Package: clustree
Type: Package
Title: Visualise Clusterings at Different Resolutions
Version: 0.4.2
Date: 2020-01-29
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
BugReports: https://github.com/lazappi/clustree/issues
VignetteBuilder: knitr
Depends: R (>= 3.4), ggraph
Imports: checkmate, igraph, dplyr, grid, ggplot2, viridis, methods,
        rlang, tidygraph, ggrepel
Suggests: testthat (>= 2.1.0), knitr, rmarkdown, SingleCellExperiment,
        Seurat (>= 2.3.0), covr, SummarizedExperiment, pkgdown,
        spelling
RoxygenNote: 7.0.2
Language: en-GB
NeedsCompilation: no
Packaged: 2020-01-29 11:25:40 UTC; Luke
Author: Luke Zappia [aut, cre] (<https://orcid.org/0000-0001-7744-8565>),
  Alicia Oshlack [aut] (<https://orcid.org/0000-0001-9788-5690>),
  Andrea Rau [ctb],
  Paul Hoffman [ctb] (<https://orcid.org/0000-0002-7693-8957>)
Repository: CRAN
Date/Publication: 2020-01-29 12:30:02 UTC
Built: R 3.5.3; ; 2020-04-22 09:36:04 UTC; windows
