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Rank-based signature enrichment analysis for single-cell data

Bioconductor version: Release (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>

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


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

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


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 2.8.0
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
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Suggests scater, scRNAseq, reshape2, patchwork, ggplot2, BiocStyle, Seurat (>= 5.0.0), SeuratObject (>= 5.0.0), knitr, rmarkdown
Linking To
Depends On Me
Imports Me escape, scGate
Suggests Me SCpubr
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Follow Installation instructions to use this package in your R session.

Source Package UCell_2.8.0.tar.gz
Windows Binary
macOS Binary (x86_64) UCell_2.8.0.tgz
macOS Binary (arm64) UCell_2.8.0.tgz
Source Repository git clone
Source Repository (Developer Access) git clone
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