Package: SingleR 2.9.6

Aaron Lun

SingleR: Reference-Based Single-Cell RNA-Seq Annotation

Performs unbiased cell type recognition from single-cell RNA sequencing data, by leveraging reference transcriptomic datasets of pure cell types to infer the cell of origin of each single cell independently.

Authors:Dvir Aran [aut, cph], Aaron Lun [ctb, cre], Daniel Bunis [ctb], Jared Andrews [ctb], Friederike Dündar [ctb]

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SingleR/json (API)
NEWS

# Install 'SingleR' in R:
install.packages('SingleR', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/singler-inc/singler/issues

Uses libs:
  • c++– GNU Standard C++ Library v3

On BioConductor:SingleR-2.9.4(bioc 3.21)SingleR-2.8.0(bioc 3.20)

softwaresinglecellgeneexpressiontranscriptomicsclassificationclusteringannotationbioconductorsinglercpp

12.60 score 182 stars 1 packages 2.1k scripts 6.2k downloads 97 mentions 25 exports 43 dependencies

Last updated 7 days agofrom:96c5041530. Checks:11 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 17 2025
R-4.5-win-x86_64OKFeb 17 2025
R-4.5-mac-x86_64OKFeb 17 2025
R-4.5-mac-aarch64OKFeb 17 2025
R-4.5-linux-x86_64OKFeb 17 2025
R-4.4-win-x86_64OKFeb 17 2025
R-4.4-mac-x86_64OKFeb 17 2025
R-4.4-mac-aarch64OKFeb 17 2025
R-4.3-win-x86_64OKFeb 17 2025
R-4.3-mac-x86_64OKFeb 17 2025
R-4.3-mac-aarch64OKFeb 17 2025

Exports:.mockRefData.mockTestDataaggregateReferenceBlueprintEncodeDataclassifySingleRcombineCommonResultscombineRecomputedResultsconfigureMarkerHeatmapDatabaseImmuneCellExpressionDatagetClassicMarkersgetDeltaFromMedianHumanPrimaryCellAtlasDataImmGenDatamatchReferencesMonacoImmuneDataMouseRNAseqDataNovershternHematopoieticDataplotDeltaDistributionplotMarkerHeatmapplotScoreDistributionplotScoreHeatmappruneScoresrebuildIndexSingleRtrainSingleR

Dependencies:abindaskpassassortheadbeachmatBHBiobaseBiocGenericsBiocNeighborsBiocParallelcodetoolscpp11crayoncurlDelayedArrayDelayedMatrixStatsformatRfutile.loggerfutile.optionsgenericsGenomeInfoDbGenomeInfoDbDataGenomicRangeshttrIRangesjsonlitelambda.rlatticeMatrixMatrixGenericsmatrixStatsmimeopensslR6RcppS4ArraysS4VectorssnowSparseArraysparseMatrixStatsSummarizedExperimentsysUCSC.utilsXVector

Using SingleR to annotate single-cell RNA-seq data

Rendered fromSingleR.Rmdusingknitr::rmarkdownon Feb 17 2025.

Last update: 2024-12-11
Started: 2019-07-12

Readme and manuals

Help Manual

Help pageTopics
Mock data for examples.mockRefData .mockTestData
Aggregate reference samplesaggregateReference
Classify cells with SingleRclassifySingleR
Combine SingleR results with recomputationcombineCommonResults combineRecomputedResults
Reference dataset extractorsBlueprintEncodeData DatabaseImmuneCellExpressionData datasets HumanPrimaryCellAtlasData ImmGenData MonacoImmuneData MouseRNAseqData NovershternHematopoieticData
Get classic markersgetClassicMarkers
Compute the difference from mediangetDeltaFromMedian
Match labels from two referencesmatchReferences
Plot delta distributionsplotDeltaDistribution
Plot a heatmap of the markers for a labelconfigureMarkerHeatmap plotMarkerHeatmap
Plot score distributionsplotScoreDistribution
Plot a score heatmapplotScoreHeatmap
Prune out low-quality assignmentspruneScores
Rebuild the indexrebuildIndex
Annotate scRNA-seq dataSingleR
Train the SingleR classifiertrainSingleR