MetNet
Bioc currentInferring metabolic networks from untargeted high-resolution mass spectrometry data
Release Lineage
Entered 3.8 · Oct 31, 2018
Current · Requires R 4.6
Description
MetNet contains functionality to infer metabolic network topologies from quantitative data and high-resolution mass/charge information. Using statistical models (including correlation, mutual information, regression and Bayes statistics) and quantitative data (intensity values of features) adjacency matrices are inferred that can be combined to a consensus matrix. Mass differences calculated between mass/charge values of features will be matched against a data frame of supplied mass/charge differences referring to transformations of enzymatic activities. In a third step, the two levels of information are combined to form a adjacency matrix inferred from both quantitative and structure information.
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
21 17 exported
Complexity
6.3 avg / 21 max
Call network
21 nodes / 8 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
7,626
Files
68
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
17
Internal functions
4
Recent export changes
Testing & CI
Has tests
Yes
Test-to-code ratio
0.59
testthat edition
–
CI present
Yes
CI type
["github-actions"]
PR gated
Yes
Docs
Roxygen coverage
100%
Health & Security signals
Informational signals; not verdicts.
on.exit coverage
–
Unsafe pattern score
3
Dep constraint coverage
100%
Secret pattern count
0
Bundled 3rd-party code
2 items
Portability & License
Min R version
4.1
System requirements
–
C++ standard
–
License
GPL (>= 3)
License flags
SPDX valid, OSI approved
History
Versions
16
First release
2019-01-04
Latest release
2026-04-28
Avg cadence
182 days
Cold removal rate
100%
Dep drift
18
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
- 98%
- Return-value docs
- 100%
- References docs
- 16%
Datasets
| Name | Class | Rows × Cols | Also in |
|---|---|---|---|
| peaklist | data.frame | 5,067 × 122 | No other package |
| x_annotation | data.frame | 36 × 11 | No other package |
| x_test | data.frame | 36 × 122 | No other package |
Topics
People
- Thomas Naake author maintainer
- Elva Maria Novoa-del-Toro contributor
- Liesa Salzer contributor
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("MetNet")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.
From data release v2026-08-25, which the citation names so these numbers can be found later. More on citing and the projects behind them.