{ "_id": "6a1af81c1d7bb097a09faaf1", "Package": "singleCellTK", "Type": "Package", "Title": "Comprehensive and Interactive Analysis of Single Cell RNA-Seq\nData", "Version": "2.23.0", "Authors@R": "c(person(given=\"Yichen\", family=\"Wang\", email=\"wangych@bu.edu\", role=c(\"aut\"),\ncomment = c(ORCID = \"0000-0003-4347-5199\")),\nperson(given=\"Irzam\", family=\"Sarfraz\", email=\"isarfraz@bu.edu\", role=c(\"aut\"),\ncomment = c(ORCID = \"0000-0001-8121-792X\")),\nperson(given=\"Rui\", family=\"Hong\", email=\"rzhong@bu.edu\", role=c(\"aut\")),\nperson(given=\"Yusuke\", family=\"Koga\", email=\"ykoga07@bu.edu\", role=c(\"aut\")),\nperson(given=\"Salam\", family=\"Alabdullatif\", email=\"salamha@bu.edu\", role=c(\"aut\")),\nperson(given=\"Nida\", family=\"Pervaiz\", email=\"nidapervaiz27@gmail.com\", role=c(\"aut\")),\nperson(given=\"David\", family=\"Jenkins\", email=\"dfj@bu.edu\", role=c(\"aut\"),\ncomment = c(ORCID = \"0000-0002-7451-4288\")),\nperson(given=\"Vidya\", family=\"Akavoor\", email=\"vidyaap@bu.edu\", role=c(\"aut\")),\nperson(given=\"Xinyun\", family=\"Cao\", email=\"xcao19@bu.edu\", role=c(\"aut\")),\nperson(given=\"Shruthi\", family=\"Bandyadka\", email=\"sbandya@bu.edu\", role=c(\"aut\")),\nperson(given=\"Anastasia\", family=\"Leshchyk\", email=\"aleshchk@bu.edu\", role=c(\"aut\")),\nperson(given=\"Tyler\", family=\"Faits\", email=\"tfaits@bu.edu\", role=c(\"aut\")),\nperson(given=c(\"Mohammed\", \"Muzamil\"), family=\"Khan\", email=\"mmkhan@bu.edu\", role=c(\"aut\")),\nperson(given=\"Zhe\", family=\"Wang\", email=\"zhe@bu.edu\", role=c(\"aut\")),\nperson(given=c(\"W.\", \"Evan\"), family=\"Johnson\", email=\"wej@bu.edu\", role=c(\"aut\"),\ncomment = c(ORCID = \"0000-0002-6247-6595\")),\nperson(given=\"Ming\", family=\"Liu\", email=\"mingl@bu.edu\", role=c(\"aut\")),\nperson(given=c(\"Joshua\", \"David\"), family=\"Campbell\", email=\"camp@bu.edu\", role=c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0003-0780-8662\"))\n)", "Description": "The Single Cell Toolkit (SCTK) in the singleCellTK package\nprovides an interface to popular tools for importing, quality\ncontrol, analysis, and visualization of single cell RNA-seq\ndata. 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"subDiffExANOVA", "subDiffExttest", "subsetSCECols", "subsetSCERows", "summarizeSCE", "trimCounts" ], "_datasets": [ { "name": "MitoGenes", "title": "List of mitochondrial genes of multiple reference", "object": "MitoGenes", "file": "MitoGenes.rda", "class": [ "list" ], "fields": [], "table": true, "tojson": true }, { "name": "mouseBrainSubsetSCE", "title": "Example Single Cell RNA-Seq data in SingleCellExperiment Object, GSE60361 subset", "object": "mouseBrainSubsetSCE", "file": "mouseBrainSubsetSCE.rda", "class": [ "SingleCellExperiment" ], "fields": [], "table": false, "tojson": false }, { "name": "msigdb_table", "title": "MSigDB gene get Category table", "object": "msigdb_table", "file": "msigdb_table.rda", "class": [ "data.frame" ], "fields": [ "ID", "Category", "Subcategory", "Category_Description", "Subcategory_Description" ], "rows": 17, "table": true, "tojson": true }, { "name": "sce", "title": "Example Single Cell RNA-Seq data in SingleCellExperiment Object, subset of 10x public dataset", "object": "scExample", "file": "scExample.rda", "class": [ "SingleCellExperiment" ], "fields": [], "table": false, "tojson": false }, { "name": "sceBatches", "title": "Example Single Cell RNA-Seq data in SingleCellExperiment object, with different batches annotated", "object": "sceBatches", "file": "sceBatches.rda", "class": [ "SingleCellExperiment" ], "fields": [], "table": false, "tojson": false }, { "name": "SEG", "title": "Stably Expressed Gene (SEG) list obect, with SEG sets for human and mouse.", "object": "SEG", "file": "SEG.rda", "class": [ "list" ], "fields": [], "table": false, "tojson": true } ], "_help": [ { "page": "calcEffectSizes", "title": "Finds the effect sizes for all genes in the original dataset, regardless of significance.", "topics": [ "calcEffectSizes" ] }, { "page": "combineSCE", "title": "Combine a list of SingleCellExperiment objects as one SingleCellExperiment object", "topics": [ "combineSCE" ] }, { "page": "computeHeatmap", "title": "Computes heatmap for a set of features against dimensionality reduction components", "topics": [ "computeHeatmap" ] }, { "page": "computeZScore", "title": "Compute Z-Score", "topics": [ "computeZScore" ] }, { "page": "constructSCE", "title": "Create SingleCellExperiment object from csv or txt input", "topics": [ "constructSCE" ] }, { "page": "convertSCEToSeurat", "title": "convertSCEToSeurat Converts sce object to