clustree: Visualise Clusterings at Different Resolutions

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.

Version: 0.5.1
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
Published: 2023-11-05
Author: Luke Zappia ORCID iD [aut, cre], Alicia Oshlack ORCID iD [aut], Andrea Rau [ctb], Paul Hoffman ORCID iD [ctb]
Maintainer: Luke Zappia <luke at lazappi.id.au>
BugReports: https://github.com/lazappi/clustree/issues
License: GPL-3
URL: https://github.com/lazappi/clustree, https://lazappi.github.io/clustree/
NeedsCompilation: no
Language: en-GB
Citation: clustree citation info
Materials: README NEWS
CRAN checks: clustree results

Documentation:

Reference manual: clustree.pdf
Vignettes: Plotting clustering trees

Downloads:

Package source: clustree_0.5.1.tar.gz
Windows binaries: r-devel: clustree_0.5.1.zip, r-release: clustree_0.5.1.zip, r-oldrel: clustree_0.5.1.zip
macOS binaries: r-release (arm64): clustree_0.5.1.tgz, r-oldrel (arm64): clustree_0.5.1.tgz, r-release (x86_64): clustree_0.5.1.tgz
Old sources: clustree archive

Reverse dependencies:

Reverse imports: crosshap, scRNAstat, scTreeViz
Reverse suggests: CIARA, MitoHEAR

Linking:

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