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This is the development version of SingleR; for the stable release version, see SingleR.

Reference-Based Single-Cell RNA-Seq Annotation

Bioconductor version: Development (3.20)

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.

Author: Dvir Aran [aut, cph], Aaron Lun [ctb, cre], Daniel Bunis [ctb], Jared Andrews [ctb], Friederike D√ľndar [ctb]

Maintainer: Aaron Lun <infinite.monkeys.with.keyboards at>

Citation (from within R, enter citation("SingleR")):


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if (!require("BiocManager", quietly = TRUE))

# The following initializes usage of Bioc devel


For older versions of R, please refer to the appropriate Bioconductor release.


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Annotating scRNA-seq data HTML R Script
Reference Manual PDF


biocViews Annotation, Classification, Clustering, GeneExpression, SingleCell, Software, Transcriptomics
Version 2.7.1
In Bioconductor since BioC 3.10 (R-3.6) (4.5 years)
License GPL-3 + file LICENSE
Depends SummarizedExperiment
Imports methods, Matrix, S4Vectors, DelayedArray, DelayedMatrixStats, BiocParallel, BiocSingular, stats, utils, Rcpp, beachmat(>= 2.21.1), parallel
System Requirements C++17
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Suggests testthat, knitr, rmarkdown, BiocStyle, BiocGenerics, SingleCellExperiment, scuttle, scater, scran, scRNAseq, ggplot2, pheatmap, grDevices, gridExtra, viridis, celldex
Linking To Rcpp, beachmat, BiocNeighbors
Depends On Me OSCA.advanced, OSCA.basic, OSCA.multisample, OSCA.workflows
Imports Me singleCellTK
Suggests Me sketchR, tidySingleCellExperiment, tidyseurat
Links To Me
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Source Package SingleR_2.7.1.tar.gz
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macOS Binary (x86_64) SingleR_2.7.1.tgz
macOS Binary (arm64) SingleR_2.7.1.tgz
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