Interactive Analysis of Single Cell RNA-Seq Data

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Documentation for package ‘singleCellTK’ version 1.7.0

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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