AUCell
Bioc currentAUCell: Analysis of 'gene set' activity in single-cell RNA-seq data (e.g. identify cells with specific gene signatures)
Release Lineage
Entered 3.6 · Oct 31, 2017
Current · Requires R 4.6
Description
AUCell allows to identify cells with active gene sets (e.g. signatures, gene modules...) in single-cell RNA-seq data. AUCell uses the "Area Under the Curve" (AUC) to calculate whether a critical subset of the input gene set is enriched within the expressed genes for each cell. The distribution of AUC scores across all the cells allows exploring the relative expression of the signature. Since the scoring method is ranking-based, AUCell is independent of the gene expression units and the normalization procedure. In addition, since the cells are evaluated individually, it can easily be applied to bigger datasets, subsetting the expression matrix if needed.
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
26 12 exported
Complexity
8.1 avg / 48 max
Call network
26 nodes / 13 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
4,584
Files
61
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
21
Internal functions
14
Recent export changes
Testing & CI
Has tests
Yes
Test-to-code ratio
0.15
testthat edition
–
CI present
No
CI type
[]
PR gated
No
Docs
Roxygen coverage
100%
Health & Security signals
Informational signals; not verdicts.
on.exit coverage
0%
Unsafe pattern score
0
Dep constraint coverage
0%
Secret pattern count
0
Bundled 3rd-party code
2 items
Portability & License
Min R version
–
System requirements
–
C++ standard
–
License
GPL-3
License flags
SPDX valid, OSI approved
History
Versions
18
First release
2017-10-30
Latest release
2026-04-28
Avg cadence
182 days
Cold removal rate
100%
Dep drift
9
LOC over versions
Per-file churn detail lives in the source pipeline: https://github.com/r-observatory/bioc-code-metrics.
Documentation
- Examples that run
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- References docs
- 0%
Topics
Depended on by (11)
Bioconductor (11)
People
Gert Hulselmans
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("AUCell")Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
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