rScudo
Bioc currentSignature-based Clustering for Diagnostic Purposes
Release Lineage
Entered 3.9 · May 3, 2019
Current · Requires R 4.6
Description
SCUDO (Signature-based Clustering for Diagnostic Purposes) is a rank-based method for the analysis of gene expression profiles for diagnostic and classification purposes. It is based on the identification of sample-specific gene signatures composed of the most up- and down-regulated genes for that sample. Starting from gene expression data, functions in this package identify sample-specific gene signatures and use them to build a graph of samples. In this graph samples are joined by edges if they have a similar expression profile, according to a pre-computed similarity matrix. The similarity between the expression profiles of two samples is computed using a method similar to GSEA. The graph of samples can then be used to perform community clustering or to perform supervised classification of samples in a testing set.
None published for Bioconductor
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
32 6 exported
Complexity
3.7 avg / 11 max
Call network
32 nodes / 36 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
4,471
Files
37
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
16
Internal functions
26
Recent export changes
Testing
Has tests
Yes
Test-to-code ratio
0.63
testthat edition
–
Docs
Roxygen coverage
100%
Health & Security signals
Informational signals; not verdicts.
on.exit coverage
–
Unsafe pattern score
0
Dep constraint coverage
0%
Secret pattern count
0
Bundled 3rd-party code
2 items
Portability & License
Min R version
3.6
System requirements
–
C++ standard
–
License
GPL-3
License flags
SPDX valid, OSI approved
History
Versions
15
First release
2019-05-02
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
- 9includes a package overview page
- Examples that run
- 100%9 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 90%
- Return-value docs
- 88%
- Help pages citing references
- 0%
Repository practices
1 development-tooling and community-health practice detected across 1 family in the upstream repository
Checks run against github.com/matteo-ciciani/scudo on 2026-10-21.
Topics
People
- Matteo Ciciani author maintainer
- Thomas Cantore author
- Enrica Colasurdo contributor
- Mario Lauria contributor
Cite
Cite this package
Run in R for the authors' entry:
citation("rScudo")The package provides a citation file, so citation() returns the authors' own entry.
It points to 10.1093/bioinformatics/btaa296.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-25, which the citation names so these numbers can be found later. More on citing and the projects behind them.