adverSCarial
Bioc currentadverSCarial, generate and analyze the vulnerability of scRNA-seq classifier to adversarial attacks
Release Lineage
Entered 3.18 · Oct 25, 2023
Current · Requires R 4.6
Description
adverSCarial is an R Package designed for generating and analyzing the vulnerability of scRNA-seq classifiers to adversarial attacks. The package is versatile and provides a format for integrating any type of classifier. It offers functions for studying and generating two types of attacks, single gene attack and max change attack. The single-gene attack involves making a small modification to the input to alter the classification. The max-change attack involves making a large modification to the input without changing its classification. The CGD attack is based on an estimated gradient descent. against adversarial attacks. The package provides a comprehensive solution for evaluating the robustness of scRNA-seq classifiers against adversarial attacks.
None published for Bioconductor
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
37 14 exported
Complexity
12.4 avg / 50 max
Call network
37 nodes / 39 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
5,546
Files
46
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
16
Internal functions
23
Recent export changes
Testing
Has tests
Yes
Test-to-code ratio
0.00
testthat edition
–
Docs
Roxygen coverage
93.8%
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
MIT + file LICENSE
License flags
SPDX valid, OSI approved
History
Versions
6
First release
2023-10-24
Latest release
2026-04-28
Avg cadence
182 days
Cold removal rate
–
Dep drift
0
LOC over versions
Per-file churn detail lives in the source pipeline: https://github.com/r-observatory/bioc-code-metrics.
Documentation
- Help pages
- 15
- Examples that run
- 100%15 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 94%
- Return-value docs
- 93%
- Help pages citing references
- 0%
Repository practices
Checks read the Bioconductor git repository (git.bioconductor.org), branch RELEASE_3_23.
No development-tooling practices detected in the Bioconductor git repository.
Datasets
| Name | Class | Size | Also in |
|---|---|---|---|
| pbmc3k_cell_types | data.frame | 2,700 × 2 | No other package |
Topics
People
- Ghislain FIEVET author maintainer
- Sébastien HERGALANT author
Cite
Cite this package
Run in R for the authors' entry:
citation("adverSCarial")The package provides a citation file, so citation() returns the authors' own entry.
It points to 10.1093/bioinformatics/btaf168.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-24, which the citation names so these numbers can be found later. More on citing and the projects behind them.