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SVMDO

Bioc current

Identification of Tumor-Discriminating mRNA Signatures via Support Vector Machines Supported by Disease Ontology

v1.11.0 · software · GPL-3

Release Lineage

Entered 3.17 · Apr 26, 2023

Current · Requires R 4.6

1.0 In 7 of 49 releases 3.23

Description

It is an easy-to-use GUI using disease information for detecting tumor/normal sample discriminating gene sets from differentially expressed genes. Our approach is based on an iterative algorithm filtering genes with disease ontology enrichment analysis and wilk and wilks lambda criterion connected to SVM classification model construction. Along with gene set extraction, SVMDO also provides individual prognostic marker detection. The algorithm is designed for FPKM and RPKM normalized RNA-Seq transcriptome datasets.

Test coverage

Line coverage

Expression

Tests / Examples

Functions

42 1 exported

Complexity

2.6 avg / 15 max

Call network

42 nodes / 20 edges

Test coverage is not measured for Bioconductor packages; nodes fall back to a neutral fill.

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Lowest coverage

Per-function coverage is not measured for this package yet.

Code

Structure

Lines of code

3,310

Files

102

Compiled share

0%

Has compiled src

No

Language breakdown

R 1,633 (49.3%)Tests 561 (16.9%)Docs 792 (23.9%)Vignettes 324 (9.8%)

API

Exported functions

1

Internal functions

41

Testing & CI

Has tests

Yes

Test-to-code ratio

0.34

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

0%

Unsafe pattern score

0

Dep constraint coverage

82.6%

Secret pattern count

0

Bundled 3rd-party code

2 items

Portability & License

Min R version

4.4

System requirements

C++ standard

License

GPL-3

License flags

SPDX valid, OSI approved

History

Versions

7

First release

2023-04-25

Latest release

2026-04-28

Avg cadence

189 days

Cold removal rate

Dep drift

1

LOC over versions

v3.17: 3,451 LOCv3.18: 3,405 LOCv3.19: 3,309 LOCv3.20: 3,310 LOCv3.21: 3,310 LOCv3.22: 3,310 LOCv3.23: 3,310 LOC

Per-file churn detail lives in the source pipeline: https://github.com/r-observatory/bioc-code-metrics.

Documentation

Documentation
READMEYes · 245 wordsVignettesYes · dynamicpkgdown siteNoNEWSYes · 67% structuredCode of conductNoContributing guideNo
Examples that run
100%
Documented parameters
100%
Return-value docs
100%
References docs
0%

Topics

People

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("SVMDO")
Ozer, M. E., Arga, K. Y., & Ozbek Sarica, P. (2026). SVMDO: Identification of Tumor-Discriminating mRNA Signatures via Support Vector Machines Supported by Disease Ontology (Version 1.11.0) [Computer software]. https://bioconductor.org/packages/SVMDO

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.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for SVMDO version 1.11.0 [Data set]. HJJB, LLC. Data release v2026-08-22. https://doi.org/10.5281/zenodo.21843040

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.

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