.addSeuratToMetaDataSCE
                        .addSeuratToMetaDataSCE Adds the input seurat
                        object to the metadata slot of the input sce
                        object (after removing the data matrices)
.checkDiffExpResultExists
                        Check if the specified MAST result in
                        SingleCellExperiment object is complete. But
                        does not garantee the biological correctness.
.computeSignificantPC   .computeSignificantPC Computes the significant
                        principal components from an input sce object
                        (must contain pca slot) using stdev
.extractSCEAnnotation   Extract columns from row/colData and transfer
                        to factors
.formatDEAList          Helper function for differential expression
                        analysis methods that accepts multiple ways of
                        conditional subsetting and returns stable index
                        format. Meanwhile it does all the input
                        checkings.
.getComponentNames      .getComponentNames Creates a list of PC/IC
                        components to populate the picker for PC/IC
                        heatmap generation
.ggBar                  Bar plot plotting tool.
.ggDensity              Density plot plotting tool.
.ggScatter              Plot results of reduced dimensions data.
.ggViolin               Violin plot plotting tool.
.sce2adata              Coverts SingleCellExperiment object from R to
                        anndata.AnnData object in Python
.seuratGetVariableFeatures
                        .seuratGetVariableFeatures Retrieves the
                        requested number of variable feature names
.seuratInvalidate       .seuratInvalidate Removes seurat data from the
                        input SingleCellExperiment object specified by
                        the task in the Seurat workflow.
.updateAssaySCE         .updateAssaySCE Update/Modify/Add an assay in
                        the provided SingleCellExperiment object from a
                        Seurat object
MitoGenes               List of mitochondrial genes of multiple
                        reference
SEG                     Stably Expressed Gene (SEG) list obect, with
                        SEG sets for human and mouse.
calcEffectSizes         Finds the effect sizes for all genes in the
                        original dataset, regardless of significance.
combineSCE              Combine a list of SingleCellExperiment objects
                        as one SingleCellExperiment object
computeHeatmap          computeHeatmap The computeHeatmap method
                        computes the heatmap visualization for a set of
                        features against a set of dimensionality
                        reduction components. This method uses the
                        heatmap computation algorithm code from
                        'Seurat' but plots the heatmap using
                        'ComplexHeatmap' and 'cowplot' libraries.
computeZScore           Compute Z-Score
constructSCE            Create SingleCellExperiment object from csv or
                        txt input
convertSCEToSeurat      convertSCEToSeurat Converts sce object to
                        seurat while retaining all assays and metadata
convertSeuratToSCE      convertSeuratToSCE Converts the input seurat
                        object to a sce object
dataAnnotationColor     Generate distinct colors for all categorical
                        col/rowData entries. Character columns will be
                        considered as well as all-integer columns. Any
                        column with all-distinct values will be
                        excluded.
dedupRowNames           Deduplicate the rownames of a matrix or
                        SingleCellExperiment object Adds '-1', '-2',
                        ... '-i' to multiple duplicated rownames, and
                        in place replace the unique rownames, store
                        unique rownames in 'rowData', or return the
                        unique rownames as character vecetor.
detectCellOutlier       Detecting outliers within the
                        SingleCellExperiment object.
diffAbundanceFET        Calculate Differential Abundance with FET
discreteColorPalette    Generate given number of color codes
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
expData                 expData Get data item from an input
                        'SingleCellExperiment' object. The data item
                        can be an 'assay', 'altExp' (subset) or a
                        'reducedDim', which is retrieved based on the
                        name of the data item.
expData,ANY,character-method
                        expData Get data item from an input
                        'SingleCellExperiment' object. The data item
                        can be an 'assay', 'altExp' (subset) or a
                        'reducedDim', which is retrieved based on the
                        name of the data item.
expData<-               expData Store data items using tags to identify
                        the type of data item stored. To be used as a
                        replacement for assay<- setter function but
                        with additional parameter to set a tag to a
                        data item.
