Single-Cell Analysis Toolkit for Gene Expression Data in R

Documentation for package ‘scater’ version 1.10.0

Help Pages

scater-package	Single-cell analysis toolkit for expression in R
arrange	Arrange columns (cells) of a SingleCellExperiment object
arrange-method	Arrange columns (cells) of a SingleCellExperiment object
bootstraps	Accessor and replacement for bootstrap results in a 'SingleCellExperiment' object
bootstraps-method	Accessor and replacement for bootstrap results in a 'SingleCellExperiment' object
bootstraps<-	Accessor and replacement for bootstrap results in a 'SingleCellExperiment' object
bootstraps<--method	Accessor and replacement for bootstrap results in a 'SingleCellExperiment' object
calcAverage	Calculate average counts, adjusting for size factors or library size
calcIsExprs	Calculate which features are expressed in which cells using a threshold on observed counts, transcripts-per-million, counts-per-million, FPKM, or defined expression levels.
calculateAverage	Calculate average counts, adjusting for size factors or library size
calculateCPM	Calculate counts per million (CPM)
calculateFPKM	Calculate fragments per kilobase of exon per million reads mapped (FPKM)
calculateQCMetrics	Calculate QC metrics
calculateTPM	Calculate transcripts-per-million (TPM)
centreSizeFactors	Centre size factors at unity
exprs	Additional accessors for the typical elements of a SingleCellExperiment object.
exprs,SingleCellExperiment-method,	Additional accessors for the typical elements of a SingleCellExperiment object.
exprs<--method	Additional accessors for the typical elements of a SingleCellExperiment object.
filter	Return 'SingleCellExperiment' with cells matching conditions.
filter-method	Return 'SingleCellExperiment' with cells matching conditions.
findImportantPCs	Plot the explanatory PCs for each variable
fpkm	Additional accessors for the typical elements of a SingleCellExperiment object.
fpkm<-	Additional accessors for the typical elements of a SingleCellExperiment object.
getBMFeatureAnnos	Get feature annotation information from Biomart
getExplanatoryPCs	Estimate the percentage of variance explained for each gene.
getVarianceExplained	Estimate the percentage of variance explained for each gene.
isOutlier	Identify outlier values
librarySizeFactors	Compute library size factors
multiplot	Multiple plot function for ggplot2 plots
mutate	Add new variables to 'colData(object)'.
mutate-method	Add new variables to 'colData(object)'.
nexprs	Count the number of non-zero counts per cell or feature
normalise	Normalise a SingleCellExperiment object using pre-computed size factors
normalise-method	Normalise a SingleCellExperiment object using pre-computed size factors
normalize	Normalise a SingleCellExperiment object using pre-computed size factors
normalize-method	Normalise a SingleCellExperiment object using pre-computed size factors
normalizeCounts	Divide columns of a count matrix by the size factors
normalizeSCE	Normalise a SingleCellExperiment object using pre-computed size factors
norm_exprs	Additional accessors for the typical elements of a SingleCellExperiment object.
norm_exprs<-	Additional accessors for the typical elements of a SingleCellExperiment object.
plotCellData	Plot column metadata
plotColData	Plot column metadata
plotDiffusionMap	Plot specific reduced dimensions
plotExplanatoryPCs	Plot the explanatory PCs for each variable
plotExplanatoryVariables	Plot explanatory variables ordered by percentage of variance explained
plotExpression	Plot expression values for all cells
plotExprsFreqVsMean	Plot frequency against mean for each feature
plotExprsVsTxLength	Plot expression against transcript length
plotFeatureData	Plot row metadata
plotHeatmap	Plot heatmap of gene expression values
plotHighestExprs	Plot the highest expressing features
plotMDS	Plot specific reduced dimensions
plotPCA	Plot specific reduced dimensions
plotPCA-method	Plot specific reduced dimensions
plotPCASCE	Plot specific reduced dimensions
plotPhenoData	Plot column metadata
plotPlatePosition	Plot cells in plate positions
plotQC	Produce QC diagnostic plots
plotReducedDim	Plot reduced dimensions
plotRLE	Plot a relative log expression (RLE) plot
plotRLE-method	Plot a relative log expression (RLE) plot
plotRowData	Plot row metadata
plotScater	Plot an overview of expression for each cell
plotTSNE	Plot specific reduced dimensions
plotUMAP	Plot specific reduced dimensions
readKallistoResults	Read transcript quantification data
readSalmonResults	Read transcript quantification data
readSparseCounts	Read sparse count matrix from file
readTxResults	Read transcript quantification data
Reduced dimension plots	Plot specific reduced dimensions
rename	Rename variables of 'colData(object)'.
rename-method	Rename variables of 'colData(object)'.
runDiffusionMap	Create a diffusion map from cell-level data
runMDS	Perform MDS on cell-level data
runPCA	Perform PCA on cell-level data
runTSNE	Perform t-SNE on cell-level data
runUMAP	Perform UMAP on cell-level data
scater-plot-args	General visualization parameters
scater-vis-var	Variable selection for visualization
SCESet	The "Single Cell Expression Set" (SCESet) class
SCESet-class	The "Single Cell Expression Set" (SCESet) class
sc_example_cell_info	Cell information for the small example single-cell counts dataset to demonstrate capabilities of scater
sc_example_counts	A small example of single-cell counts dataset to demonstrate capabilities of scater
stand_exprs	Additional accessors for the typical elements of a SingleCellExperiment object.
stand_exprs<-	Additional accessors for the typical elements of a SingleCellExperiment object.
sumCountsAcrossFeatures	Sum counts across a feature set
summariseExprsAcrossFeatures	Summarise expression values across feature
toSingleCellExperiment	Convert an SCESet object to a SingleCellExperiment object
uniquifyFeatureNames	Make feature names unique
updateSCESet	Convert an SCESet object to a SingleCellExperiment object