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nnNorm

Bioc current

Spatial and intensity based normalization of cDNA microarray data based on robust neural nets

v2.76.0 · software · LGPL

Release Lineage

Entered 1.5 · Oct 25, 2004

Current · Requires R 4.6

1.0 In 44 of 49 releases 3.23

Description

This package allows to detect and correct for spatial and intensity biases with two-channel microarray data. The normalization method implemented in this package is based on robust neural networks fitting.

Test coverage

Line coverage

Expression

Tests / Examples

Functions

3 3 exported

Complexity

16.7 avg / 31 max

Call network

3 nodes / 0 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

667

Files

13

Compiled share

0%

Has compiled src

No

Language breakdown

R 324 (48.6%)Docs 185 (27.7%)Vignettes 158 (23.7%)

API

Exported functions

3

Internal functions

0

Testing & CI

Has tests

No

Test-to-code ratio

0.00

testthat edition

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

0%

Secret pattern count

0

Bundled 3rd-party code

2 items

Portability & License

Min R version

2.2.0

System requirements

C++ standard

License

LGPL

License flags

not SPDX, not OSI

History

Versions

44

First release

2004-11-03

Latest release

2026-04-28

Avg cadence

182 days

Cold removal rate

Dep drift

4

LOC over versions

v1.5: 603 LOCv1.6: 485 LOCv1.7: 485 LOCv1.8: 560 LOCv1.9: 560 LOCv2.0: 514 LOCv2.1: 514 LOCv2.2: 514 LOCv2.3: 514 LOCv2.4: 509 LOCv2.5: 509 LOCv2.6: 509 LOCv2.7: 509 LOCv2.8: 509 LOCv2.9: 509 LOCv2.10: 509 LOCv2.11: 509 LOCv2.12: 509 LOCv2.13: 509 LOCv2.14: 667 LOCv3.0: 667 LOCv3.1: 667 LOCv3.2: 667 LOCv3.3: 667 LOCv3.4: 667 LOCv3.5: 667 LOCv3.6: 667 LOCv3.7: 667 LOCv3.8: 667 LOCv3.9: 667 LOCv3.10: 667 LOCv3.11: 667 LOCv3.12: 667 LOCv3.13: 667 LOCv3.14: 667 LOCv3.15: 667 LOCv3.16: 667 LOCv3.17: 667 LOCv3.18: 667 LOCv3.19: 667 LOCv3.20: 667 LOCv3.21: 667 LOCv3.22: 667 LOCv3.23: 667 LOC

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

Documentation

Documentation
READMENoVignettesYes · dynamicpkgdown siteNoNEWSNoCode of conductNoContributing guideNo
Examples that run
100%
Documented parameters
100%
Return-value docs
100%
References docs
100%

Topics

People

Adi Laurentiu Tarca

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("nnNorm")

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 nnNorm version 2.76.0 [Data set]. HJJB, LLC. Data release v2026-08-23. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-23, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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