Package: scAnnotatR
Type: Package
Title: Pretrained learning models for cell type prediction on single
        cell RNA-sequencing data
Version: 1.19.0
Authors@R: 
    c(person("Vy", "Nguyen", email = "thi-tuong-vy.nguyen@meduniwien.ac.at", 
      role = c("aut"), comment = c(ORCID = "0000-0003-3436-3662")),
      person("Johannes", "Griss", email = "johannes.griss@meduniwien.ac.at", 
      role = c("cre"), comment = c(ORCID = "0000-0003-2206-9511")))
Description: The package comprises a set of pretrained machine learning
        models to predict basic immune cell types. This enables all
        users to quickly get a first annotation of the cell types
        present in their dataset without requiring prior knowledge.
        scAnnotatR also allows users to train their own models to
        predict new cell types based on specific research needs.
License: MIT + file LICENSE
Encoding: UTF-8
biocViews: SingleCell, Transcriptomics, GeneExpression,
        SupportVectorMachine, Classification, Software
Imports: dplyr, ggplot2, caret, ROCR, pROC, data.tree, methods, stats,
        e1071, ape, kernlab, AnnotationHub, utils
Suggests: knitr, rmarkdown, scRNAseq, testthat
VignetteBuilder: knitr
Depends: R (>= 4.1), Seurat, SingleCellExperiment, SummarizedExperiment
LazyData: true
RoxygenNote: 7.3.3
URL: https://github.com/grisslab/scAnnotatR
BugReports: https://github.com/grisslab/scAnnotatR/issues/new
Config/pak/sysreqs: cmake libglpk-dev make libicu-dev libpng-dev
        libuv1-dev libxml2-dev libssl-dev python3 zlib1g-dev
Repository: https://bioc.r-universe.dev
Date/Publication: 2026-04-28 12:56:50 UTC
RemoteUrl: https://github.com/bioc/scAnnotatR
RemoteRef: HEAD
RemoteSha: d98cd9e80ae4e942cfef3c1e5ca3a03ceaa28b5e
NeedsCompilation: no
Packaged: 2026-07-04 00:18:15 UTC; root
Author: Vy Nguyen [aut] (ORCID: <https://orcid.org/0000-0003-3436-3662>),
  Johannes Griss [cre] (ORCID: <https://orcid.org/0000-0003-2206-9511>)
Maintainer: Johannes Griss <johannes.griss@meduniwien.ac.at>