Package: immunoClust
Type: Package
Title: immunoClust - Automated Pipeline for Population Detection in
        Flow Cytometry
Version: 1.42.0
Date: 2025-09-18
Authors@R: person("Till", "Soerensen", email="till.soerensen@bioretis.com",
                    role=c("aut", "cre"))
Maintainer: Till Soerensen <till.soerensen@bioretis.com>
Depends: R(>= 4.2), flowCore
Imports: methods, stats, graphics, grid, lattice, grDevices
Suggests: BiocStyle, utils, testthat
Description: immunoClust is a model based clustering approach for Flow Cytometry
    samples. The cell-events of single Flow Cytometry samples are modelled by a
    mixture of multinominal normal- or t-distributions. The cell-event clusters
    of several samples are modelled by a mixture of multinominal
    normal-distributions aiming stable co-clusters across these samples.
Collate: generics.R class.immunoClust.R plot.immunoClust.R
        splom.immunoClust.R methods.immunoClust.R class.immunoMeta.R
        plot.immunoMeta.R methods.immunoMeta.R data.R process.R
        cell.clustering.R meta.clustering.R meta.annotation.R
        meta.SON.R meta.export.R clust.util.R transform.R
biocViews: Clustering, FlowCytometry, SingleCell, CellBasedAssays,
        ImmunoOncology
License: Artistic-2.0
git_url: https://git.bioconductor.org/packages/immunoClust
git_branch: RELEASE_3_22
git_last_commit: 3c4237c
git_last_commit_date: 2025-10-29
Repository: Bioconductor 3.22
Date/Publication: 2025-10-29
NeedsCompilation: yes
Packaged: 2025-10-30 03:09:17 UTC; biocbuild
Author: Till Soerensen [aut, cre]
Built: R 4.5.1; aarch64-apple-darwin20; 2025-10-30 09:28:17 UTC; unix
