Package: ASURAT
Type: Package
Title: Functional annotation-driven unsupervised clustering for
        single-cell data
Version: 1.17.0
Authors@R: c(person("Keita", "Iida", email = "kiida@protein.osaka-u.ac.jp",
             role = c("aut", "cre"),
             comment = c(ORCID = "0000-0002-1076-830X")),
             person("Johannes Nicolaus", "Wibisana",
                    email = "nico@protein.osaka-u.ac.jp", role = c("ctb")))
Description: 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).
License: GPL-3 + file LICENSE
biocViews: GeneExpression, SingleCell, Sequencing, Clustering,
        GeneSignaling
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: TRUE
Depends: R (>= 4.0.0)
Imports: SingleCellExperiment, SummarizedExperiment, S4Vectors, Rcpp
        (>= 1.0.7), cluster, utils, plot3D, ComplexHeatmap, circlize,
        grid, grDevices, graphics
Suggests: ggplot2, TENxPBMCData, dplyr, Rtsne, Seurat, AnnotationDbi,
        BiocGenerics, stringr, org.Hs.eg.db, knitr, rmarkdown, testthat
        (>= 3.0.0)
RoxygenNote: 7.1.2
LinkingTo: Rcpp
Config/testthat/edition: 3
Config/pak/sysreqs: libpng-dev perl zlib1g-dev
Repository: https://bioc.r-universe.dev
Date/Publication: 2026-04-28 12:58:02 UTC
RemoteUrl: https://github.com/bioc/ASURAT
RemoteRef: HEAD
RemoteSha: 35fd355722f703060e021e979ae800c6b4cf2dff
NeedsCompilation: yes
Packaged: 2026-06-20 06:24:23 UTC; root
Author: Keita Iida [aut, cre] (ORCID: <https://orcid.org/0000-0002-1076-830X>),
  Johannes Nicolaus Wibisana [ctb]
Maintainer: Keita Iida <kiida@protein.osaka-u.ac.jp>