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:
nnNorm_2.71.0.tar.gz
nnNorm_2.71.0.zip(r-4.5)nnNorm_2.71.0.zip(r-4.4)nnNorm_2.71.0.zip(r-4.3)
nnNorm_2.71.0.tgz(r-4.4-any)nnNorm_2.71.0.tgz(r-4.3-any)
nnNorm_2.71.0.tar.gz(r-4.5-noble)nnNorm_2.71.0.tar.gz(r-4.4-noble)
nnNorm_2.71.0.tgz(r-4.4-emscripten)nnNorm_2.71.0.tgz(r-4.3-emscripten)
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')) |
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
Last updated 26 days agofrom:18cab7b330. Checks:OK: 1 NOTE: 6. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 30 2024 |
R-4.5-win | NOTE | Oct 30 2024 |
R-4.5-linux | NOTE | Oct 30 2024 |
R-4.4-win | NOTE | Oct 30 2024 |
R-4.4-mac | NOTE | Oct 30 2024 |
R-4.3-win | NOTE | Oct 30 2024 |
R-4.3-mac | NOTE | Oct 30 2024 |