R: Coralysis sensitive identification of imbalanced cell types and states in single-cell data via multi-level integration

# Coralysis sensitive identification of imbalanced cell types and states in single-cell data via multi-level integration

## Documentation for package ‘Coralysis’ version 1.2.0

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

AggregateDataByBatch | Aggregates feature expression by cell clusters, per batch if provided.
AggregateDataByBatch-method | Aggregates feature expression by cell clusters, per batch if provided.
AggregateDataByBatch.SingleCellExperiment | Aggregates feature expression by cell clusters, per batch if provided.
BinCellClusterProbability | Bin cell cluster probability
BinCellClusterProbability-method | Bin cell cluster probability
BinCellClusterProbability.SingleCellExperiment | Bin cell cluster probability
CellBinsFeatureCorrelation | Cell bins feature correlation
CellBinsFeatureCorrelation-method | Cell bins feature correlation
CellBinsFeatureCorrelation.SingleCellExperiment | Cell bins feature correlation
CellClusterProbabilityDistribution | Cell cluster probability distribution
CellClusterProbabilityDistribution-method | Cell cluster probability distribution
CellClusterProbabilityDistribution.SingleCellExperiment | Cell cluster probability distribution
FindAllClusterMarkers | Identification of feature markers for all clusters
FindAllClusterMarkers-method | Identification of feature markers for all clusters
FindAllClusterMarkers.SingleCellExperiment | Identification of feature markers for all clusters
FindClusterMarkers | Differential expression between cell clusters
FindClusterMarkers-method | Differential expression between cell clusters
FindClusterMarkers.SingleCellExperiment | Differential expression between cell clusters
GetCellClusterProbability | Get ICP cell cluster probability
GetCellClusterProbability-method | Get ICP cell cluster probability
GetCellClusterProbability.SingleCellExperiment | Get ICP cell cluster probability
GetFeatureCoefficients | Get feature coefficients
GetFeatureCoefficients-method | Get feature coefficients
GetFeatureCoefficients.SingleCellExperiment | Get feature coefficients
HeatmapFeatures | Heatmap visualization of the expression of features by clusters
HeatmapFeatures-method | Heatmap visualization of the expression of features by clusters
HeatmapFeatures.SingleCellExperiment | Heatmap visualization of the expression of features by clusters
MajorityVotingFeatures | Majority voting features by label
MajorityVotingFeatures-method | Majority voting features by label
MajorityVotingFeatures.SingleCellExperiment | Majority voting features by label
PCAElbowPlot | Elbow plot of the standard deviations of the principal components
PCAElbowPlot-method | Elbow plot of the standard deviations of the principal components
PCAElbowPlot.SingleCellExperiment | Elbow plot of the standard deviations of the principal components
PlotClusterTree | Plot cluster tree
PlotClusterTree-method | Plot cluster tree
PlotClusterTree.SingleCellExperiment | Plot cluster tree
PlotDimRed | Plot dimensional reduction categorical variables
PlotDimRed-method | Plot dimensional reduction categorical variables
PlotDimRed.SingleCellExperiment | Plot dimensional reduction categorical variables
PlotExpression | Plot dimensional reduction feature expression
PlotExpression-method | Plot dimensional reduction feature expression
PlotExpression.SingleCellExperiment | Plot dimensional reduction feature expression
PrepareData | Prepare 'SingleCellExperiment' object for analysis
PrepareData-method | Prepare 'SingleCellExperiment' object for analysis
PrepareData.SingleCellExperiment | Prepare 'SingleCellExperiment' object for analysis
ReferenceMapping | Reference mapping
ReferenceMapping-method | Reference mapping
ReferenceMapping.SingleCellExperiment | Reference mapping
RunParallelDivisiveICP | Multi-level integration
RunParallelDivisiveICP-method | Multi-level integration
RunParallelDivisiveICP.SingleCellExperiment | Multi-level integration
RunPCA | Principal Component Analysis
RunPCA-method | Principal Component Analysis
RunPCA.SingleCellExperiment | Principal Component Analysis
RunTSNE | Barnes-Hut implementation of t-Distributed Stochastic Neighbor Embedding (t-SNE)
RunTSNE-method | Barnes-Hut implementation of t-Distributed Stochastic Neighbor Embedding (t-SNE)
RunTSNE.SingleCellExperiment | Barnes-Hut implementation of t-Distributed Stochastic Neighbor Embedding (t-SNE)
RunUMAP | Uniform Manifold Approximation and Projection (UMAP)
RunUMAP-method | Uniform Manifold Approximation and Projection (UMAP)
RunUMAP.SingleCellExperiment | Uniform Manifold Approximation and Projection (UMAP)
SummariseCellClusterProbability | Summarise ICP cell cluster probability
SummariseCellClusterProbability-method | Summarise ICP cell cluster probability
SummariseCellClusterProbability.SingleCellExperiment | Summarise ICP cell cluster probability
TabulateCellBinsByGroup | Tabulate cell bins by group
TabulateCellBinsByGroup-method | Tabulate cell bins by group
TabulateCellBinsByGroup.SingleCellExperiment | Tabulate cell bins by group
VlnPlot | Visualization of feature expression using violin plots
VlnPlot-method | Visualization of feature expression using violin plots
VlnPlot.SingleCellExperiment | Visualization of feature expression using violin plots