nnNorm
Spatial and intensity based normalization of cDNA microarray data based on robust neural nets
Bioconductor version: 2.6
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.
Author: Adi Laurentiu Tarca <atarca at med.wayne.edu>
Maintainer: Adi Laurentiu Tarca <atarca at med.wayne.edu>
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("nnNorm")
To cite this package in a publication, start R and enter:
citation("nnNorm")
Documentation
| R Script | nnNorm Tutorial | |
| nnNormGuide.pdf | ||
| Reference Manual |
Details
| biocViews | Microarray, TwoChannel, Preprocessing |
| Depends | R(>= 2.2.0), marray |
| Imports | graphics, grDevices, marray, methods, nnet, stats |
| Suggests | |
| System Requirements | |
| License | LGPL |
| URL | http://bioinformaticsprb.med.wayne.edu/tarca/ |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Version | 2.12.0 |
| Since | Bioconductor 1.6 (R-2.1) or earlier |
Package Downloads
| Package Source | nnNorm_2.12.0.tar.gz |
| Windows Binary | nnNorm_2.12.0.zip (32- & 64-bit) |
| MacOS 10.5 (Leopard) binary | nnNorm_2.12.0.tgz |
| Package Downloads Report | Download Stats |
Common Bioconductor workflows include:
- Oligonucleotide Arrays
- High-throughput Sequencing
- Annotation
- Variants
- Flow Cytometry and other assays
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