AUCell

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

AUCell: Analysis of 'gene set' activity in single-cell RNA-seq data (e.g. identify cells with specific gene signatures)

Platform availability badge Ranking badge Support activity badge Years in BioConductor badge Build results badge Last commit badge Dependency count badge

DOI: 10.18129/B9.bioc.AUCell

Bioconductor version: Development (3.23)

AUCell allows to identify cells with active gene sets (e.g. signatures, gene modules...) in single-cell RNA-seq data. AUCell uses the "Area Under the Curve" (AUC) to calculate whether a critical subset of the input gene set is enriched within the expressed genes for each cell. The distribution of AUC scores across all the cells allows exploring the relative expression of the signature. Since the scoring method is ranking-based, AUCell is independent of the gene expression units and the normalization procedure. In addition, since the cells are evaluated individually, it can easily be applied to bigger datasets, subsetting the expression matrix if needed.

Author: Sara Aibar, Stein Aerts. Laboratory of Computational Biology. VIB-KU Leuven Center for Brain & Disease Research. Leuven, Belgium.

Maintainer: Gert Hulselmans <Gert.Hulselmans at kuleuven.be>

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

Installation

To install this package, start R (version "4.6") and enter:


if (!require("BiocManager", quietly = TRUE))
 install.packages("BiocManager")
# The following initializes usage of Bioc devel
BiocManager::install(version='devel')
BiocManager::install("AUCell")

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