SingleR

Reference-Based Single-Cell RNA-Seq Annotation


Bioconductor version: Release (3.19)

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 Dündar [ctb]

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

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

Installation

To install this package, start R (version "4.4") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("SingleR")

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

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("SingleR")
Annotating scRNA-seq data HTML R Script
Reference Manual PDF
NEWS Text
LICENSE Text

Details

biocViews Annotation, Classification, Clustering, GeneExpression, SingleCell, Software, Transcriptomics
Version 2.6.0
In Bioconductor since BioC 3.10 (R-3.6) (5 years)
License GPL-3 + file LICENSE
Depends SummarizedExperiment
Imports methods, Matrix, S4Vectors, DelayedArray, DelayedMatrixStats, BiocParallel, BiocSingular, stats, utils, Rcpp, beachmat, parallel
System Requirements C++17
URL https://github.com/LTLA/SingleR
Bug Reports https://support.bioconductor.org/
See More
Suggests testthat, knitr, rmarkdown, BiocStyle, BiocGenerics, SingleCellExperiment, scuttle, scater, scran, scRNAseq, ggplot2, pheatmap, grDevices, gridExtra, viridis, celldex
Linking To Rcpp, beachmat, BiocNeighbors
Enhances
Depends On Me OSCA.advanced, OSCA.basic, OSCA.multisample, OSCA.workflows, SingleRBook
Imports Me singleCellTK
Suggests Me sketchR, tidySingleCellExperiment, tidySpatialExperiment, tidyseurat
Links To Me
Build Report Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package SingleR_2.6.0.tar.gz
Windows Binary (x86_64) SingleR_2.6.0.zip
macOS Binary (x86_64) SingleR_2.6.0.tgz
macOS Binary (arm64) SingleR_2.6.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/SingleR
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/SingleR
Bioc Package Browser https://code.bioconductor.org/browse/SingleR/
Package Short Url https://bioconductor.org/packages/SingleR/
Package Downloads Report Download Stats