Package: nnNorm 2.71.0

Adi Laurentiu Tarca

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

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.

Authors:Adi Laurentiu Tarca <[email protected]>

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nnNorm.pdf |nnNorm.html
nnNorm/json (API)

# Install 'nnNorm' in R:
install.packages('nnNorm', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

On BioConductor:nnNorm-2.69.0(bioc 3.20)nnNorm-2.68.0(bioc 3.19)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

microarraytwochannelpreprocessing

3.30 score 1 scripts 268 downloads 1 mentions 3 exports 4 dependencies

Last updated 26 days agofrom:18cab7b330. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 30 2024
R-4.5-winNOTEOct 30 2024
R-4.5-linuxNOTEOct 30 2024
R-4.4-winNOTEOct 30 2024
R-4.4-macNOTEOct 30 2024
R-4.3-winNOTEOct 30 2024
R-4.3-macNOTEOct 30 2024

Exports:compNormdetectSpatialBiasmaNormNN

Dependencies:limmamarraynnetstatmod

nnNorm Tutorial

Rendered fromnnNorm.Rnwusingutils::Sweaveon Oct 30 2024.

Last update: 2013-11-01
Started: 2013-11-01