Visualise Clusterings at Different Resolutions R package clustree version 0.5.1 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. Software 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 Luke Zappia <luke@lazappi.id.au> Comprehensive R Archive Network (CRAN) Luke Zappia [aut, cre] (ORCID: <https://orcid.org/0000-0001-7744-8565>), Alicia Oshlack [aut] (ORCID: <https://orcid.org/0000-0001-9788-5690>), Andrea Rau [ctb], Paul Hoffman [ctb] (ORCID: <https://orcid.org/0000-0002-7693-8957>) GPL-3 2023-11-05 application/tgz https://CRAN.R-project.org/package=clustree doi:10.32614/CRAN.package.clustree en-GB