R Observatory: Metrics for ClustAssess version 1.2.0

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

ClustAssess

1.2.0Package record

Tools for Assessing Clustering

0packages depend

7.8Kdownloads / year

2.8%test coverage

13/13flavors OK

Overview

About

Maintained by Andi MunteanuCRAN page ↗GitHub ↗Website ↗Issues ↗

A set of tools for evaluating clustering robustness using proportion of ambiguously clustered pairs (Senbabaoglu et al. (2014) doi:10.1038/srep06207), as well as 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 stability-based parameter assessment for graph-based clustering pipelines typical in single-cell data analysis.

Changes in 1.2.0

---

Updates

Add subsetting option for the Shiny heatmaps and bubbleplots. The subset is based on already existing metadata columns.
Use leidenbase package for Leiden clustering instead of leiden (aligning with Seurat's changes). Algorithm=6 contains the leidenbase implementation, whereas algorithm=4 and 5 are associated with leiden (for matrix and igraph input objects, respectively).
Minimise redundant calculations of the adjacency matrix in the automatic assessment.
Add function that calculates the nn2 index in parallel.
Add an ordering of the points in the metadata shiny plots based on the order of the input subgroups.
Scale the colour values of gene expression in ShinyApp based on provided cap value.
Control the number of values shown on the continuous UMAP legend.
Add option to download multiple genes in separate UMAP files.
Removes ggtext dependency from the package (used in the shiny gene UMAP plots).

Fixes

Show all changes in 1.2.0Hide the rest of the changes in 1.2.0

Ensure the expression matrix or embedding has row names. If not, set them to "cell_1", "cell_2", etc.
Treat the case when enrichment analysis returns no results.
Sort the group 2 markers for enrichment analysis based on the absolute logfoldchange.
Discard the metadata columns with too many unique values for visualisation in the Shiny app.
When creating a Seurat object, the number of PCs is set to the minimum between 30 and half the number of genes. This is to avoid errors when the number of genes is low.

---

From NEWS.md in the release

Install

R (CRAN)pak (dev)Ubuntu (r2u)Fedora (COPR)openSUSE (OBS)

install.packages("ClustAssess", repos = "https://cloud.r-project.org/")

Installs the current CRAN release. Prebuilt binaries on Windows and macOS.

if (!requireNamespace("pak", quietly = TRUE))
  install.packages("pak", repos = "https://cloud.r-project.org/")
pak::pak("Core-Bioinformatics/ClustAssess")

Development version from Core-Bioinformatics/ClustAssess. Installs pak first if it is not already available.

Release

# enable cranapt (r2u) if it is not already set up, then install
grep -rqs r2u.stat.illinois.edu /etc/apt/sources.list /etc/apt/sources.list.d/ \
  || curl -fsSL https://raw.githubusercontent.com/eddelbuettel/r2u/master/inst/scripts/add_cranapt_noble.sh | sudo bash
sudo apt install -y r-cran-clustassess

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled. We list this channel from recorded r2u download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

bspm (used by r2u) also needs make: sudo apt install make

# enable the iucar/cran COPR if it is not already present, then install
ls /etc/yum.repos.d/*iucar*cran*.repo >/dev/null 2>&1 \
  || sudo dnf copr enable -y iucar/cran
sudo dnf install -y R-CRAN-ClustAssess

RPMs from the iucar/cran COPR, rebuilt from CRAN.

For install.packages() integration in R, also: sudo dnf install R-CoprManager

# add the autoCRAN OBS repo (Tumbleweed) if it is missing, then install
zypper -q lr | grep -qi autoCRAN \
  || sudo zypper addrepo https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/devel:languages:R:autoCRAN.repo
sudo zypper install -y R-ClustAssess

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed). We list this channel from recorded autoCRAN download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

Health

CRAN checks

13OK

CRAN check page ↗

Slowest check: 8.1 min · r-oldrel-windows-x86_64

Status changes

OK13 OK2026-08-05
NOTE12 OK, 1 NOTE2026-08-01
OK13 OK2026-06-09
ERROR12 OK, 1 ERROR2026-06-08
OK12 OK2026-04-25

Show 5 earlier changesHide 5 earlier changes

NOTE11 OK, 3 NOTE2026-04-22
ERROR10 OK, 3 NOTE, 1 ERROR2026-04-18
NOTE11 OK, 3 NOTE2026-04-10
ERROR10 OK, 3 NOTE, 1 ERROR2026-04-09
NOTE11 OK, 3 NOTE2026-03-10

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 1.2.0

READMEYes · 1,341 wordsVignettes· In the repository, left out of the releaseNEWSYes · 100% structured · mentions 1.2.0Citation fileYes · cites a publicationWebsiteYes · pkgdown

Help pages: 64 (4 internal)
Examples that run: 89%32 run in a plain check · 3 never run · 1 hold no code
Exported functions with examples: 61%
Documented parameters: 96%
Return-value docs: 77%
Help pages citing references: 8%

How these are measured

Downloads

7.8K

CRAN downloads in the past year

Rank #6,453 · ~21/day · ~651/mo

Releases R versions

Daily download trend is not available in this view yet.

