CellMentor
Bioc currentSupervised Non-negative Matrix Factorization for Dimensional Reduction in Single-Cell Analysis
Release Lineage
Entered 3.23 · Apr 29, 2026
Current · Requires R 4.6
Description
Implements supervised cell type-aware non-negative matrix factorization (NMF) for dimensional reduction in single-cell RNA sequencing analysis. The package provides methods for incorporating cell type information into the dimensionality reduction process, enabling improved visualization and downstream analysis of single-cell data while preserving biological structure. CellMentor employs a unique loss function that simultaneously minimizes variation within known cell populations while maximizing distinctions between different cell types, enabling effective transfer of learned patterns from labeled reference datasets to new unlabeled data.
None published for Bioconductor
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
79 13 exported
Complexity
2.5 avg / 9 max
Call network
79 nodes / 59 edges
Test coverage is not measured for Bioconductor packages; nodes fall back to a neutral fill.
Call graph
Open call graph →Lowest coverage
Per-function coverage is not measured for this package yet.
Code
Structure
Lines of code
5,411
Files
57
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
13
Internal functions
64
Recent export changes
Testing
Has tests
Yes
Test-to-code ratio
0.22
testthat edition
3
Docs
Roxygen coverage
100%
Health & Security signals
Informational signals; not verdicts.
on.exit coverage
–
Unsafe pattern score
0
Dep constraint coverage
4%
Secret pattern count
0
Bundled 3rd-party code
2 items
Portability & License
Min R version
4.5.0
System requirements
–
C++ standard
–
License
Apache License (>= 2)
License flags
SPDX valid, OSI approved
History
Versions
1
First release
2026-05-25
Latest release
2026-05-25
Avg cadence
–
Cold removal rate
–
Dep drift
0
Per-file churn detail lives in the source pipeline: https://github.com/r-observatory/bioc-code-metrics.
Documentation
- Help pages
- 15 (1 internal)includes a package overview page
- Examples that run
- 86%12 run in a plain check · 1 only when donttest examples are enabled (R CMD check --as-cran) · 1 never run
- Exported functions with examples
- 92%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 7%
Bug fixes
calculate_performance()now passesas.factor(true_labels)andas.factor(clusters)toaricode::NMI(). As ofaricode1.1.0,NMI()routes mixed-type inputs throughsort_pairs(), which callsas.integer()on character labels — turning cell-type names such as"alpha"intoNAand aborting with"NA are not supported.". Coercing both sides to factor keeps the computation well-defined. Backport of the fix shipped in 1.1.2 on the devel branch.
From NEWS.md in the release
Repository practices
1 development-tooling and community-health practice detected across 1 family in the upstream repository
Checks run against github.com/petrenkokate/cellmentor on 2026-10-11.
Datasets
| Name | Class | Size | Also in |
|---|---|---|---|
| obj_toy | – | – | – |
| qry_matrix_toy | matrix | 50 × 8 | No other package |
| ref_celltype_toy | vector | 12 elements | No other package |
| ref_matrix_toy | matrix | 50 × 12 | No other package |
Topics
People
- Ekaterina Petrenko author maintainer
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("CellMentor")This package has no citation file, so citation() returns this entry built from DESCRIPTION.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-18, which the citation names so these numbers can be found later. More on citing and the projects behind them.