Function reference • AcidGenerics

All functions

EnsemblToNcbi(): Ensembl-to-NCBI gene identifier mappings

GeneToSymbol(): Gene-to-symbol mappings

KnownMarkers(): Known cell markers

NcbiToEnsembl(): NCBI-to-Ensembl gene identifier mappings

TxToGene(): Transcript-to-gene mappings

aggregateCellsToSamples(): Aggregate cells to samples

aggregateCols(): Aggregate columns

aggregateRows(): Aggregate rows

alphaSummary(): Alpha level cutoff summary statistics

alphaThreshold() `alphaThreshold<-`(): Alpha threshold

as.DESeqDataSet(): Coerce object to DESeqDataSet

as.DESeqTransform(): Coerce object to DESeqTransform

as.DGEList(): Coerce object to DGEList

as.DataFrame(): Coerce object to S4 DataFrame

as.Seurat(): Coerce object to Seurat

as.SingleCellExperiment(): Coerce object to SingleCellExperiment

as.SummarizedExperiment(): Coerce object to SummarizedExperiment

atomize(): Atomize

autopadZeros(): Autopad zeros

barcodeRanksPerSample(): Barcode ranks per sample

baseMeanThreshold() `baseMeanThreshold<-`(): Base mean threshold

calculateMetrics(): Calculate quality control metrics

camelCase(): Camel case

capitalize(): Capitalize

cast(): Cast data from long to wide format

cellCountsPerCluster(): Cell counts per cluster

cellToSample(): Cell-to-sample mappings

cellTypesPerCluster(): Cell types per cluster

cellsPerGeneFusion(): Cells per gene fusion

cellsPerMutation(): Cells per mutation

clusters(): Cluster identifiers

coerceToList(): Coerce to list

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

convertToHuman(): Convert data set by mapping to human orthologs

convertTranscriptsToGenes(): Convert transcripts to genes

correlation(): Correlation

cpm(): Counts per million

deg(): Differentially expressed genes

degIntersection(): Intersection of differentially expressed genes

degPerContrast(): Differentially expressed genes per contrast

diffExp(): Differential expression

diffExpPerCluster(): Differential expression per cluster

dottedCase(): Dotted case

droplevels2(): Drop factor levels

encode(): Encode using run-length encoding

enrichedGeneSets(): Enriched gene sets

euclidean(): Calculate Euclidean distance

excludeContaminatedCells(): Exclude contaminated cells

excludeNonCancerCells(): Exclude non-cancer cell lines

excludeNonHumanCells(): Exclude non-human cell lines

excludeProblematicCells(): Exclude problematic cells

export(): Export data from R

factorize(): Factorize

filterCells(): Filter cells

filterNested(): Keep rows that match a nested condition

findMarkers(): Find cluster-specific marker genes

foldChangeToLogRatio(): Fold change to log ratio

fpkm(): Fragments per kilobase per million mapped fragments

geneFusions(): Gene fusion pairs

geneIds(): Gene identifiers

geneNames(): Gene names

geneSet(): Gene set

geneSetNames(): Gene set names

geneSetResults(): Gene set results

geometricMean(): Geometric mean

headtail(): Return the first and last parts of an object

humanize(): Humanize an R object

import(): Import data into R

integerCounts(): Integer counts

interestingGroups() `interestingGroups<-`(): Interesting groups

intersectAll(): Intersection of more than two vectors

intersectionMatrix(): Intersection matrix

innerJoin() leftJoin() rightJoin() fullJoin() semiJoin() antiJoin(): Join operations

kebabCase(): Kebab case

keepOnlyAtomicCols(): Keep only atomic columns

leadingEdge(): Leading edge genes

lfcShrink() `lfcShrink<-`(): Shrink log2 fold changes

lfcShrinkType(): Shrunken log2 fold change (LFC) type

lfcThreshold() `lfcThreshold<-`(): Log2 fold change threshold

logRatioToFoldChange(): Log ratio to fold change

makeDimnames(): Make syntactically valid dimnames

makeLabel(): Make a plot axis or legend label out of a character string

makeNames(): Make syntactically valid names

makeSampleData(): Make sample data

makeTitle(): Make a title out of character string

makeWords(): Convert syntactic names to words separated by spaces

mapCells(): Map input to cell identifiers

mapColnames(): Map input to column names

mapGenes(): Map input to gene identifiers

mapGenesToIds(): Map genes (gene names) to gene identifiers

mapGenesToRownames(): Map genes to row names

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

mapRownames(): Map input to row names

markdownPlots(): Markdown plots

markdownTables(): Markdown tables

matchAll(): Match all positions of an argument

matchCellColumn(): Match cell identifier column

matchGeneColumn(): Match gene identifier column

matchNested(): Match inside nested elements

matchRownameColumn(): Match row name column

matchSampleColumn(): Match sample identifier column

matchTranscriptColumn(): Match transcript identifier column

melt(): Melt data from wide to long format

metadata2() `metadata2<-`(): Metadata

metrics(): Quality control metrics

metricsPerSample(): Quality control metrics per sample

mutateAll() mutateAt() mutateIf() transmuteAt() transmuteIf(): Mutate multiple columns

