All functions

aggregateCellsToSamples()

Aggregate cells to samples

aggregateCols()

Aggregate columns

aggregateReplicates()

Aggregate technical replicates

aggregateRows()

Aggregate rows

alphaSummary()

Alpha level cutoff summary statistics

alphaThreshold() `alphaThreshold<-`()

Alpha threshold

atomize()

Atomize

autopadZeros()

Autopad zeros

barcodeRanksPerSample()

Barcode ranks per sample

calculateMetrics()

Calculate quality control metrics

cell2sample()

Cell-to-sample mappings

cellCountsPerCluster()

Cell counts per cluster

cellTypesPerCluster()

Cell types per cluster

clusters()

Cluster identifiers

collapseToString()

Collapse to string

collectionNames() `collectionNames<-`()

Gene set collection names

contrastName() `contrastName<-`()

Contrast name

contrastNames() `contrastNames<-`()

Contrast names

contrastSamples()

Samples corresponding to a differential expression contrast

convertGenesToSymbols()

Convert genes to symbols

convertSampleIDsToNames()

Convert sample identifiers to names

convertSymbolsToGenes()

Convert symbols to genes

convertTranscriptsToGenes()

Convert transcripts to genes

cpm()

Counts per million

deg()

Differentially expressed genes

diffExp()

Differential expression

diffExpPerCluster()

Differential expression per cluster

encode()

Encode using run-length encoding

enrichedGeneSets()

Enriched gene sets

export()

Export

factorize()

Factorize

filterCells()

Filter cells

findMarkers()

Find cluster-specific marker genes

foldChangeToLogRatio()

Fold change to log ratio

fpkm()

Fragments per kilobase per million mapped fragments

geneNames()

Gene names

geometricMean()

Geometric mean

headtail()

Return the first and last parts of an object

humanize()

Humanize an R object

interestingGroups() `interestingGroups<-`()

Interesting groups

innerJoin() leftJoin() rightJoin() fullJoin() semiJoin() antiJoin()

Join operations

lfcThreshold() `lfcThreshold<-`()

Log2 fold change threshold

logRatioToFoldChange()

Log ratio to fold change

mapGenesToIDs()

Map genes (gene names) to gene identifiers

mapGenesToRownames()

Map genes to row names

mapGenesToSymbols()

Map genes (gene identifiers) to gene names (symbols)

markdown()

Markdown

mcolnames() `mcolnames<-`()

Metadata column names

melt()

Melt columns into key-value pairs

metrics()

Quality control metrics

metricsPerSample()

Quality control metrics per sample

mutateAll() mutateAt() mutateIf() transmuteAt() transmuteIf()

Mutate multiple columns

nonzeroRowsAndCols()

Subset object to keep only non-zero rows and columns

plot5Prime3PrimeBias()

Plot 5' to 3' bias

plotBarcodeRanks()

Plot barcode ranks

plotCellCounts()

Plot cell counts

plotCellCountsPerCluster()

Plot cell counts per cluster

plotCellTypesPerCluster()

Plot cell types per cluster

plotCells()

Plot cells

plotCorrelationHeatmap()

Correlation heatmap

plotCountDensity()

Plot count density

plotCounts()

Plot counts

plotCountsCorrelation()

Plot counts correlation

plotCountsCorrelationHeatmap()

Plot counts correlation heatmap

plotCountsPerBiotype()

Plot counts per biotype

plotCountsPerBroadClass()

Plot counts per broad class definition

plotCountsPerCell()

Plot counts per cell

plotCountsPerFeature()

Plot counts per feature

plotCountsPerGene()

Plot counts per gene

plotCountsVsFeatures()

Plot count and feature correlation

plotDEGHeatmap()

Differentially expressed gene heatmap

plotDEGPCA()

Plot differentially expressed gene principal component analysis

plotDEGUpset()

UpSet plot of directional DEG intersections across contrasts

plotDot()

Dot plot

plotEnrichedGeneSets()

Plot enriched gene sets

plotEnrichedUpset()

UpSet plot of directional enriched pathway intersections across contrasts

plotExonicMappingRate()

Plot exonic mapping rate

plotFeature()

Plot feature

plotFeaturesDetected()

Plot features detected

plotFeaturesPerCell()

Plot features per cell

plotGSEATable()

Plot GSEA enrichment table

plotGenderMarkers()

Plot sexually dimorphic gender marker genes

plotGeneSaturation()

Plot gene detection saturation

plotHeatmap()

Heatmap

plotIntergenicMappingRate()

Plot intergenic mapping rate

plotIntronicMappingRate()

Plot intronic mapping rate

plotKnownMarkers()

Plot known markers

plotMappedReads()

Plot mapped reads

plotMappingRate()

Plot mapping rate

plotMarker()

Plot cell-type-specific gene markers

plotMeanSD()

Plot row standard deviations vs. row means

plotMitoRatio()

Plot mitochondrial transcript abundance

plotMitoVsCoding()

Plot mitochondrial vs. coding counts

plotNovelty()

Plot novelty score

plotPCACovariates()

Find correlation between principal components (PCs) and covariates

plotPCElbow()

Plot principal component elbow

plotQC()

Quality control

plotQuantileHeatmap()

Quantile heatmap

plotRRNAMappingRate()

Plot ribosomal RNA (rRNA) mapping rate

plotReadsPerCell()

Plot read counts per cell

plotReducedDim()

Plot reduced dimensions

plotSums()

Plot row or column sums

plotTSNE()

t-SNE plot

plotTopMarkers()

Plot top markers

plotTotalCounts()

Plot total read counts

plotTotalReads()

Plot total reads

plotUMAP()

UMAP plot

plotViolin()

Violin plot

plotVolcano()

Volcano plot

plotZerosVsDepth()

Plot percentage of zeros vs. library depth

pseudobulk()

Pseudobulk

rankedList()

Ranked list

relativeLogExpression()

Relative log expression

removeNA()

Remove rows and columns containing only NA values

results()

Results

resultsMatrix()

Results matrix

resultsNames() `resultsNames<-`()

Results names

resultsTables()

Results tables

sampleData() `sampleData<-`()

Sample data

sanitizeNA()

Sanitize NA values

sanitizePercent()

Sanitize percentage

selectIf()

Select multiple columns

selectSamples()

Select samples

stripTranscriptVersions()

Strip transcript versions

subsetPerSample()

Subset per sample

tmm()

Trimmed mean of M-values

topCellsPerSample()

Top cells per sample

topMarkers()

Top markers

topTables()

Top tables

tpm()

Transcripts per million

uniteInterestingGroups()

Unite interesting groups into a single column

zerosVsDepth()

Percentage of zeros vs. library depth