Visualise Clusterings at Different Resolutions (original) (raw)

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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.

Installation

You can install the release version of clustree from CRAN with:

If you want to use the development version that can be installed from GitHub using the remotes package:

# install.packages("remotes")
remotes::install_github("lazappi/clustree@develop")

To also build the vignettes use:

# install.packages("remotes")
remotes::install_github("lazappi/clustree@develop", dependencies = TRUE,
                         build_vignettes = TRUE)

NOTE: Building the vignettes requires the installation of additional packages.

Citing clustree

If you use clustree or the clustering trees approach in your work please cite our publication “Zappia L, Oshlack A. Clustering trees: a visualization for evaluating clusterings at multiple resolutions. Gigascience. 2018;7. DOI:gigascience/giy083.

citation("clustree")
 
   Zappia L, Oshlack A. Clustering trees: a visualization for
   evaluating clusterings at multiple resolutions. GigaScience.
   2018;7. DOI:gigascience/giy083
 
A BibTeX entry for LaTeX users is
 
   @Article{,
     author = {Luke Zappia and Alicia Oshlack},
     title = {Clustering trees: a visualization for evaluating clusterings at
              multiple resolutions},
     journal = {GigaScience},
     volume = {7},
     number = {7},
     month = {jul},
     year = {2018},
     url = {http://dx.doi.org/10.1093/gigascience/giy083},
     doi = {10.1093/gigascience/giy083},
   }

Contributors

Thank you to everyone who has contributed code to the clustree package: