scGOclust: Measuring Cell Type Similarity with Gene Ontology in Single-Cell RNA-Seq

Traditional methods for analyzing single cell RNA-seq datasets focus solely on gene expression, but this package introduces a novel approach that goes beyond this limitation. Using Gene Ontology terms as features, the package allows for the functional profile of cell populations, and comparison within and between datasets from the same or different species. Our approach enables the discovery of previously unrecognized functional similarities and differences between cell types and has demonstrated success in identifying cell types' functional correspondence even between evolutionarily distant species.

Version: 0.2.1
Depends: R (≥ 2.10)
Imports: limma, Seurat (≥ 5.0.0), biomaRt, dplyr, magrittr, stats, tibble, tidyr, Matrix, utils, networkD3, slanter
Suggests: knitr, devtools, pheatmap, rmarkdown, httr
Published: 2024-01-24
DOI: 10.32614/CRAN.package.scGOclust
Author: Yuyao Song [aut, cre, ctb], Irene Papatheodorou [aut, ths]
Maintainer: Yuyao Song <ysong at>
License: GPL (≥ 3)
NeedsCompilation: no
Materials: README
CRAN checks: scGOclust results


Reference manual: scGOclust.pdf
Vignettes: scGOclust_vignette


Package source: scGOclust_0.2.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): scGOclust_0.2.1.tgz, r-oldrel (arm64): scGOclust_0.2.1.tgz, r-release (x86_64): scGOclust_0.2.1.tgz, r-oldrel (x86_64): scGOclust_0.2.1.tgz
Old sources: scGOclust archive


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