mutations(): Mutations

nesThreshold() `nesThreshold<-`(): Normalized enrichment score (NES) threshold

nonzeroRowsAndCols(): Subset object to keep only non-zero rows and columns

plot5Prime3PrimeBias(): Plot 5' to 3' bias

plotBarcodeRanks(): Plot barcode ranks

plotBaseMean(): Plot base mean distribution

plotCellCounts(): Plot cell counts

plotCellCountsPerCluster(): Plot cell counts per cluster

plotCellTypesPerCluster(): Plot cell types per cluster

plotCells(): Plot cells

plotCleveland(): Cleveland plot

plotContrastScatter(): Plot scatterplot of differential expression contrast

plotCorrelation(): Correlation X-Y scatterplot

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

plotCountsVsFeatures(): Plot count and feature correlation

plotDegHeatmap(): Differentially expressed gene heatmap

plotDegPca(): Plot differentially expressed gene principal component analysis

plotDegStackedBar(): Stacked bar plot of DEGs

plotDegUpset(): UpSet plot of directional DEG intersections across contrasts

plotDots(): 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

plotFeatureSaturation(): Plot feature (gene) detection saturation

plotFeaturesDetected(): Plot features detected

plotFeaturesPerCell(): Plot features per cell

plotGenderMarkers(): Plot sexually dimorphic gender marker genes

plotGeneEffect(): Plot gene effect

plotGeneEffectVsExpression(): Plot gene effect vs. expression

plotGeneSet(): Plot gene set enrichment

plotHeatmap(): Heatmap

plotIntergenicMappingRate(): Plot intergenic mapping rate

plotIntronicMappingRate(): Plot intronic mapping rate

plotKnownMarkers(): Plot known markers

plotLfc(): Plot log2 fold change distributions

plotMa(): MA plot

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

plotNes(): Plot normalized enrichment score

plotNovelty(): Plot novelty score

plotPcElbow(): Plot principal component elbow

plotPca(): Principal component analysis plot

plotPcaCovariates(): Find correlation between principal components (PCs) and covariates

plotPseudoVsAlignedCounts(): Plot pseudo vs. aligned counts

plotQc(): Quality control

plotQuantileHeatmap(): Quantile heatmap

plotReadsPerCell(): Plot read counts per cell

plotReducedDim(): Plot reduced dimensions

plotRrnaMappingRate(): Plot ribosomal RNA (rRNA) mapping rate

plotStackedBarPlot(): Plot stacked bar plot

plotSums(): Plot row or column sums

plotTopGeneEffectPerCell(): Plot top gene effect per cell

plotTopGeneEffectPerGroup(): Plot top gene effect per group

plotTopMarkers(): Plot top markers

plotTotalCounts(): Plot total read counts

plotTotalReads(): Plot total reads

plotTsne(): t-SNE plot

plotUmap(): UMAP plot

plotUpset(): UpSet plot

plotViolin(): Violin plot

plotVolcano(): Volcano plot

plotWaterfall(): Plot waterfall

plotZerosVsDepth(): Plot percentage of zeros vs. library depth

predictSensitivity(): Predict sensitivity

rankedMatrix(): Calculate a ranked matrix

rbindToDataFrame(): Row bind elements 1:1 to a data frame

relativeLogExpression(): Relative log expression

removeNa(): Remove rows and columns containing only NA values

results(): Results

resultsDiff(): Relative difference of 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

selectCells(): Select cells

selectSamples(): Select samples

sem(): Standard error of the mean

sentenceCase(): Sentence case

showHeader(): Header for object show method

slotAlignedCounts(): Slot aligned counts

snakeCase(): Snake case

splitByLevel(): Split by factor level

standardizeCells(): Standardize cell line names

stripExonVersions(): Strip exon identifier versions

stripGeneVersions(): Strip gene identifier versions

stripTranscriptVersions(): Strip transcript identifier versions

subsetPerSample(): Subset per sample

tmm(): Trimmed mean of M-values

tnbc(): Triple-negative breast cancer (TNBC)

topCellsPerSample(): Top cells per sample

topMarkers(): Top markers

tpm(): Transcripts per million

transcriptIds(): Transcript identifiers

transcriptNames(): Transcript names

transformType(): Variance-stabilizing transformation type

unfactorize(): Unfactorize

uniteInterestingGroups(): Unite interesting groups into a single column

unlist2(): Flatten lists

unnest2(): Unnest a single list-column into expanded rows

upperCamelCase(): Upper camel case

zerosVsDepth(): Percentage of zeros vs. library depth

zscore(): Calculate Z-score