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: | 0.1.2 |
Depends: | R (≥ 3.4), ggraph |
Imports: | checkmate, igraph, dplyr, grid, ggplot2, viridis, methods, rlang |
Suggests: | testthat, knitr, rmarkdown, SingleCellExperiment, Seurat, covr |
Published: | 2018-04-20 |
Author: | Luke Zappia |
Maintainer: | Luke Zappia <luke.zappia at mcri.edu.au> |
BugReports: | https://github.com/lazappi/clustree/issues |
License: | MIT + file LICENSE |
URL: | https://github.com/lazappi/clustree |
NeedsCompilation: | no |
Citation: | clustree citation info |
Materials: | README NEWS |
CRAN checks: | clustree results |
Reference manual: | clustree.pdf |
Vignettes: |
Plotting clustering trees |
Package source: | clustree_0.1.2.tar.gz |
Windows binaries: | r-devel: clustree_0.1.2.zip, r-release: clustree_0.1.2.zip, r-oldrel: clustree_0.1.2.zip |
OS X binaries: | r-release: clustree_0.1.2.tgz, r-oldrel: not available |
Old sources: | clustree archive |
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