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

Rank-based signature enrichment analysis for single-cell data

Bioconductor version: Development (3.19)

UCell is a package for evaluating gene signatures in single-cell datasets. UCell signature scores, based on the Mann-Whitney U statistic, are robust to dataset size and heterogeneity, and their calculation demands less computing time and memory than other available methods, enabling the processing of large datasets in a few minutes even on machines with limited computing power. UCell can be applied to any single-cell data matrix, and includes functions to directly interact with SingleCellExperiment and Seurat objects.

Author: Massimo Andreatta [aut, cre] , Santiago Carmona [aut]

Maintainer: Massimo Andreatta <massimo.andreatta at unil.ch>

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


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

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

# The following initializes usage of Bioc devel


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


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

1. Gene signature scoring with UCell HTML R Script
2. Using UCell with SingleCellExperiment HTML R Script
3. Using UCell with Seurat HTML R Script
Reference Manual PDF


biocViews CellBasedAssays, GeneExpression, GeneSetEnrichment, SingleCell, Software, Transcriptomics
Version 2.7.3
In Bioconductor since BioC 3.15 (R-4.2) (2 years)
License GPL-3 + file LICENSE
Depends R (>= 4.3.0)
Imports methods, data.table (>= 1.13.6), Matrix, stats, BiocParallel, BiocNeighbors, SingleCellExperiment, SummarizedExperiment
System Requirements
URL https://github.com/carmonalab/UCell
Bug Reports https://github.com/carmonalab/UCell/issues
See More
Suggests Seurat (>= 5.0.0), scater, scRNAseq, reshape2, patchwork, ggplot2, BiocStyle, knitr, rmarkdown
Linking To
Depends On Me
Imports Me escape
Suggests Me SCpubr
Links To Me
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Package Archives

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

Source Package UCell_2.7.3.tar.gz
Windows Binary UCell_2.7.3.zip
macOS Binary (x86_64) UCell_2.7.3.tgz
macOS Binary (arm64) UCell_2.7.3.tgz
Source Repository git clone https://git.bioconductor.org/packages/UCell
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/UCell
Bioc Package Browser https://code.bioconductor.org/browse/UCell/
Package Short Url https://bioconductor.org/packages/UCell/
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