Importing scRNA-seq data

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() importCellRangerV2() importCellRangerV3()

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

readSingleCellMatrix()

Read single cell expression matrix

Quality Control & Preprocessing

runCellQC()

Perform comprehensive single cell QC

runDropletQC()

Perform comprehensive droplet QC

Decontamination

runDecontX()

Detecting contamination with DecontX.

Doublet/Empty Droplet Detection

runBarcodeRankDrops()

Identify empty droplets using barcodeRanks.

runEmptyDrops()

Identify empty droplets using emptyDrops.

runBcds()

Find doublets/multiplets using bcds.

runCxds()

Find doublets/multiplets using cxds.

runCxdsBcdsHybrid()

Find doublets/multiplets using cxds_bcds_hybrid.

runScDblFinder()

Detect doublet cells using scDblFinder.

runDoubletFinder()

Generates a doublet score for each cell via doubletFinder

runScrublet()

Find doublets using scrublet.

Normalization

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.

scaterlogNormCounts()

scaterlogNormCounts Uses logNormCounts to log normalize input data

scaterCPM()

scaterCPM Uses CPM from scater library to compute counts-per-million.

seuratNormalizeData()

seuratNormalizeData Wrapper for NormalizeData() function from seurat library Normalizes the sce object according to the input parameters

seuratScaleData()

seuratScaleData Scales the input sce object according to the input parameters

computeZScore()

Compute Z-Score

trimCounts()

Trim Counts

Batch Effect Correction

runComBatSeq()

Apply ComBat-Seq batch effect correction method to SingleCellExperiment object

runBBKNN()

Apply BBKNN batch effect correction method to SingleCellExperiment object

runFastMNN()

Apply a fast version of the mutual nearest neighbors (MNN) batch effect correction method to SingleCellExperiment object

runLimmaBC()

Apply Limma's batch effect correction method to SingleCellExperiment object

runMNNCorrect()

Apply the mutual nearest neighbors (MNN) batch effect correction method to SingleCellExperiment object

runSCANORAMA()

Apply the mutual nearest neighbors (MNN) batch effect correction method to SingleCellExperiment object

runSCMerge()

Apply scMerge batch effect correction method to SingleCellExperiment object

seuratIntegration()

seuratIntegration A wrapper function to Seurat Batch-Correction/Integration workflow.

runZINBWaVE()

Apply ZINBWaVE Batch effect correction method to SingleCellExperiment object

plotBatchVariance()

Plot the percent of the variation that is explained by batch and condition in the data

Feature Selection

scranModelGeneVar()

scranModelGeneVar Generates and stores variability data from scran::modelGeneVar in the input singleCellExperiment object

seuratFindHVG()

seuratFindHVG Find highly variable genes and store in the input sce object

getTopHVG()

getTopHVG Extracts the top variable genes from an input singleCellExperiment object

seuratPlotHVG()

seuratPlotHVG Plot highly variable genes from input sce object (must have highly variable genes computations stored)

Dimensionality Reduction

scaterPCA()

Perform PCA on a SingleCellExperiment Object A wrapper to runPCA function to compute principal component analysis (PCA) from a given SingleCellExperiment object.

getUMAP()

Uniform Manifold Approximation and Projection(UMAP) algorithm for dimension reduction.

getTSNE()

Run t-SNE dimensionality reduction method on a SingleCellExperiment Object

seuratICA()

seuratICA Computes ICA on the input sce object and stores the calculated independent components within the sce object

seuratPCA()

seuratPCA Computes PCA on the input sce object and stores the calculated principal components within the sce object

seuratRunUMAP()

seuratRunUMAP Computes UMAP from the given sce object and stores the UMAP computations back into the sce object

seuratRunTSNE()

seuratRunTSNE Computes tSNE from the given sce object and stores the tSNE computations back into the sce object

plotSCEDimReduceColData()

Dimension reduction plot tool for colData

plotSCEDimReduceFeatures()

Dimension reduction plot tool for assay data

Clustering

runScranSNN()

Get clustering with SNN graph

seuratFindClusters()

seuratFindClusters Computes the clusters from the input sce object and stores them back in sce object

runKMeans()

Get clustering with KMeans

Differential Expression

runDEAnalysis()

Perform differential expression analysis on SCE with specified method Method supported: 'MAST', 'DESeq2', 'Limma', 'ANOVA'

runWilcox()

Perform differential expression analysis on SCE with Wilcoxon test

runMAST()

Perform differential expression analysis on SCE with MAST

runDESeq2()

Perform differential expression analysis on SCE with DESeq2.

runLimmaDE()

Perform differential expression analysis on SCE with Limma.

runANOVA()

Perform differential expression analysis on SCE with ANOVA

plotDEGViolin()

plot the violin plot to show visualize the expression distribution of DEGs identified by differential expression analysis

plotDEGRegression()

plot the linear regression to show visualize the expression the of DEGs identified by differential expression analysis

plotDEGHeatmap()

Heatmap visualization of DEG result

plotMASTThresholdGenes()

MAST Identify adaptive thresholds

Find Marker

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.

plotMarkerDiffExp()

Plot a heatmap to visualize the result of findMarkerDiffExp

Visualization

plotBarcodeRankDropsResults()

Plots for runEmptyDrops outputs.

plotBarcodeRankScatter()

Plots for runBarcodeRankDrops outputs.

plotBatchVariance()

Plot the percent of the variation that is explained by batch and condition in the data

plotBcdsResults()

Plots for runBcds outputs.

plotBiomarker()

Given a set of genes, return a ggplot of expression values.

plotClusterAbundance()

Plot the differential Abundance

plotCxdsResults()

Plots for runCxds outputs.

plotDecontXResults()

Plots for runDecontX 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

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.

plotHeatmapMulti()

plotHeatmapMulti

plotMarkerDiffExp()

Plot a heatmap to visualize the result of findMarkerDiffExp

plotMASTThresholdGenes()

MAST Identify adaptive thresholds

plotPCA()

Plot PCA run data from its components.

plotRunPerCellQCResults()

Plots for runPerCellQC outputs.

plotScDblFinderResults()

Plots for runScDblFinder outputs.

plotScdsHybridResults()

Plots for runCxdsBcdsHybrid 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.

plotScrubletResults()

Plots for runScrublet outputs.

plotTopHVG()

Plot highly variable genes

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.

Exporting Results

exportSCE()

Export data in SingleCellExperiment object

exportSCEtoAnnData()

Export a SingleCellExperiment R object as Python annData object

exportSCEtoFlatFile()

Export a SingleCellExperiment object to flat text files

exportSCEToSeurat()

Export data in Seurat object

Other Data processing

combineSCE()

Combine a list of SingleCellExperiment objects as one SingleCellExperiment object

convertSCEToSeurat()

convertSCEToSeurat Converts sce object to seurat while retaining all assays and metadata

convertSeuratToSCE()

convertSeuratToSCE Converts the input seurat object to a sce object

subsetSCECols()

Subset a SingleCellExperiment object by columns

subsetSCERows()

Subset a SingleCellExperiment object by rows

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.