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gINTomics

Bioc current

Multi-Omics data integration

v1.8.0 · Package record · software · AGPL-3

Release Lineage

Entered 3.19 · May 1, 2024

Current · Requires R 4.6

1.0 In 5 of 49 releases 3.23

Description

gINTomics is an R package for Multi-Omics data integration and visualization. gINTomics is designed to detect the association between the expression of a target and of its regulators, taking into account also their genomics modifications such as Copy Number Variations (CNV) and methylation. What is more, gINTomics allows integration results visualization via a Shiny-based interactive app.

Advisories

None published for Bioconductor

Test coverage

Line coverage

–

Expression

–

Tests / Examples

–

Functions

154 17 exported

Complexity

3.3 avg / 18 max

Call network

154 nodes / 207 edges

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

Loading call graph…

Lowest coverage

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

Code

Structure

Lines of code

12,107

Files

66

Compiled share

0%

Has compiled src

No

Language breakdown

R 8,721 (72%)Tests 1,998 (16.5%)Docs 1,122 (9.3%)Vignettes 266 (2.2%)

API

Exported functions

18

Internal functions

137

Recent export changes

v3.19+18 create_multiassay, dot_plotly, extract_model_res +15 more

Testing

Has tests

Yes

Test-to-code ratio

0.23

testthat edition

3

Docs

Roxygen coverage

100%

Health & Security signals

Informational signals; not verdicts.

on.exit coverage

14.3%

Unsafe pattern score

0

Dep constraint coverage

0%

Secret pattern count

0

Bundled 3rd-party code

2 items

Portability & License

Min R version

4.4.0

System requirements

–

C++ standard

–

License

AGPL-3

License flags

SPDX valid, OSI approved

History

Versions

5

First release

2024-04-30

Latest release

2026-04-28

Avg cadence

182 days

Cold removal rate

–

Dep drift

2

LOC over versions

v3.19: 11,105 LOCv3.20: 11,105 LOCv3.21: 12,107 LOCv3.22: 12,107 LOCv3.23: 12,107 LOC

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

Documentation

In the Bioconductor 3.23 release
READMEYes · 1,878 wordsVignettesYes · 1 · dynamicNEWSYesCitation fileYes · cites a publication
Help pages
23 (1 internal)includes a package overview page
Examples that run
100%20 run in a plain check
Exported functions with examples
100%
Documented parameters
100%
Return-value docs
100%
Help pages citing references
4%
Vignettes (1)

Repository practices

Upstream repositoryBeta

1 development-tooling and community-health practice detected across 1 family in the upstream repository

Checks run against github.com/angelovelle96/gintomics on 2026-10-11.

Docs source (1)

GitHub Pages site last deployed 2024-03-04

How this is detected·Detection ruleset v3 (2026-09-26)

Datasets

Bundled datasets · 2
NameClassSizeAlso in
mirna_hsadata.frame1,914 × 13No other package
mmultiassay_ov–––

3 internal objects are bundled for the package's own use and not listed here.

All of gINTomics's data objects

Topics

Maintainer
Angelo Velle

Available on

CRANr2uBioconductorautoCRANCOPR

People

Cite

Cite this package

Run in R for the authors' entry:

citation("gINTomics")

The package provides a citation file, so citation() returns the authors' own entry.

It points to 10.1101/2025.10.07.680960.

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 gINTomics version 1.8.0 [Data set]. HJJB, LLC. Data release v2026-10-18. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-18, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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