seurat while retaining all assays and metadata", "topics": [ "convertSCEToSeurat" ] }, { "page": "convertSeuratToSCE", "title": "convertSeuratToSCE Converts the input seurat object to a sce object", "topics": [ "convertSeuratToSCE" ] }, { "page": "dedupRowNames", "title": "Deduplicate the rownames of a matrix or SingleCellExperiment object", "topics": [ "dedupRowNames" ] }, { "page": "detectCellOutlier", "title": "Detecting outliers within the SingleCellExperiment object.", "topics": [ "detectCellOutlier" ] }, { "page": "diffAbundanceFET", "title": "Calculate Differential Abundance with FET", "topics": [ "diffAbundanceFET" ] }, { "page": "discreteColorPalette", "title": "Generate given number of color codes", "topics": [ "discreteColorPalette" ] }, { "page": "distinctColors", "title": "Generate a distinct palette for coloring different clusters", "topics": [ "distinctColors" ] }, { "page": "downSampleCells", "title": "Estimate numbers of detected genes, significantly differentially expressed genes, and median significant effect size", "topics": [ "downSampleCells" ] }, { "page": "downSampleDepth", "title": "Estimate numbers of detected genes, significantly differentially expressed genes, and median significant effect size", "topics": [ "downSampleDepth" ] }, { "page": "expData", "title": "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.", "topics": [ "expData" ] }, { "page": "expData-ANY-character-method", "title": "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.", "topics": [ "expData,ANY,character-method" ] }, { "page": "expData-set", "title": "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.", "topics": [ "expData<-" ] }, { "page": "expData-set-ANY-character-CharacterOrNullOrMissing-logical-method", "title": "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.", "topics": [ "expData<-,ANY,character,CharacterOrNullOrMissing,logical-method" ] }, { "page": "expDataNames", "title": "expDataNames Get names of all the data items in the input 'SingleCellExperiment' object including assays, altExps and reducedDims.", "topics": [ "expDataNames" ] }, { "page": "expDataNames-ANY-method", "title": "expDataNames Get names of all the data items in the input 'SingleCellExperiment' object including assays, altExps and reducedDims.", "topics": [ "expDataNames,ANY-method" ] }, { "page": "expDeleteDataTag", "title": "expDeleteDataTag Remove tag against an input data from the stored tag information in the metadata of the input object.", "topics": [ "expDeleteDataTag" ] }, { "page": "exportSCE", "title": "Export data in SingleCellExperiment object", "topics": [ "exportSCE" ] }, { "page": "exportSCEtoAnnData", "title": "Export a SingleCellExperiment R object as Python annData object", "topics": [ "exportSCEtoAnnData" ] }, { "page": "exportSCEtoFlatFile", "title": "Export a SingleCellExperiment object to flat text files", "topics": [ "exportSCEtoFlatFile" ] }, { "page": "exportSCEToSeurat", "title": "Export data in Seurat object", "topics": [ "exportSCEToSeurat" ] }, { "page": "expSetDataTag", "title": "expSetDataTag Set tag to an assay or a data item in the input SCE object.", "topics": [ "expSetDataTag" ] }, { "page": "expTaggedData", "title": "expTaggedData Returns a list of names of data items from the input 'SingleCellExperiment' object based upon the input parameters.", "topics": [ "expTaggedData" ] }, { "page": "featureIndex", "title": "Retrieve row index for a set of features", "topics": [ "featureIndex" ] }, { "page": "generateHTANMeta", "title": "Generate HTAN manifest file for droplet and cell count data", "topics": [ "generateHTANMeta" ] }, { "page": "generateMeta", "title": "Generate HTAN manifest file for droplet and cell count data", "topics": [ "generateMeta" ] }, { "page": "generateSimulatedData", "title": "Generates a single simulated dataset, bootstrapping from the input counts matrix.", "topics": [ "generateSimulatedData" ] }, { "page": "getBiomarker", "title": "Given a list of genes and a SingleCellExperiment object, return the binary or continuous expression of the genes.", "topics": [ "getBiomarker" ] }, { "page": "getDEGTopTable", "title": "Get Top Table of a DEG analysis", "topics": [ "getDEGTopTable" ] }, { "page": "getDiffAbundanceResults", "title": "Get/Set diffAbundanceFET result table", "topics": [ "getDiffAbundanceResults", "getDiffAbundanceResults,SingleCellExperiment-method", "getDiffAbundanceResults<-", "getDiffAbundanceResults<-,SingleCellExperiment-method" ] }, { "page": "getEnrichRResult", "title": "Get or Set EnrichR Result", "topics": [ "getEnrichRResult", "getEnrichRResult,SingleCellExperiment-method", "getEnrichRResult<-", "getEnrichRResult<-,SingleCellExperiment-method" ] }, { "page": "getFindMarkerTopTable", "title": "Fetch the table of top markers that pass the filtering", "topics": [ "findMarkerTopTable", "getFindMarkerTopTable" ] }, { "page": "getGenesetNamesFromCollection", "title": "List geneset names from geneSetCollection", "topics": [ "getGenesetNamesFromCollection" ] }, { "page": "getMSigDBTable", "title": "Shows MSigDB categories", "topics": [ "getMSigDBTable" ] }, { "page": "getPathwayResultNames", "title": "List pathway analysis result names", "topics": [ "getPathwayResultNames" ] }, { "page": "getSampleSummaryStatsTable", "title": "Stores and returns table of SCTK QC outputs to metadata.", "topics": [ "getSampleSummaryStatsTable", "getSampleSummaryStatsTable,SingleCellExperiment-method", "setSampleSummaryStatsTable<-", "setSampleSummaryStatsTable<-,SingleCellExperiment-method" ] }, { "page": "getSceParams", "title": "Extract QC parameters from the SingleCellExperiment object", "topics": [ "getSceParams" ] }, { "page": "getSeuratVariableFeatures", "title": "Get variable feature names after running runSeuratFindHVG function", "topics": [ "getSeuratVariableFeatures" ] }, { "page": "getSoupX", "title": "Get or Set SoupX Result", "topics": [ "getSoupX", "getSoupX,SingleCellExperiment-method", "getSoupX<-", "getSoupX<-,SingleCellExperiment-method" ] }, { "page": "getTopHVG", "title": "Get or set top HVG after calculation", "topics": [ "getTopHVG", "setTopHVG" ] }, { "page": "getTSCANResults", "title": "getTSCANResults accessor function", "topics": [ "getTSCANResults", "getTSCANResults,SingleCellExperiment-method", "getTSCANResults<-", "getTSCANResults<-,SingleCellExperiment-method", "listTSCANResults", "listTSCANResults,SingleCellExperiment-method", "listTSCANTerminalNodes", "listTSCANTerminalNodes,SingleCellExperiment-method" ] }, { "page": "importAlevin", "title": "Construct SCE object from Salmon-Alevin output", "topics": [ "importAlevin" ] }, { "page": "importAnnData", "title": "Create a SingleCellExperiment Object from Python AnnData .h5ad files", "topics": [ "importAnnData" ] }, { "page": "importBUStools", "title": "Construct SCE object from BUStools output", "topics": [ "importBUStools" ] }, { "page": "importCellRanger", "title": "Construct SCE object from Cell Ranger output", "topics": [ "importCellRanger", "importCellRangerV2", "importCellRangerV3" ] }, { "page": "importCellRangerV2Sample", "title": "Construct SCE object from Cell Ranger V2 output for a single sample", "topics": [ "importCellRangerV2Sample" ] }, { "page": "importCellRangerV3Sample", "title": "Construct SCE object from Cell Ranger V3 output for a single sample", "topics": [ "importCellRangerV3Sample" ] }, { "page": "importDropEst", "title": "Create a SingleCellExperiment Object from DropEst output", "topics": [ "importDropEst" ] }, { "page": "importExampleData", "title": "Retrieve example datasets", "topics": [ "importExampleData" ] }, { "page": "importFromFiles", "title": "Create a SingleCellExperiment object from files", "topics": [ "importFromFiles" ] }, { "page": "importGeneSetsFromCollection", "title": "Imports gene sets from a GeneSetCollection object", "topics": [ "importGeneSetsFromCollection" ] }, { "page": "importGeneSetsFromGMT", "title": "Imports gene sets from a GMT file", "topics": [ "importGeneSetsFromGMT" ] }, { "page": "importGeneSetsFromList", "title": "Imports gene sets from a list", "topics": [ "importGeneSetsFromList" ] }, { "page": "importGeneSetsFromMSigDB", "title": "Imports gene sets from MSigDB", "topics": [ "importGeneSetsFromMSigDB" ] }, { "page": "importMitoGeneSet", "title": "Import mitochondrial gene sets", "topics": [ "importMitoGeneSet" ] }, { "page": "importMultipleSources", "title": "Imports samples from different sources and compiles them into a list of SCE objects", "topics": [ "importMultipleSources" ] }, { "page": "importOptimus", "title": "Construct SCE object from Optimus output", "topics": [ "importOptimus" ] }, { "page": "importSEQC", "title": "Construct SCE object from seqc output", "topics": [ "importSEQC" ] }, { "page": "importSTARsolo", "title": "Construct SCE object from STARsolo outputs", "topics": [ "importSTARsolo" ] }, { "page": "iterateSimulations", "title": "Returns significance data from a snapshot.", "topics": [ "iterateSimulations" ] }, { "page": "listSampleSummaryStatsTables", "title": "Lists the table of SCTK QC outputs stored within the metadata.", "topics": [ "listSampleSummaryStatsTables", "listSampleSummaryStatsTables,SingleCellExperiment-method" ] }, { "page": "mergeSCEColData", "title": "Merging colData from two singleCellExperiment objects", "topics": [ "mergeSCEColData" ] }, { "page": "MitoGenes", "title": "List of mitochondrial genes of multiple reference", "topics": [ "MitoGenes" ] }, { "page": "mouseBrainSubsetSCE", "title": "Example Single Cell RNA-Seq data in SingleCellExperiment Object, GSE60361 subset", "topics": [ "mouseBrainSubsetSCE" ] }, { "page": "msigdb_table", "title": "MSigDB gene get Category table", "topics": [ "msigdb_table" ] }, { "page": "plotBarcodeRankDropsResults", "title": "Plots for runBarcodeRankDrops outputs.", "topics": [ "plotBarcodeRankDropsResults" ] }, { "page": "plotBarcodeRankScatter", "title": "Plots for runBarcodeRankDrops outputs.", "topics": [ "plotBarcodeRankScatter" ] }, { "page": "plotBatchCorrCompare", "title": "Plot comparison of batch corrected result against original assay", "topics": [ "plotBatchCorrCompare" ] }, { "page": "plotBatchVariance", "title": "Plot the percent of the variation that is explained by batch and condition in the data", "topics": [ "plotBatchVariance" ] }, { "page": "plotBcdsResults", "title": "Plots for runBcds outputs.", "topics": [ "plotBcdsResults" ] }, { "page": "plotBubble", "title": "Plot Bubble plot", "topics": [ "plotBubble" ] }, { "page": "plotClusterAbundance", "title": "Plot the differential Abundance", "topics": [ "plotClusterAbundance" ] }, { "page": "plotCxdsResults", "title": "Plots for runCxds outputs.", "topics": [ "plotCxdsResults" ] }, { "page": "plotDecontXResults", "title": "Plots for runDecontX outputs.", "topics": [ "plotDecontXResults" ] }, { "page": "plotDEGHeatmap", "title": "Heatmap visualization of DEG result", "topics": [ "plotDEGHeatmap" ] }, { "page": "plotDEGRegression", "title": "Create linear regression plot to show the expression the of top DEGs", "topics": [ "plotDEGRegression" ] }, { "page": "plotDEGViolin", "title": "Generate violin plot to show the expression of top DEGs", "topics": [ "plotDEGViolin" ] }, { "page": "plotDEGVolcano", "title": "Generate volcano plot for DEGs", "topics": [ "plotDEGVolcano" ] }, { "page": "plotDimRed", "title": "Plot dimensionality reduction from computed metrics including PCA, ICA, tSNE and UMAP", "topics": [ "plotDimRed" ] }, { "page": "plotDoubletFinderResults", "title": "Plots for runDoubletFinder outputs.", "topics": [ "plotDoubletFinderResults" ] }, { "page": "plotEmptyDropsResults", "title": "Plots for runEmptyDrops outputs.", "topics": [ "plotEmptyDropsResults" ] }, { "page": "plotEmptyDropsScatter", "title": "Plots for runEmptyDrops outputs.", "topics": [ "plotEmptyDropsScatter" ] }, { "page": "plotEnrichR", "title": "Plot EnrichR results", "topics": [ "plotEnrichR" ] }, { "page": "plotFindMarkerHeatmap", "title": "Plot a heatmap to visualize the result of 'runFindMarker'", "topics": [ "plotFindMarkerHeatmap", "plotMarkerDiffExp" ] }, { "page": "plotMASTThresholdGenes", "title": "MAST Identify adaptive thresholds", "topics": [ "plotMASTThresholdGenes" ] }, { "page": "plotPathway", "title": "Generate violin plots for pathway analysis results", "topics": [ "plotPathway" ] }, { "page": "plotPCA", "title": "Plot PCA run data from its components.", "topics": [ "plotPCA" ] }, { "page": "plotRunPerCellQCResults", "title": "Plots for runPerCellQC outputs.", "topics": [ "plotRunPerCellQCResults" ] }, { "page": "plotScanpyDotPlot", "title": "plotScanpyDotPlot", "topics": [ "plotScanpyDotPlot" ] }, { "page": "plotScanpyEmbedding", "title": "plotScanpyEmbedding", "topics": [ "plotScanpyEmbedding" ] }, { "page": "plotScanpyHeatmap", "title": "plotScanpyHeatmap", "topics": [ "plotScanpyHeatmap" ] }, { "page": "plotScanpyHVG", "title": "plotScanpyHVG", "topics": [ "plotScanpyHVG" ] }, { "page": "plotScanpyMarkerGenes", "title": "plotScanpyMarkerGenes", "topics": [ "plotScanpyMarkerGenes" ] }, { "page": "plotScanpyMarkerGenesDotPlot", "title": "plotScanpyMarkerGenesDotPlot", "topics": [ "plotScanpyMarkerGenesDotPlot" ] }, { "page": "plotScanpyMarkerGenesHeatmap", "title": "plotScanpyMarkerGenesHeatmap", "topics": [ "plotScanpyMarkerGenesHeatmap" ] }, { "page": "plotScanpyMarkerGenesMatrixPlot", "title": "plotScanpyMarkerGenesMatrixPlot", "topics": [ "plotScanpyMarkerGenesMatrixPlot" ] }, { "page": "plotScanpyMarkerGenesViolin", "title": "plotScanpyMarkerGenesViolin", "topics": [ "plotScanpyMarkerGenesViolin" ] }, { "page": "plotScanpyMatrixPlot", "title": "plotScanpyMatrixPlot", "topics": [ "plotScanpyMatrixPlot" ] }, { "page": "plotScanpyPCA", "title": "plotScanpyPCA", "topics": [ "plotScanpyPCA" ] }, { "page": "plotScanpyPCAGeneRanking", "title": "plotScanpyPCAGeneRanking", "topics": [ "plotScanpyPCAGeneRanking" ] }, { "page": "plotScanpyPCAVariance", "title": "plotScanpyPCAVariance", "topics": [ "plotScanpyPCAVariance" ] }, { "page": "plotScanpyViolin", "title": "plotScanpyViolin", "topics": [ "plotScanpyViolin" ] }, { "page": "plotScDblFinderResults", "title": "Plots for runScDblFinder outputs.", "topics": [ "plotScDblFinderResults" ] }, { "page": "plotScdsHybridResults", "title": "Plots for runCxdsBcdsHybrid outputs.", "topics": [ "plotScdsHybridResults" ] }, { "page": "plotSCEBarAssayData", "title": "Bar plot of assay data.", "topics": [ "plotSCEBarAssayData" ] }, { "page": "plotSCEBarColData", "title": "Bar plot of colData.", "topics": [ "plotSCEBarColData" ] }, { "page": "plotSCEBatchFeatureMean", "title": "Plot mean feature value in each batch of a SingleCellExperiment object", "topics": [ "plotSCEBatchFeatureMean" ] }, { "page": "plotSCEDensity", "title": "Density plot of any data stored in the SingleCellExperiment object.", "topics": [ "plotSCEDensity" ] }, { "page": "plotSCEDensityAssayData", "title": "Density plot of assay data.", "topics": [ "plotSCEDensityAssayData" ] }, { "page": "plotSCEDensityColData", "title": "Density plot of colData.", "topics": [ "plotSCEDensityColData" ] }, { "page": "plotSCEDimReduceColData", "title": "Dimension reduction plot tool for colData", "topics": [ "plotSCEDimReduceColData" ] }, { "page": "plotSCEDimReduceFeatures", "title": "Dimension reduction plot tool for assay data", "topics": [ "plotSCEDimReduceFeatures" ] }, { "page": "plotSCEHeatmap", "title": "Plot heatmap of using data stored in SingleCellExperiment Object", "topics": [ "plotSCEHeatmap" ] }, { "page": "plotSCEScatter", "title": "Dimension reduction plot tool for all types of data", "topics": [ "plotSCEScatter" ] }, { "page": "plotSCEViolin", "title": "Violin plot of any data stored in the SingleCellExperiment object.", "topics": [ "plotSCEViolin" ] }, { "page": "plotSCEViolinAssayData", "title": "Violin plot of assay data.", "topics": [ "plotSCEViolinAssayData" ] }, { "page": "plotSCEViolinColData", "title": "Violin plot of colData.", "topics": [ "plotSCEViolinColData" ] }, { "page": "plotScrubletResults", "title": "Plots for runScrublet outputs.", "topics": [ "plotScrubletResults" ] }, { "page": "plotSeuratElbow", "title": "plotSeuratElbow Computes the plot object for elbow plot from the pca slot in the input sce object", "topics": [ "plotSeuratElbow" ] }, { "page": "plotSeuratGenes", "title": "Compute and plot visualizations for marker genes", "topics": [ "plotSeuratGenes" ] }, { "page": "plotSeuratHeatmap", "title": "plotSeuratHeatmap Modifies the heatmap plot object so it contains specified number of heatmaps in a single plot", "topics": [ "plotSeuratHeatmap" ] }, { "page": "plotSeuratHVG", "title": "plotSeuratHVG Plot highly variable genes from input sce object (must have highly variable genes computations stored)", "topics": [ "plotSeuratHVG" ] }, { "page": "plotSeuratJackStraw", "title": "plotSeuratJackStraw Computes the plot object for jackstraw plot from the pca slot in the input sce object", "topics": [ "plotSeuratJackStraw" ] }, { "page": "plotSeuratReduction", "title": "plotSeuratReduction Plots the selected dimensionality reduction method", "topics": [ "plotSeuratReduction" ] }, { "page": "plotSoupXResults", "title": "Plot SoupX Result", "topics": [ "plotSoupXResults" ] }, { "page": "plotTopHVG", "title": "Plot highly variable genes", "topics": [ "plotTopHVG" ] }, { "page": "plotTSCANClusterDEG", "title": "Plot features identified by 'runTSCANClusterDEAnalysis' on cell 2D embedding with MST overlaid", "topics": [ "plotTSCANClusterDEG" ] }, { "page": "plotTSCANClusterPseudo", "title": "Plot TSCAN pseudotime rooted from given cluster", "topics": [ "plotTSCANClusterPseudo" ] }, { "page": "plotTSCANDimReduceFeatures", "title": "Plot feature expression on cell 2D embedding with MST overlaid", "topics": [ "plotTSCANDimReduceFeatures" ] }, { "page": "plotTSCANPseudotimeGenes", "title": "Plot expression changes of top features along a TSCAN pseudotime path", "topics": [ "plotTSCANPseudotimeGenes" ] }, { "page": "plotTSCANPseudotimeHeatmap", "title": "Plot heatmap of genes with expression change along TSCAN pseudotime", "topics": [ "plotTSCANPseudotimeHeatmap" ] }, { "page": "plotTSCANResults", "title": "Plot MST pseudotime values on cell 2D embedding", "topics": [ "plotTSCANResults" ] }, { "page": "plotTSNE", "title": "Plot t-SNE plot on dimensionality reduction data run from t-SNE method.", "topics": [ "plotTSNE" ] }, { "page": "plotUMAP", "title": "Plot UMAP results either on already run results or run first and then plot.", "topics": [ "plotUMAP" ] }, { "page": "qcInputProcess", "title": "Create SingleCellExperiment object from command