Man pages for nukappa/seurat_v2
Seurat : R toolkit for single cell genomics

AddImputedScore	Calculate imputed expression values
AddMetaData	Add Metadata
AddSamples	Add samples into existing Seurat object.
AddSmoothedScore	Calculate smoothed expression values
AssessNodes	Assess Internal Nodes
AssessSplit	Assess Cluster Split
AverageExpression	Averaged gene expression by identity class
AveragePCA	Average PCA scores by identity class
BatchGene	Identify potential genes associated with batch effects
BuildClusterTree	Phylogenetic Analysis of Identity Classes
BuildRFClassifier	Build Random Forest Classifier
BuildSNN	SNN Graph Construction
CellPlot	Cell-cell scatter plot
ClassifyCells	Classify New Data
ClusterAlpha	Probability of detection by identity class
ColorTSNESplit	Color tSNE Plot Based on Split
DBClustDimension	Perform spectral density clustering on single cells
DiffExpTest	Likelihood ratio test for zero-inflated data
DiffTTest	Differential expression testing using Student's t-test
DimPlot	Dimensional reduction plot
DoHeatmap	Gene expression heatmap
DoKMeans	K-Means Clustering
DotPlot	Dot plot visualization
FeatureHeatmap	Vizualization of multiple features
FeaturePlot	Visualize 'features' on a dimensional reduction plot
FetchData	Access cellular data
FindAllMarkers	Gene expression markers for all identity classes
FindAllMarkersNode	Find all markers for a node
FindClusters	Cluster Determination
FindMarkers	Gene expression markers of identity classes
FindMarkersNode	Gene expression markers of identity classes defined by a...
FitGeneK	Build mixture models of gene expression
GenePlot	Scatter plot of single cell data
GetCentroids	Get cell centroids
HeatmapNode	Node Heatmap
ICA	Run Independent Component Analysis on gene expression
ICAPlot	Plot ICA map
ICHeatmap	Independent component heatmap
ICTopGenes	Find genes with highest ICA scores
InitialMapping	Infer spatial origins for single cells
JackStraw	Determine statistical significance of PCA scores.
JackStrawPlot	JackStraw Plot
KClustDimension	Perform spectral k-means clustering on single cells
LogNormalize	Normalize raw data
MakeSparse	Make object sparse
MarkerTest	ROC-based marker discovery
MeanVarPlot	Identify variable genes
MergeNode	Merge subchilden of a node
MergeSeurat	Merge Seurat Objects
NegBinomDETest	Negative binomial test for UMI-count based data
PCA	Run Principal Component Analysis on gene expression
PCAFast	Run Principal Component Analysis on gene expression using...
PCAPlot	Plot PCA map
PCASigGenes	Significant genes from a PCA
PCElbowPlot	Quickly Pick Relevant PCs
PCHeatmap	Principal component heatmap
PCTopCells	Find cells with highest PCA scores
PCTopGenes	Find genes with highest PCA scores
PlotClusterTree	Plot phylogenetic tree
PlotNoiseModel	Visualize expression/dropout curve
PoissonDETest	Poisson test for UMI-count based data
PrintPCA	Print the results of a PCA analysis
ProjectPCA	Project Principal Components Analysis onto full dataset
Read10X	Load in data from 10X
RefinedMapping	Quantitative refinement of spatial inferences
RegressOut	Regress out technical effects and cell cycle
RenameIdent	Rename one identity class to another
ReorderIdent	Reorder identity classes
RunDiffusion	Run t-distributed Stochastic Neighbor Embedding
RunTSNE	Run t-distributed Stochastic Neighbor Embedding
SampleUMI	Sample UMI
ScaleData	Scale and center the data
SetAllIdent	Switch identity class definition to another variable
SetIdent	Set identity class information
Setup	Setup Seurat object
seurat	The Seurat Class
Seurat-deprecated	Deprecated function(s) in the Seurat package
StashIdent	Set identity class information
SubsetCells	Return a subset of the Seurat object
SubsetData	Return a subset of the Seurat object
TobitTest	Differential expression testing using Tobit models
TSNEPlot	Plot tSNE map
ValidateClusters	Cluster Validation
ValidateSpecificClusters	Specific Cluster Validation
VizClassification	Highlight classification results
VizICA	Visualize ICA genes
VizPCA	Visualize PCA genes
VlnPlot	Single cell violin plot
WhichCells	Identify cells matching certain criteria