Function reference • singleCellTK

Shiny App
`singleCellTK()`	Run the single cell analysis app
Data Summary and Filtering
`filterSCData()`	Filter Genes and Samples from a Single Cell Object
`summarizeTable()`	Summarize SCtkExperiment
`convertGeneIDs()`	Convert Gene IDs
Dimensionality Reduction and Clustering
`getPCA()`	Get and plot PCA components for a SCtkE object
`getTSNE()`	Run t-SNE dimensionality reduction method on the assay data.
`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
`plotBiomarker()`	Given a set of genes, return a ggplot of expression values.
`plotPCA()`	Plot PCA run data from its components.
`plotTSNE()`	Plot t-SNE plot on dimensionality reduction data run from t-SNE method.
Batch Correction
`plotBatchVariance()`	Plot the percent of the variation that is explained by batch and condition in the data
`ComBatSCE()`	ComBatSCE
Differential Expression
`scDiffEx()` `scDiffExDESeq2()` `scDiffExlimma()` `scDiffExANOVA()`	Perform differential expression analysis on a SCtkExperiment object
`plotDiffEx()`	Plot Differential Expression
`MAST()` `thresholdGenes()` `MASTviolin()` `MASTregression()`	MAST
Pathway Activity Analysis
`gsvaSCE()` `gsvaPlot()`	Run GSVA analysis on a SCtkExperiment object.
Sample Size
`calcEffectSizes()`	Finds the effect sizes for all genes in the original dataset, regardless of significance.
`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
`generateSimulatedData()`	Generates a single simulated dataset, bootstrapping from the input counts matrix.
`iterateSimulations()`	Returns significance data from a snapshot.
`subDiffEx()` `subDiffExttest()` `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.
Data
`mouseBrainSubsetSCE`	Example Single Cell RNA-Seq data in SCtkExperiment Object, GSE60361 subset
SCtkExperiment
`createSCE()`	Create a SCtkExperiment object
`SCtkExperiment-class`	A lightweight S4 extension to the SingleCellExperiment class to store additional information.
`SCtkExperiment()`	Create a SCtkExperiment
`pcaVariances<-`()	Set PCA variances
`pcaVariances()` `pcaVariances<-`(<SCtkExperiment>)	Get PCA variances
Alignment
`alignSingleCellData()`	Align Single Cell RNA-Seq Data and Create a SCtkExperiment Object
`parseRsubreadLogs()`	Parse Rsubread Logs for Mapping and Feature Count Statistics

Reference

Shiny App

Data Summary and Filtering

Dimensionality Reduction and Clustering

Batch Correction

Differential Expression

Pathway Activity Analysis

Sample Size

Data

SCtkExperiment

Alignment