expData<-,ANY,character,CharacterOrNullOrMissing,logical-method
                        expData Store data items using tags to identify
                        the type of data item stored. To be used as a
                        replacement for assay<- setter function but
                        with additional parameter to set a tag to a
                        data item.
expDataNames            expDataNames Get names of all the data items in
                        the input 'SingleCellExperiment' object
                        including assays, altExps and reducedDims.
expDataNames,ANY-method
                        expDataNames Get names of all the data items in
                        the input 'SingleCellExperiment' object
                        including assays, altExps and reducedDims.
expDeleteDataTag        expDeleteDataTag Remove tag against an input
                        data from the stored tag information in the
                        metadata of the input object.
expSetDataTag           expSetDataTag Set tag to an assay or a data
                        item in the input SCE object.
expTaggedData           expTaggedData Returns a list of names of data
                        items from the input 'SingleCellExperiment'
                        object based upon the input parameters.
exportSCE               Export data in SingleCellExperiment object
exportSCEToSeurat       Export data in Seurat object
exportSCEtoAnnData      Export a SingleCellExperiment R object as
                        Python annData object
exportSCEtoFlatFile     Export a SingleCellExperiment object to flat
                        text files
featureIndex            Retrieve row index for a set of features
findMarkerDiffExp       Find the marker gene set for each cluster With
                        an input SingleCellExperiment object and
                        specifying the clustering labels, this function
                        iteratively call the differential expression
                        analysis on each cluster against all the
                        others.
findMarkerTopTable      Fetch the table of top markers that pass the
                        filtering
generateHTANMeta        Generate HTAN manifest file for droplet and
                        cell count data
generateMeta            Generate HTAN manifest file for droplet and
                        cell count data
generateSimulatedData   Generates a single simulated dataset,
                        bootstrapping from the input counts matrix.
getBiomarker            Given a list of genes and a
                        SingleCellExperiment object, return the binary
                        or continuous expression of the genes.
getDEGTopTable          Get Top Table of a DEG analysis
getMSigDBTable          Shows MSigDB categories
getSceParams            Extract QC parameters from the
                        SingleCellExperiment object
getTSNE                 Run t-SNE dimensionality reduction method on a
                        SingleCellExperiment Object
getTopHVG               getTopHVG Extracts the top variable genes from
                        an input 'SingleCellExperiment' object. Note
                        that the variability metrics must be computed
                        using the 'runFeatureSelection' method before
                        extracting the feature names of the top
                        variable features. If 'altExp' parameter is a
                        'character' value, this function will return
                        the input 'SingleCellExperiment' object with
                        the subset containing only the top variable
                        features stored as an 'altExp' slot in returned
                        object. However, if this parameter is set to
                        'NULL', only the names of the top variable
                        features will be returned as a 'character'
                        vector.
getUMAP                 Uniform Manifold Approximation and
                        Projection(UMAP) algorithm for dimension
                        reduction.
importAlevin            Construct SCE object from Salmon-Alevin output
importAnnData           Create a SingleCellExperiment Object from
                        Python AnnData .h5ad files
importBUStools          Construct SCE object from BUStools output
importCellRanger        Construct SCE object from Cell Ranger output
importCellRangerV2Sample
                        Construct SCE object from Cell Ranger V2 output
                        for a single sample
importCellRangerV3Sample
                        Construct SCE object from Cell Ranger V3 output
                        for a single sample
importDropEst           Create a SingleCellExperiment Object from
                        DropEst output
importExampleData       Retrieve example datasets
importFromFiles         Create a SingleCellExperiment object from files
importGeneSetsFromCollection
                        Imports gene sets from a GeneSetCollection
                        object
importGeneSetsFromGMT   Imports gene sets from a GMT file
importGeneSetsFromList
                        Imports gene sets from a list
importGeneSetsFromMSigDB
                        Imports gene sets from MSigDB
importMitoGeneSet       Import mitochondrial gene sets
importMultipleSources   Imports samples from different sources and
                        compiles them into a list of SCE objects
importOptimus           Construct SCE object from Optimus output
importSEQC              Construct SCE object from seqc output
importSTARsolo          Construct SCE object from STARsolo outputs
iterateSimulations      Returns significance data from a snapshot.