line input arguments", "topics": [ "qcInputProcess" ] }, { "page": "readSingleCellMatrix", "title": "Read single cell expression matrix", "topics": [ "readSingleCellMatrix" ] }, { "page": "reportCellQC", "title": "Get runCellQC .html report", "topics": [ "reportCellQC" ] }, { "page": "reportClusterAbundance", "title": "Get plotClusterAbundance .html report", "topics": [ "reportClusterAbundance" ] }, { "page": "reportDiffAbundanceFET", "title": "Get diffAbundanceFET .html report", "topics": [ "reportDiffAbundanceFET" ] }, { "page": "reportDiffExp", "title": "Get runDEAnalysis .html report", "topics": [ "reportDiffExp" ] }, { "page": "reportDropletQC", "title": "Get runDropletQC .html report", "topics": [ "reportDropletQC" ] }, { "page": "reportFindMarker", "title": "Get runFindMarker .html report", "topics": [ "reportFindMarker" ] }, { "page": "reportQCTool", "title": "Get .html report of the output of the selected QC algorithm", "topics": [ "reportQCTool" ] }, { "page": "reportSeurat", "title": "Generates an HTML report for the complete Seurat workflow and returns the SCE object with the results computed and stored inside the object.", "topics": [ "reportSeurat" ] }, { "page": "reportSeuratClustering", "title": "Generates an HTML report for Seurat Clustering and returns the SCE object with the results computed and stored inside the object.", "topics": [ "reportSeuratClustering" ] }, { "page": "reportSeuratDimRed", "title": "Generates an HTML report for Seurat Dimensionality Reduction and returns the SCE object with the results computed and stored inside the object.", "topics": [ "reportSeuratDimRed" ] }, { "page": "reportSeuratFeatureSelection", "title": "Generates an HTML report for Seurat Feature Selection and returns the SCE object with the results computed and stored inside the object.", "topics": [ "reportSeuratFeatureSelection" ] }, { "page": "reportSeuratMarkerSelection", "title": "Generates an HTML report for Seurat Results (including Clustering & Marker Selection) and returns the SCE object with the results computed and stored inside the object.", "topics": [ "reportSeuratMarkerSelection" ] }, { "page": "reportSeuratNormalization", "title": "Generates an HTML report for Seurat Normalization and returns the SCE object with the results computed and stored inside the object.", "topics": [ "reportSeuratNormalization" ] }, { "page": "reportSeuratResults", "title": "Generates an HTML report for Seurat Results (including Clustering & Marker Selection) and returns the SCE object with the results computed and stored inside the object.", "topics": [ "reportSeuratResults" ] }, { "page": "reportSeuratRun", "title": "Generates an HTML report for Seurat Run (including Normalization, Feature Selection, Dimensionality Reduction & Clustering) and returns the SCE object with the results computed and stored inside the object.", "topics": [ "reportSeuratRun" ] }, { "page": "reportSeuratScaling", "title": "Generates an HTML report for Seurat Scaling and returns the SCE object with the results computed and stored inside the object.", "topics": [ "reportSeuratScaling" ] }, { "page": "retrieveSCEIndex", "title": "Retrieve cell/feature index by giving identifiers saved in col/rowData", "topics": [ "retrieveSCEIndex" ] }, { "page": "runBarcodeRankDrops", "title": "Identify empty droplets using barcodeRanks.", "topics": [ "runBarcodeRankDrops" ] }, { "page": "runBBKNN", "title": "Apply BBKNN batch effect correction method to SingleCellExperiment object", "topics": [ "runBBKNN" ] }, { "page": "runBcds", "title": "Find doublets/multiplets using bcds.", "topics": [ "runBcds" ] }, { "page": "runCellQC", "title": "Perform comprehensive single cell QC", "topics": [ "runCellQC" ] }, { "page": "runClusterSummaryMetrics", "title": "Run Cluster Summary Metrics", "topics": [ "runClusterSummaryMetrics" ] }, { "page": "runComBatSeq", "title": "Apply ComBat-Seq batch effect correction method to SingleCellExperiment object", "topics": [ "runComBatSeq" ] }, { "page": "runCxds", "title": "Find doublets/multiplets using cxds.", "topics": [ "runCxds" ] }, { "page": "runCxdsBcdsHybrid", "title": "Find doublets/multiplets using cxds_bcds_hybrid.", "topics": [ "runCxdsBcdsHybrid" ] }, { "page": "runDEAnalysis", "title": "Perform differential expression analysis on SCE object", "topics": [ "runANOVA", "runDEAnalysis", "runDESeq2", "runLimmaDE", "runMAST", "runWilcox" ] }, { "page": "runDecontX", "title": "Detecting contamination with DecontX.", "topics": [ "runDecontX" ] }, { "page": "runDimReduce", "title": "Generic Wrapper function for running dimensionality reduction", "topics": [ "runDimReduce" ] }, { "page": "runDoubletFinder", "title": "Generates a doublet score for each cell via doubletFinder", "topics": [ "runDoubletFinder" ] }, { "page": "runDropletQC", "title": "Perform comprehensive droplet QC", "topics": [ "runDropletQC" ] }, { "page": "runEmptyDrops", "title": "Identify empty droplets using emptyDrops.", "topics": [ "runEmptyDrops" ] }, { "page": "runEnrichR", "title": "Run EnrichR on SCE object", "topics": [ "runEnrichR" ] }, { "page": "runFastMNN", "title": "Apply a fast version of the mutual nearest neighbors (MNN) batch effect correction method to SingleCellExperiment object", "topics": [ "runFastMNN" ] }, { "page": "runFeatureSelection", "title": "Run Variable Feature Detection Methods", "topics": [ "runFeatureSelection" ] }, { "page": "runFindMarker", "title": "Find the marker gene set for each cluster", "topics": [ "findMarkerDiffExp", "runFindMarker" ] }, { "page": "runGSVA", "title": "Run GSVA analysis on a SingleCellExperiment object", "topics": [ "runGSVA" ] }, { "page": "runHarmony", "title": "Apply Harmony batch effect correction method to SingleCellExperiment object", "topics": [ "runHarmony" ] }, { "page": "runKMeans", "title": "Get clustering with KMeans", "topics": [ "runKMeans" ] }, { "page": "runLimmaBC", "title": "Apply Limma's batch effect correction method to SingleCellExperiment object", "topics": [ "runLimmaBC" ] }, { "page": "runMNNCorrect", "title": "Apply the mutual nearest neighbors (MNN) batch effect correction method to SingleCellExperiment object", "topics": [ "runMNNCorrect" ] }, { "page": "runModelGeneVar", "title": "Calculate Variable Genes with Scran modelGeneVar", "topics": [ "runModelGeneVar" ] }, { "page": "runNormalization", "title": "Run normalization/transformation with various methods", "topics": [ "runNormalization" ] }, { "page": "runPerCellQC", "title": "Wrapper for calculating QC metrics with scater.", "topics": [ "runPerCellQC" ] }, { "page": "runSCANORAMA", "title": "Apply the mutual nearest neighbors (MNN) batch effect correction method to SingleCellExperiment object", "topics": [ "runSCANORAMA" ] }, { "page": "runScanpyFindClusters", "title": "runScanpyFindClusters Computes the clusters from the input sce object and stores them back in sce object", "topics": [ "runScanpyFindClusters" ] }, { "page": "runScanpyFindHVG", "title": "runScanpyFindHVG Find highly variable genes and store in the input sce object", "topics": [ "runScanpyFindHVG" ] }, { "page": "runScanpyFindMarkers", "title": "runScanpyFindMarkers", "topics": [ "runScanpyFindMarkers" ] }, { "page": "runScanpyNormalizeData", "title": "runScanpyNormalizeData Wrapper for NormalizeData() function from scanpy library Normalizes the sce object according to the input parameters", "topics": [ "runScanpyNormalizeData" ] }, { "page": "runScanpyPCA", "title": "runScanpyPCA Computes PCA on the input sce object and stores the calculated principal components within the sce object", "topics": [ "runScanpyPCA" ] }, { "page": "runScanpyScaleData", "title": "runScanpyScaleData Scales the input sce object according to the input parameters", "topics": [ "runScanpyScaleData" ] }, { "page": "runScanpyTSNE", "title": "runScanpyTSNE Computes tSNE from the given sce object and stores the tSNE computations back into the sce object", "topics": [ "runScanpyTSNE" ] }, { "page": "runScanpyUMAP", "title": "runScanpyUMAP Computes UMAP from the given sce object and stores the UMAP computations back into the sce object", "topics": [ "runScanpyUMAP" ] }, { "page": "runScDblFinder", "title": "Detect doublet cells using scDblFinder.", "topics": [ "runScDblFinder" ] }, { "page": "runSCMerge", "title": "Apply scMerge batch effect correction method to SingleCellExperiment object", "topics": [ "runSCMerge" ] }, { "page": "runScranSNN", "title": "Get clustering with SNN graph", "topics": [ "runScranSNN" ] }, { "page": "runScrublet", "title": "Find doublets using 'scrublet'.", "topics": [ "runScrublet" ] }, { "page": "runSeuratFindClusters", "title": "runSeuratFindClusters Computes the clusters from the input sce object and stores them back in sce object", "topics": [ "runSeuratFindClusters" ] }, { "page": "runSeuratFindHVG", "title": "runSeuratFindHVG Find highly variable genes and store in the input sce object", "topics": [ "runSeuratFindHVG" ] }, { "page": "runSeuratFindMarkers", "title": "runSeuratFindMarkers", "topics": [ "runSeuratFindMarkers" ] }, { "page": "runSeuratHeatmap", "title": "runSeuratHeatmap Computes the heatmap plot object from the pca slot in the input sce object", "topics": [ "runSeuratHeatmap" ] }, { "page": "runSeuratICA", "title": "runSeuratICA Computes ICA on the input