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To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("TurboNorm")
In most cases, you don't need to download the package archive at all.
TurboNorm
A fast scatterplot smoother suitable for microarray normalization
Bioconductor version: 3.0
A fast scatterplot smoother based on B-splines with second-order difference penalty. Functions for microarray normalization of single-colour data i.e. Affymetrix/Illumina and two-colour data supplied as marray MarrayRaw-objects or limma RGList-objects are available.
Author: Maarten van Iterson and Chantal van Leeuwen
Maintainer: Maarten van Iterson <mviterson at gmail.com>
Citation (from within R,
enter citation("TurboNorm")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("TurboNorm")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("TurboNorm")
| R Script | TurboNorm Overview | |
| Reference Manual | ||
| Text | NEWS |
Details
| biocViews | CpGIsland, DNAMethylation, MethylationArray, Microarray, Normalization, OneChannel, Preprocessing, Software, TwoChannel |
| Version | 1.14.0 |
| In Bioconductor since | BioC 2.8 (R-2.13) |
| License | LGPL |
| Depends | R (>= 2.12.0), convert, limma(>= 1.7.0), marray |
| Imports | stats, grDevices, affy, lattice |
| LinkingTo | |
| Suggests | BiocStyle, affydata |
| SystemRequirements | |
| Enhances | |
| URL | http://www.humgen.nl/MicroarrayAnalysisGroup.html |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | TurboNorm_1.14.0.tar.gz |
| Windows Binary | TurboNorm_1.14.0.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | TurboNorm_1.14.0.tgz |
| Mac OS X 10.9 (Mavericks) | TurboNorm_1.14.0.tgz |
| Browse/checkout source | (username/password: readonly) |
| Package Downloads Report | Download Stats |
Common Bioconductor workflows include:
- Oligonucleotide Arrays
- High-throughput Sequencing
- Counting Reads for Differential Expression (parathyroideSE vignette)
- Annotation
- Annotating Variants
- Annotating Ranges
- Flow Cytometry and other assays
- Candidate Binding Sites for Known Transcription Factors
- Cloud-enabled cis-eQTL search and annotation
- RNA-Seq workflow: gene-level exploratory analysis and differential expression
- Changing genomic coordinate systems with rtracklayer::liftOver
- Mass spectrometry and proteomics data analysis
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