ClustAssess: Tools for Assessing Clustering

A set of tools for evaluating clustering similarity across methods and method stability using element-centric clustering comparison (Gates et al. (2019) <doi:10.1038/s41598-019-44892-y>). Additionally, this package enables data-wide assessment of clustering robustness using proportion of ambiguously clustered pairs (Senbabaoglu et al. (2014) <doi:10.1038/srep06207>), which can be used to infer the optimal number of clusters in the data.

Version: 0.1.1
Imports: ggplot2, dplyr, fastcluster, rlang, Matrix, igraph, magrittr, Rcpp, methods, stats
LinkingTo: Rcpp
Suggests: knitr, rmarkdown, e1071, dbscan, dendextend, Seurat
Published: 2021-03-31
Author: Arash Shahsavari [aut, cre], Irina Mohorianu [aut]
Maintainer: Arash Shahsavari <as3006 at cam.ac.uk>
License: MIT + file LICENSE
URL: https://github.com/Core-Bioinformatics/ClustAssess
NeedsCompilation: yes
Materials: README
CRAN checks: ClustAssess results

Downloads:

Reference manual: ClustAssess.pdf
Vignettes: Evaluating single-cell clustering with ClustAssess
Comparing soft and hierarchical clusterings with element-centric similarity
Package source: ClustAssess_0.1.1.tar.gz
Windows binaries: r-devel: ClustAssess_0.1.1.zip, r-release: ClustAssess_0.1.1.zip, r-oldrel: not available
macOS binaries: r-release: ClustAssess_0.1.1.tgz, r-oldrel: not available
Old sources: ClustAssess archive

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