DESCRIPTION

Package: clustree
Type: Package
Title: Visualise Clusterings at Different Resolutions
Version: 0.5.1
Date: 2023-11-05
Authors@R:
    c(person("Luke", "Zappia", role = c("aut", "cre"),
             email = "luke@lazappi.id.au",
             comment = c(ORCID = "0000-0001-7744-8565")),
      person("Alicia", "Oshlack", role = c("aut"),
             email = "alicia.oshlack@petermac.org",
             comment = c(ORCID = "0000-0001-9788-5690")),
      person("Andrea", "Rau", role = c("ctb"),
             email = "andrea.rau@inra.fr"),
      person("Paul", "Hoffman", role = c("ctb"),
             email = "phoffman@nygenome.org",
             comment = c(ORCID = "0000-0002-7693-8957")))
Maintainer: Luke Zappia <luke@lazappi.id.au>
Description: Deciding what resolution to use can be a difficult question when
    approaching a clustering analysis. One way to approach this problem is to
    look at how samples move as the number of clusters increases. This package
    allows you to produce clustering trees, a visualisation for interrogating
    clusterings as resolution increases.
License: GPL-3
Encoding: UTF-8
LazyData: true
URL: https://github.com/lazappi/clustree, https://lazappi.github.io/clustree/
BugReports: https://github.com/lazappi/clustree/issues
VignetteBuilder: knitr
Depends: R (>= 3.5),
    ggraph
Imports: checkmate,
    igraph,
    dplyr,
    grid,
    ggplot2 (>= 3.4.0),
    viridis,
    methods,
    rlang,
    tidygraph,
    ggrepel
Suggests: 
    testthat (>= 2.1.0),
    knitr,
    rmarkdown,
    SingleCellExperiment,
    Seurat (>= 2.3.0),
    covr,
    SummarizedExperiment,
    pkgdown,
    spelling
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.2.3
Language: en-GB