sce object and stores the calculated independent components within the sce object", "topics": [ "runSeuratICA" ] }, { "page": "runSeuratIntegration", "title": "runSeuratIntegration A wrapper function to Seurat Batch-Correction/Integration workflow.", "topics": [ "runSeuratIntegration" ] }, { "page": "runSeuratJackStraw", "title": "runSeuratJackStraw Compute jackstraw plot and store the computations in the input sce object", "topics": [ "runSeuratJackStraw" ] }, { "page": "runSeuratNormalizeData", "title": "runSeuratNormalizeData Wrapper for NormalizeData() function from seurat library Normalizes the sce object according to the input parameters", "topics": [ "runSeuratNormalizeData" ] }, { "page": "runSeuratPCA", "title": "runSeuratPCA Computes PCA on the input sce object and stores the calculated principal components within the sce object", "topics": [ "runSeuratPCA" ] }, { "page": "runSeuratScaleData", "title": "runSeuratScaleData Scales the input sce object according to the input parameters", "topics": [ "runSeuratScaleData" ] }, { "page": "runSeuratSCTransform", "title": "runSeuratSCTransform Runs the SCTransform function to transform/normalize the input data", "topics": [ "runSeuratSCTransform" ] }, { "page": "runSeuratTSNE", "title": "runSeuratTSNE Computes tSNE from the given sce object and stores the tSNE computations back into the sce object", "topics": [ "runSeuratTSNE" ] }, { "page": "runSeuratUMAP", "title": "runSeuratUMAP Computes UMAP from the given sce object and stores the UMAP computations back into the sce object", "topics": [ "runSeuratUMAP" ] }, { "page": "runSingleR", "title": "Label cell types with SingleR", "topics": [ "runSingleR" ] }, { "page": "runSoupX", "title": "Detecting and correct contamination with SoupX", "topics": [ "runSoupX" ] }, { "page": "runTSCAN", "title": "Run TSCAN to obtain pseudotime values for cells", "topics": [ "runTSCAN" ] }, { "page": "runTSCANClusterDEAnalysis", "title": "Find DE genes between all TSCAN paths rooted from given cluster", "topics": [ "runTSCANClusterDEAnalysis" ] }, { "page": "runTSCANDEG", "title": "Test gene expression changes along a TSCAN trajectory path", "topics": [ "runTSCANDEG" ] }, { "page": "runTSNE", "title": "Run t-SNE embedding with Rtsne method", "topics": [ "getTSNE", "runQuickTSNE", "runTSNE" ] }, { "page": "runUMAP", "title": "Run UMAP embedding with scater method", "topics": [ "getUMAP", "runQuickUMAP", "runUMAP" ] }, { "page": "runVAM", "title": "Run VAM to score gene sets in single cell data", "topics": [ "runVAM" ] }, { "page": "runZINBWaVE", "title": "Apply ZINBWaVE Batch effect correction method to SingleCellExperiment object", "topics": [ "runZINBWaVE" ] }, { "page": "sampleSummaryStats", "title": "Generate table of SCTK QC outputs.", "topics": [ "sampleSummaryStats" ] }, { "page": "scaterCPM", "title": "scaterCPM Uses CPM from scater library to compute counts-per-million.", "topics": [ "scaterCPM" ] }, { "page": "scaterlogNormCounts", "title": "scaterlogNormCounts Uses logNormCounts to log normalize input data", "topics": [ "scaterlogNormCounts" ] }, { "page": "scaterPCA", "title": "Perform scater PCA on a SingleCellExperiment Object", "topics": [ "scaterPCA" ] }, { "page": "sce", "title": "Example Single Cell RNA-Seq data in SingleCellExperiment Object, subset of 10x public dataset", "topics": [ "sce" ] }, { "page": "sceBatches", "title": "Example Single Cell RNA-Seq data in SingleCellExperiment object, with different batches annotated", "topics": [ "sceBatches" ] }, { "page": "sctkListGeneSetCollections", "title": "Lists imported GeneSetCollections", "topics": [ "sctkListGeneSetCollections" ] }, { "page": "sctkPythonInstallConda", "title": "Installs Python packages into a Conda environment", "topics": [ "sctkPythonInstallConda" ] }, { "page": "sctkPythonInstallVirtualEnv", "title": "Installs Python packages into a virtual environment", "topics": [ "sctkPythonInstallVirtualEnv" ] }, { "page": "SEG", "title": "Stably Expressed Gene (SEG) list obect, with SEG sets for human and mouse.", "topics": [ "SEG" ] }, { "page": "selectSCTKConda", "title": "Selects a Conda environment", "topics": [ "selectSCTKConda" ] }, { "page": "selectSCTKVirtualEnvironment", "title": "Selects a virtual environment", "topics": [ "selectSCTKVirtualEnvironment" ] }, { "page": "setRowNames", "title": "Set rownames of SCE with a character vector or a rowData column", "topics": [ "setRowNames" ] }, { "page": "setSCTKDisplayRow", "title": "Indicates which rowData to use for visualization", "topics": [ "setSCTKDisplayRow" ] }, { "page": "singleCellTK", "title": 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