This package is for version 3.15 of Bioconductor; for the stable, up-to-date release version, see UCell.
Bioconductor version: 3.15
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 "4.2") and enter:
if (!require("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install("UCell")
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:
browseVignettes("UCell")
HTML | R Script | Gene signature scoring with UCell |
Reference Manual | ||
Text | NEWS | |
Text | LICENSE |
biocViews | CellBasedAssays, GeneExpression, GeneSetEnrichment, SingleCell, Software, Transcriptomics |
Version | 2.0.1 |
In Bioconductor since | BioC 3.15 (R-4.2) (0.5 years) |
License | GPL-3 + file LICENSE |
Depends | R (>= 4.1.0) |
Imports | methods, data.table (>= 1.13.6), Matrix, BiocParallel, SingleCellExperiment, SummarizedExperiment |
LinkingTo | |
Suggests | Seurat, scater, scRNAseq, reshape2, patchwork, ggplot2, BiocStyle, knitr, rmarkdown |
SystemRequirements | |
Enhances | |
URL | https://github.com/carmonalab/UCell |
BugReports | https://github.com/carmonalab/UCell/issues |
Depends On Me | |
Imports Me | escape |
Suggests Me | |
Links To Me | |
Build Report |
Follow Installation instructions to use this package in your R session.
Source Package | UCell_2.0.1.tar.gz |
Windows Binary | UCell_2.0.1.zip |
macOS Binary (x86_64) | UCell_2.0.1.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/UCell |
Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/UCell |
Package Short Url | https://bioconductor.org/packages/UCell/ |
Package Downloads Report | Download Stats |
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