mergeSCEColData         Merging colData from two singleCellExperiment
                        objects
mouseBrainSubsetSCE     Example Single Cell RNA-Seq data in
                        SingleCellExperiment Object, GSE60361 subset
msigdb_table            MSigDB gene get Cctegory table
plotBarcodeRankDropsResults
                        Plots for runEmptyDrops outputs.
plotBarcodeRankScatter
                        Plots for runBarcodeRankDrops outputs.
plotBatchCorrCompare    Plot comparison of batch corrected result
                        against original assay
plotBatchVariance       Plot the percent of the variation that is
                        explained by batch and condition in the data
plotBcdsResults         Plots for runBcds outputs.
plotClusterAbundance    Plot the differential Abundance
plotCxdsResults         Plots for runCxds outputs.
plotDEGHeatmap          Heatmap visualization of DEG result
plotDEGRegression       plot the linear regression to show visualize
                        the expression the of DEGs identified by
                        differential expression analysis
plotDEGViolin           plot the violin plot to show visualize the
                        expression distribution of DEGs identified by
                        differential expression analysis
plotDecontXResults      Plots for runDecontX outputs.
plotDimRed              Plot dimensionality reduction from computed
                        metrics including PCA, ICA, tSNE and UMAP
plotDoubletFinderResults
                        Plots for runDoubletFinder outputs.
plotEmptyDropsResults   Plots for runEmptyDrops outputs.
plotEmptyDropsScatter   Plots for runEmptyDrops outputs.
plotMASTThresholdGenes
                        MAST Identify adaptive thresholds
plotMarkerDiffExp       Plot a heatmap to visualize the result of
                        'findMarkerDiffExp'
plotPCA                 Plot PCA run data from its components.
plotRunPerCellQCResults
                        Plots for runPerCellQC outputs.
plotSCEBarAssayData     Bar plot of assay data.
plotSCEBarColData       Bar plot of colData.
plotSCEBatchFeatureMean
                        Plot mean feature value in each batch of a
                        SingleCellExperiment object
plotSCEDensity          Density plot of any data stored in the
                        SingleCellExperiment object.
plotSCEDensityAssayData
                        Density plot of assay data.
plotSCEDensityColData   Density plot of colData.
plotSCEDimReduceColData
                        Dimension reduction plot tool for colData
plotSCEDimReduceFeatures
                        Dimension reduction plot tool for assay data
plotSCEHeatmap          Plot heatmap of using data stored in
                        SingleCellExperiment Object
plotSCEScatter          Dimension reduction plot tool for all types of
                        data
plotSCEViolin           Violin plot of any data stored in the
                        SingleCellExperiment object.
plotSCEViolinAssayData
                        Violin plot of assay data.
plotSCEViolinColData    Violin plot of colData.
plotScDblFinderResults
                        Plots for runScDblFinder outputs.
plotScdsHybridResults   Plots for runCxdsBcdsHybrid outputs.
plotScrubletResults     Plots for runScrublet outputs.
plotTSNE                Plot t-SNE plot on dimensionality reduction
                        data run from t-SNE method.
plotTopHVG              Plot highly variable genes
plotUMAP                Plot UMAP results either on already run results
                        or run first and then plot.
qcInputProcess          Create SingleCellExperiment object from command
                        line input arguments
readSingleCellMatrix    Read single cell expression matrix
reportCellQC            Get runCellQC .html report
reportDiffExp           Get runDEAnalysis .html report
reportDropletQC         Get runDropletQC .html report
reportFindMarker        Get findMarkerDiffExp .html report
reportQCTool            Get .html report of the output of the selected
                        QC algorithm
retrieveSCEIndex        Retrieve cell/feature index by giving
                        identifiers saved in col/rowData
runANOVA                Perform differential expression analysis on SCE
                        with ANOVA
runBBKNN                Apply BBKNN batch effect correction method to
                        SingleCellExperiment object
runBarcodeRankDrops     Identify empty droplets using barcodeRanks.
