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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

MaintainerKeita Iida <kiida@protein.osaka-u.ac.jp>
AuthorKeita Iida [aut, cre] (ORCID: <https://orcid.org/0000-0002-1076-830X>), Johannes Nicolaus Wibisana [ctb]
LicenseGPL-3 + file LICENSE
Downloads rank289
Source branchRELEASE_3_23
biocViewsClustering, GeneExpression, GeneSignaling, Sequencing, SingleCell, Software

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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)