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AMOUNTAIN

Bioc current

Active modules for multilayer weighted gene co-expression networks: a continuous optimization approach

v1.38.0 · software · GPL (>= 2)

Release Lineage

Entered 3.4 · Oct 18, 2016

Current · Requires R 4.6

1.0 In 20 of 49 releases 3.23

Description

A pure data-driven gene network, weighted gene co-expression network (WGCN) could be constructed only from expression profile. Different layers in such networks may represent different time points, multiple conditions or various species. AMOUNTAIN aims to search active modules in multi-layer WGCN using a continuous optimization approach.

Line coverage

Expression

Tests / Examples

Functions

19 10 exported

Complexity

2.4 avg / 5 max

Call network

19 nodes / 16 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

1,870

Files

22

Compiled share

24.4%

Has compiled src

Yes

Language breakdown

R 601 (32.1%)C/C++/src 457 (24.4%)Docs 549 (29.4%)Vignettes 263 (14.1%)

API

Exported functions

10

Internal functions

0

Recent export changes

v3.5+4 CGPFixSS, CGPFixSSMultiLayer, CGPFixSSTwolayer +1 more  −1 vecconsensus

Testing & CI

Has tests

No

Test-to-code ratio

0.00

testthat edition

CI present

No

CI type

[]

PR gated

No

Docs

Return-value doc rate

100%

\dontrun example ratio

0%

Roxygen coverage

100%

Has pkgdown

No

NEWS present

No

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

3.3.0

System requirements

1

C++ standard

License

GPL (>= 2)

License flags

SPDX valid, OSI approved

History

Versions

20

First release

2016-10-17

Latest release

2026-04-28

Avg cadence

182 days

Cold removal rate

100%

Dep drift

1

LOC over versions

v3.4: 921 LOCv3.5: 1,870 LOCv3.6: 1,870 LOCv3.7: 1,870 LOCv3.8: 1,870 LOCv3.9: 1,870 LOCv3.10: 1,870 LOCv3.11: 1,870 LOCv3.12: 1,870 LOCv3.13: 1,870 LOCv3.14: 1,870 LOCv3.15: 1,870 LOCv3.16: 1,870 LOCv3.17: 1,870 LOCv3.18: 1,870 LOCv3.19: 1,870 LOCv3.20: 1,870 LOCv3.21: 1,870 LOCv3.22: 1,870 LOCv3.23: 1,870 LOC

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

Topics

Depended on by (1)

Bioconductor (1)

People

Dong Li