runBcds                 Find doublets/multiplets using bcds.
runCellQC               Perform comprehensive single cell QC
runComBatSeq            Apply ComBat-Seq batch effect correction method
                        to SingleCellExperiment object
runCxds                 Find doublets/multiplets using cxds.
runCxdsBcdsHybrid       Find doublets/multiplets using
                        cxds_bcds_hybrid.
runDEAnalysis           Perform differential expression analysis on SCE
                        with specified method Method supported: 'MAST',
                        'DESeq2', 'Limma', 'ANOVA'
runDESeq2               Perform differential expression analysis on SCE
                        with DESeq2.
runDecontX              Detecting contamination with DecontX.
runDimReduce            Generic Wrapper function for running
                        dimensionality reduction
runDoubletFinder        Generates a doublet score for each cell via
                        doubletFinder
runDropletQC            Perform comprehensive droplet QC
runEmptyDrops           Identify empty droplets using emptyDrops.
runFastMNN              Apply a fast version of the mutual nearest
                        neighbors (MNN) batch effect correction method
                        to SingleCellExperiment object
runFeatureSelection     Wrapper function to run all of the feature
                        selection methods integrated within the
                        singleCellTK package including three methods
                        from Seurat ('vst', 'mean.var.plot' or
                        'dispersion') and the Scran 'modelGeneVar'
                        method.
runGSVA                 Run GSVA analysis on a SingleCellExperiment
                        object
runKMeans               Get clustering with KMeans
runLimmaBC              Apply Limma's batch effect correction method to
                        SingleCellExperiment object
runLimmaDE              Perform differential expression analysis on SCE
                        with Limma.
runMAST                 Perform differential expression analysis on SCE
                        with MAST
runMNNCorrect           Apply the mutual nearest neighbors (MNN) batch
                        effect correction method to
                        SingleCellExperiment object
runNormalization        Wrapper function to run any of the integrated
                        normalization/transformation methods in the
                        singleCellTK. The available methods include
                        'LogNormalize', 'CLR', 'RC' and 'SCTransform'
                        from Seurat, 'logNormCounts and 'CPM' from
                        Scater. Additionally, users can 'scale' using
                        Z.Score, 'transform' using log, log1p and sqrt,
                        add 'pseudocounts' and trim the final matrices
                        between a range of values.
runPerCellQC            Wrapper for calculating QC metrics with scater.
runSCANORAMA            Apply the mutual nearest neighbors (MNN) batch
                        effect correction method to
                        SingleCellExperiment object
runSCMerge              Apply scMerge batch effect correction method to
                        SingleCellExperiment object
runScDblFinder          Detect doublet cells using scDblFinder.
runScranSNN             Get clustering with SNN graph
runScrublet             Find doublets using 'scrublet'.
runSingleR              Label cell types with SingleR
runVAM                  Run VAM to score gene sets in single cell data
runWilcox               Perform differential expression analysis on SCE
                        with Wilcoxon test
runZINBWaVE             Apply ZINBWaVE Batch effect correction method
                        to SingleCellExperiment object
sampleSummaryStats      Generate table of SCTK QC outputs.
scaterCPM               scaterCPM Uses CPM from scater library to
                        compute counts-per-million.
scaterPCA               Perform PCA on a SingleCellExperiment Object A
                        wrapper to runPCA function to compute principal
                        component analysis (PCA) from a given
                        SingleCellExperiment object.
