combination of two object attributes
Create a custom color palette
Poisson test for UMI-count based data
Calculate the variance to mean ratio of logged values
GenesInCluster
Perform spectral density clustering on single cells
Accessor function for multimodal data
Build mixture models of gene expression
Cluster Determination
Differential expression using DESeq2
ROC-based marker discovery
Splits object into a list of subsetted objects.
Gene expression markers for all identity classes
Plot Diffusion map
Make object sparse
Project Dimensional reduction onto full dataset
Gene expression heatmap
Perform Canonical Correlation Analysis with more than two groups
Demultiplex samples based on data from cell 'hashing'
PCA Gene Loadings Accessor Function
Gene expression markers of identity classes defined by a phylogenetic clade
Differential expression using MAST
Identify variable genes
PCA Cell Embeddings Accessor Function
JackStraw Plot
Access cellular data
Dark Theme
Extract delimiter information from a string.
PrintCalcVarExpRatioParams
Print Parameters Associated with CalcVarExpRatio
Apply a ceiling and floor to all values in a matrix
Plot ICA map
FastWhichCells
Identify cells matching certain criteria (limited to character values)
Significant genes from a PCA
Differential expression testing using Tobit models
Dimensional Reduction Accessor Function
Principal component heatmap
Diffusion Maps Cell Embeddings Accessor Function
Set Cluster Assignments
Merge Seurat Objects
Print Diffusion Map Calculation Parameters
Infer spatial origins for single cells
Get Cluster Assignments
Visualize 'features' on a dimensional reduction plot
Independently shuffle values within each row of a matrix
Transfer identity class information (or meta data) from one object to another
Hover Locator
Merge childen of a node
Plot CC bicor saturation plot
Run t-distributed Stochastic Neighbor Embedding
Dot plot visualization
Normalize Assay Data
Reorder identity classes
ICA Cell Embeddings Accessor Function
Set identity class information
Convert the cluster labels to a numeric representation
Print the results of a dimensional reduction analysis
Plot PCA map
Find cells with highest PCA scores
Print FindClusters Calculation Parameters
Switch identity class definition to another variable
Scale and center the data.
Quickly Pick Relevant PCs
Quantitative refinement of spatial inferences
Specific Cluster Validation
Feature Locator
Find genes with highest PCA scores
Return a subset of the Seurat object
Dimensional Reduction Mutator Function
Rename one identity class to another
Print the results of a ICA analysis
Print ICA Calculation Parameters
Save cluster assignments to a TSV file
Run Independent Component Analysis on gene expression
Find genes with highest ICA scores
Run diffusion map
Visualize Dimensional Reduction genes
Deprecated function(s) in the Seurat package
Scatter plot of single cell data
Project Principal Components Analysis onto full dataset
View variable genes
Sample UMI
Print SNN Construction Calculation Parameters
Cluster Validation
Remove data from a table
Load in data from 10X
Print CCA Calculation Parameters
The Seurat Class
Set identity class information
Single cell violin plot
Split Dot plot visualization
Perform spectral k-means clustering on single cells
A small example version of the PBMC dataset
Print the calculation
Print TSNE Calculation Parameters
Shuffle a vector
Return a subset of rows for a matrix or data frame
Identify cells matching certain criteria
show method for seurat
Plot tSNE map
Run UMAP
Assay Data Mutator Function
Update old Seurat object to accomodate new features
Differential expression using Wilcoxon Rank Sum
Plot k-means clusters
Negative binomial test for UMI-count based data
Cell cycle genes
Print the results of a PCA analysis
Negative binomial test for UMI-count based data (regularized version)
Plot phylogenetic tree
Print PCA Calculation Parameters
A purple and yellow color palette
Single cell ridge plot
Return a subset of the Seurat object.
Return a subset of columns for a matrix or data frame
Perform Canonical Correlation Analysis
Old R based implementation of ScaleData. Scales and centers the data
Visualize PCA genes
Visualize ICA genes
Calculate smoothed expression values
Assess Internal Nodes
Add Metadata
Probability of detection by identity class
Calculate imputed expression values
Augments ggplot2 scatterplot with a PNG image.
Add samples into existing Seurat object.
Calculate module scores for gene expression programs in single cells
Average PCA scores by identity class
Align subspaces using dynamic time warping (DTW)
Assess Cluster Split
Averaged gene expression by identity class
Calculate an alignment score
Match the case of character vectors
Build Random Forest Classifier
SNN Graph Construction
Calculate the ratio of variance explained by ICA or PCA to CCA
Cell-cell scatter plot
Score cell cycle phases
Zebrafish analysis functions