# Interactive Analysis of Single Cell RNA-Seq Data

## Documentation for package ‘singleCellTK’ version 1.6.0

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

## Help Pages

alignSingleCellData | Align Single Cell RNA-Seq Data and Create a SCtkExperiment Object
calcEffectSizes | Finds the effect sizes for all genes in the original dataset, regardless of significance.
ComBatSCE | ComBatSCE
convertGeneIDs | Convert Gene IDs
createSCE | Create a SCtkExperiment object
distinctColors | Generate a distinct palette for coloring different clusters
DownsampleCells | Estimate numbers of detected genes, significantly differentially expressed genes, and median significant effect size
DownsampleDepth | Estimate numbers of detected genes, significantly differentially expressed genes, and median significant effect size
enrichRSCE | enrichR Given a list of genes this function runs the enrichR() to perform Gene enrichment
filterSCData | Filter Genes and Samples from a Single Cell Object
generateSimulatedData | Generates a single simulated dataset, bootstrapping from the input counts matrix.
getBiomarker | Given a list of genes and a SCtkExperiment object, return the binary or continuous expression of the genes.
getClusterInputData | Get data to use as input clustering algorithms
getPCA | Get and plot PCA components for a SCtkE object
getTSNE | Run t-SNE dimensionality reduction method on the assay data.
getUMAP | Uniform Manifold Approximation and Projection(UMAP) algorithm for dimension reduction.
gsvaPlot | Run GSVA analysis on a SCtkExperiment object.
gsvaSCE | Run GSVA analysis on a SCtkExperiment object.
iterateSimulations | Returns significance data from a snapshot.
MAST | MAST
MASTregression | MAST
MASTviolin | MAST
mouseBrainSubsetSCE | Example Single Cell RNA-Seq data in SCtkExperiment Object, GSE60361 subset
parseRsubreadLogs | Parse Rsubread Logs for Mapping and Feature Count Statistics
pcaVariances | Get PCA variances
pcaVariances-method | Get PCA variances
pcaVariances<- | Set PCA variances
pcaVariances<--method | Get PCA variances
plotBatchVariance | Plot the percent of the variation that is explained by batch and condition in the data
plotBiomarker | Given a set of genes, return a ggplot of expression values.
plotDiffEx | Plot Differential Expression
plotDimRed | Plot results either on already run results of reduced dimensions data.
plotPCA | Plot PCA run data from its components.
plotTSNE | Plot t-SNE plot on dimensionality reduction data run from t-SNE method.
plotUMAP | Plot UMAP results either on already run results or run first and then plot.
saveBiomarkerRes | saveBiomarkerRes Save biomarker gene information with a custom name when provided with diffex results.
saveDiffExResults | saveDiffExResults Save Differential Expression Results with a custom name.
scDiffEx | Perform differential expression analysis on a SCtkExperiment object
scDiffExANOVA | Perform differential expression analysis on a SCtkExperiment object
scDiffExDESeq2 | Perform differential expression analysis on a SCtkExperiment object
scDiffExlimma | Perform differential expression analysis on a SCtkExperiment object
SCtkExperiment | Create a SCtkExperiment
SCtkExperiment-class | A lightweight S4 extension to the SingleCellExperiment class to store additional information.
singleCellTK | Run the single cell analysis app
subDiffEx | Passes the output of generateSimulatedData() to differential expression tests, picking either t-tests or ANOVA for data with only two conditions or multiple conditions, respectively.
subDiffExANOVA | Passes the output of generateSimulatedData() to differential expression tests, picking either t-tests or ANOVA for data with only two conditions or multiple conditions, respectively.
subDiffExttest | Passes the output of generateSimulatedData() to differential expression tests, picking either t-tests or ANOVA for data with only two conditions or multiple conditions, respectively.
summarizeTable | Summarize SCtkExperiment
thresholdGenes | MAST
visPlot | visPlot