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ClustAssess
View on CRAN: Click
here
Download and install ClustAssess package within the R console
Install from CRAN:
install.packages("ClustAssess")
Install from Github:
library("remotes")
install_github("cran/ClustAssess") Install by package version:
library("remotes")
install_version("ClustAssess", "1.1.0") Attach the package and use:
library("ClustAssess")
Maintained by
Arash Shahsavari
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-03-31
Latest Update: 2025-05-27
Description:
A set of tools for evaluating clustering robustness using
proportion of ambiguously clustered pairs (Senbabaoglu et al. (2014)
), as well as similarity across methods
and method stability using element-centric clustering comparison (Gates et
al. (2019) ). Additionally, this package
enables stability-based parameter assessment for graph-based clustering
pipelines typical in single-cell data analysis.
How to cite:
Arash Shahsavari (2021). ClustAssess: Tools for Assessing Clustering. R package version 1.1.0, https://cran.r-project.org/web/packages/ClustAssess. Accessed 26 Aug. 2026.
Previous versions and publish date:
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Other R packages that ClustAssess depends,
imports, suggests or enhances
Complete documentation for ClustAssess
Functions, R codes and Examples using
the ClustAssess R package
Some associated functions: Clustering-class . consensus_cluster . create_clustering . element_agreement . element_consistency . element_sim . element_sim_elscore . element_sim_matrix . get_clustering_difference . get_feature_stability . get_nn_conn_comps . get_nn_importance . get_resolution_importance . length-Clustering-method . marker_overlap . merge_partitions . merge_resolutions . pac_convergence . pac_landscape . pipe . plot_clustering_difference_boxplot . plot_clustering_difference_facet . plot_connected_comps_evolution . plot_feature_stability_boxplot . plot_feature_stability_ecs_facet . plot_feature_stability_ecs_incremental . plot_feature_stability_mb_facet . plot_k_n_partitions . plot_k_resolution_corresp . plot_n_neigh_ecs . plot_n_neigh_k_correspondence . print-Clustering-method .
Some associated R codes: ECS.R . PAC.R . RcppExports.R . marker-overlap.R . stability-based-parameter-assessment.R . utils-pipe.R . Full ClustAssess package functions and examples
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