GSABenchmark

Tools for benchmarking single-cell gene set analysis methods

Bioconductor version: 3.24 · Package version: 1.1.2

GSABenchmark is a package designed for benchmarking scRNA-seq gene set analysis (scGSA) methods. It provides both traditional and novel benchmark metrics, as well as visualization tools. Currently, GSABenchmark supports 17 scGSA methods (AddModuleScore, AUCell, CSOA, GSVA, JASMINE, MDT, MLM, ORA, Pagoda2, PLAGE, Singscore, SiPSiC, ssGSEA, UCell, UDT, VAM, and Zscore).

Installation

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

BiocManager::install("GSABenchmark")

Details

Maintainer	Andrei-Florian Stoica <andreistoica@foxmail.com>
Author	Andrei-Florian Stoica [aut, cre] (ORCID: <https://orcid.org/0000-0002-5253-0826>)
License	MIT + file LICENSE
URL	https://github.com/andrei-stoica26/GSABenchmark
Bug Reports	https://github.com/andrei-stoica26/GSABenchmark/issues
Downloads rank	183
Source branch	devel
biocViews	GeneExpression, GeneSetEnrichment, SingleCell, Software, Visualization

Documentation

Introduction to GSABenchmark

Dependencies

Imports: abdiv, CSOA, decoupleR, dplyr, escape, fabR, ggplot2, ggrepel, GSVA, hammers, henna, jaccard, lsa, Matrix, MLmetrics, methods, mltools, pagoda2, paletteer, reshape2, rlang, scLang, singscore, SiPSiC, stringr, stats, VAM, withr

Suggests: AUCell, BiocStyle, knitr, qs2, ranger, rmarkdown, rpart, scater, scRNAseq, scuttle, Seurat, testthat (>= 3.0.0), UCell