43830 days

1.3K90 days

7.8K1 year

Compare downloads with other packages →

Also on407 r2u12 autocran2K conda_forge

How downloads are counted

Repository

core-bioinformatics/clustassess ↗Organization: Core-Bioinformatics

34Stars

6Forks

1Open issues

0Open PRs

3Releases

634Commits

4Commit identities

clusteringsingle-cellparameter-optimizationrobustnessgenomicsbioinformaticsmachine-learningunsupervised-learning

634 commits · Last activity 2026-08-29 · 0% stars, 30d

Responsiveness

How these are sampled

PRs merged (all time): 100%
Median days to close, 50 most recently updated closed issues: 271
Median days to close, 50 most recently updated closed PRs: 0

Stars over time

2025-05-22 · 242026-08-27 · 34

How these are measured

PracticesBeta

6 development-tooling and community-health practices detected across 4 families in the upstream repository

Checks run against github.com/core-bioinformatics/clustassess on 2026-10-18.

Continuous integration (1)

GitHub Actions

Docs source (3)

pkgdown

GitHub Pages site last deployed 2026-08-29 · The repository has a site deploy workflow

pkgdown site last built 2026-08-29

CRAN release process (1)

cran-comments.md

Lint, format, editor (1)

RStudio project

How this is detected·Detection ruleset v3 (2026-09-26)

Dependencies

Declared dependencies

53 external dependencies (excludes base and recommended)

Installing ClustAssess adds 169 packages (93 with compiled code, 154 MB of source tarballs). Heaviest: BH 14 MB, stringi 11 MB, ggplot2 6.0 MB.

Depends (3)

R >= 4.0.0methodsstats

LinkingTo (2)

Rcpp RcppEigen

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

0direct

0indirect

Nothing depends on this yet.

How these are counted

Code & Tests

People & History

People (6)

Andi Munteanu

Author, Maintainer since 1.0.0 (2025) · added in 0.3.0

Miguel Larraz Lopez de Novales

Author · added in 1.0.0

Irina Mohorianu

Author

Arash Shahsavari

Author

Liviu Ciortuz

Contributor · added in 1.0.0

Rafael Kollyfas

Contributor · added in 1.0.0

Previously maintained by Arash Shahsavari (0.1.0 to 0.3.0).

Releases (6)

Pick two releases to compare their code metrics.

1.2.0Latest
record
2026-08-29 · current release · diff ↗
R
R 4.6.0 released · 2026-04-24
1.1.0
record
2025-05-28 · diff ↗ ·
added 1 export
plot_clust_hierarchical
R
R 4.5.0 released · 2025-04-11
1.0.0
record
2025-01-31 · diff ↗ ·
removed 9 exports
%>%, get_clustering_difference, get_feature_stability, get_nn_importance, get_resolution_importance, plot_clustering_difference_boxplot, plot_clustering_difference_facet, plot_feature_stability_boxplot, plot_feature_stability_ecs_incremental

added 38 exports
add_metadata, assess_clustering_stability, assess_feature_stability, assess_nn_stability, automatic_stability_assessment, calculate_markers, calculate_markers_shiny, choose_stable_clusters, create_monocle_default, create_monocle_from_clustassess, create_monocle_from_clustassess_app, create_seurat_object_default, create_seurat_object_from_clustassess_app, getNNmatrix, get_clusters_from_clustassess_object, get_highest_prune_param, get_highest_prune_param_embedding, plot_clustering_overall_stability, plot_clustering_per_value_stability, plot_feature_overall_stability_boxplot, plot_feature_overall_stability_incremental, plot_feature_per_resolution_stability_boxplot, plot_feature_per_resolution_stability_incremental, server_comparisons, server_dimensionality_reduction, server_graph_clustering, server_graph_construction, server_landing_page, server_sandbox, ui_comparisons and 8 more
R
R 4.4.0 released · 2024-04-24
R
R 4.3.0 released · 2023-04-21
R
R 4.2.0 released · 2022-04-22
0.3.0
record
2022-01-26 · diff ↗ ·
removed 2 exports
create_clustering, element_frustration

added 18 exports
element_consistency, get_clustering_difference, get_feature_stability, get_nn_conn_comps, get_nn_importance, get_resolution_importance, merge_partitions, 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
R
R 4.1.0 released · 2021-05-18
0.1.1
record
2021-03-31 · diff ↗
0.1.0
record
2021-03-31
R
R 4.0.0 released · 2020-04-24

Package metadata

First published: 2021-03-31
Total releases: 6 / 5 yrs
License: MIT + file LICENSE OSI
Additional repositories: blaserlab.r-universe.dev
Minimum R: ≥ 4.0.0
Download size: 173 KB

Cite

Cite this package

Run in R for the authors' entry:

citation("ClustAssess")

The package provides a citation file, so citation() returns the authors' own entry.

It points to 10.1101/2022.01.31.478592.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

Format

APA

Balamuta, J. J. (2026). R Observatory: Metrics for ClustAssess version 1.2.0 [Data set]. HJJB, LLC. Data release v2026-10-22. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-22, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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