ASURAT
Functional annotation-driven unsupervised clustering for single-cell data
Bioconductor version: 3.23 · Package version: 1.16.0
ASURAT is a software for single-cell data analysis. Using ASURAT, one can simultaneously perform unsupervised clustering and biological interpretation in terms of cell type, disease, biological process, and signaling pathway activity. Inputting a single-cell RNA-seq data and knowledge-based databases, such as Cell Ontology, Gene Ontology, KEGG, etc., ASURAT transforms gene expression tables into original multivariate tables, termed sign-by-sample matrices (SSMs).
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("ASURAT") Details
| Maintainer | Keita Iida <kiida@protein.osaka-u.ac.jp> |
| Author | Keita Iida [aut, cre] (ORCID: <https://orcid.org/0000-0002-1076-830X>), Johannes Nicolaus Wibisana [ctb] |
| License | GPL-3 + file LICENSE |
| Downloads rank | 289 |
| Source branch | RELEASE_3_23 |
| biocViews | Clustering, GeneExpression, GeneSignaling, Sequencing, SingleCell, Software |
Download
Dependencies
Depends: R (>= 4.0.0)
Imports: SingleCellExperiment, SummarizedExperiment, S4Vectors, Rcpp (>= 1.0.7), cluster, utils, plot3D, ComplexHeatmap, circlize, grid, grDevices, graphics
LinkingTo: Rcpp
Suggests: ggplot2, TENxPBMCData, dplyr, Rtsne, Seurat, AnnotationDbi, BiocGenerics, stringr, org.Hs.eg.db, knitr, rmarkdown, testthat (>= 3.0.0)