scTypeEval
Bioc currentEvaluation of cell type classifications in single-cell transcriptomics
Release Lineage
Entered 3.23 · Apr 29, 2026
Current · Requires R 4.6
Description
scTypeEval provides tools to evaluate and validate cell type classifications in single-cell transcriptomics when ground truth labels are limited or unavailable. Results are organized in an S4 object that integrates processed data, dimensional reductions, dissimilarity assays, and consistency metrics computed across samples. The workflow includes preprocessing and feature selection, principal component analysis, computation of dissimilarity matrices, internal validation metrics (for example, silhouette-based summaries), and visualization utilities to inspect heatmaps and PCA plots. Functions support common single-cell containers and enable comparison of clustering and labeling strategies across datasets.
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
81 18 exported
Complexity
3.9 avg / 16 max
Call network
81 nodes / 94 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
12,376
Files
66
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
18
Internal functions
63
Recent export changes
Testing & CI
Has tests
Yes
Test-to-code ratio
1.16
testthat edition
3
CI present
No
CI type
[]
PR gated
No
Docs
Roxygen coverage
100%
Health & Security signals
Informational signals; not verdicts.
on.exit coverage
–
Unsafe pattern score
0
Dep constraint coverage
75%
Secret pattern count
0
Bundled 3rd-party code
2 items
Portability & License
Min R version
4.6.0
System requirements
–
C++ standard
–
License
GPL-3 + file LICENSE
License flags
SPDX valid, OSI approved
History
Versions
1
First release
2026-04-28
Latest release
2026-04-28
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
- Examples that run
- 100%
- Documented parameters
- 99%
- Return-value docs
- 100%
- References docs
- 0%
Topics
People
- Josep Garnica author maintainer
- Massimo Andreatta author
- Santiago Carmona author
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("scTypeEval")This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-08-22, which the citation names so these numbers can be found later. More on citing and the projects behind them.