scaterlogNormCounts     scaterlogNormCounts Uses logNormCounts to log
                        normalize input data
sce                     Example Single Cell RNA-Seq data in
                        SingleCellExperiment Object, subset of 10x
                        public dataset
                        https://support.10xgenomics.com/single-cell-gene-expression/datasets/2.1.0/pbmc4k
                        A subset of 390 barcodes and top 200 genes were
                        included in this example. Within 390 barcodes,
                        195 barcodes are empty droplet, 150 barcodes
                        are cell barcode and 45 barcodes are doublets
                        predicted by scrublet and doubletFinder
                        package. This example only serves as a proof of
                        concept and a tutoriol on how to run the
                        functions in this package. The results should
                        not be used for drawing scientific conclusions.
sceBatches              Example Single Cell RNA-Seq data in
                        SingleCellExperiment object, with different
                        batches annotated
scranModelGeneVar       scranModelGeneVar Generates and stores
                        variability data from scran::modelGeneVar in
                        the input singleCellExperiment object
sctkListGeneSetCollections
                        Lists imported GeneSetCollections
sctkPythonInstallConda
                        Installs Python packages into a Conda
                        environment
sctkPythonInstallVirtualEnv
                        Installs Python packages into a virtual
                        environment
selectSCTKConda         Selects a Conda environment
selectSCTKVirtualEnvironment
                        Selects a virtual environment
setSCTKDisplayRow       Indicates which rowData to use for
                        visualization
seuratComputeHeatmap    seuratComputeHeatmap Computes the heatmap plot
                        object from the pca slot in the input sce
                        object
seuratComputeJackStraw
                        seuratComputeJackStraw Compute jackstraw plot
                        and store the computations in the input sce
                        object
seuratElbowPlot         seuratElbowPlot Computes the plot object for
                        elbow plot from the pca slot in the input sce
                        object
seuratFindClusters      seuratFindClusters Computes the clusters from
                        the input sce object and stores them back in
                        sce object
seuratFindHVG           seuratFindHVG Find highly variable genes and
                        store in the input sce object
seuratFindMarkers       seuratFindMarkers
seuratGenePlot          Compute and plot visualizations for marker
                        genes
seuratHeatmapPlot       seuratHeatmapPlot Modifies the heatmap plot
                        object so it contains specified number of
                        heatmaps in a single plot
seuratICA               seuratICA Computes ICA on the input sce object
                        and stores the calculated independent
                        components within the sce object
seuratIntegration       seuratIntegration A wrapper function to Seurat
                        Batch-Correction/Integration workflow.
seuratJackStrawPlot     seuratJackStrawPlot Computes the plot object
                        for jackstraw plot from the pca slot in the
                        input sce object
seuratNormalizeData     seuratNormalizeData Wrapper for NormalizeData()
                        function from seurat library Normalizes the sce
                        object according to the input parameters
seuratPCA               seuratPCA Computes PCA on the input sce object
                        and stores the calculated principal components
                        within the sce object
seuratPlotHVG           seuratPlotHVG Plot highly variable genes from
                        input sce object (must have highly variable
                        genes computations stored)
seuratReductionPlot     seuratReductionPlot Plots the selected
                        dimensionality reduction method
seuratReport            Computes an HTML report from the Seurat
                        workflow and returns the output SCE object with
                        the computations stored in it.
seuratRunTSNE           seuratRunTSNE Computes tSNE from the given sce
                        object and stores the tSNE computations back
                        into the sce object
seuratRunUMAP           seuratRunUMAP Computes UMAP from the given sce
                        object and stores the UMAP computations back
                        into the sce object
seuratSCTransform       seuratSCTransform Runs the SCTransform function
                        to transform/normalize the input data
seuratScaleData         seuratScaleData Scales the input sce object
                        according to the input parameters
seuratVariableFeatures
                        Get variable feature names after running
                        seuratFindHVG function
simpleLog               A decorator that prints the arguments to the
                        decorated function
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.
subsetSCECols           Subset a SingleCellExperiment object by columns
subsetSCERows           Subset a SingleCellExperiment object by rows
summarizeSCE            Summarize an assay in a SingleCellExperiment
trimCounts              Trim Counts
