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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 |
| DOI: |
10.32614/CRAN.package.clustree |
| Author: |
Luke Zappia  [aut,
cre],
Alicia Oshlack
[aut],
Andrea Rau [ctb],
Paul Hoffman
[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:
Downloads:
Reverse dependencies:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=clustree
to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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