To install this package, start R and enter:
## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("biosigner")
In most cases, you don't need to download the package archive at all.
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Bioconductor version: Release (3.5)
Feature selection is critical in omics data analysis to extract restricted and meaningful molecular signatures from complex and high-dimension data, and to build robust classifiers. This package implements a new method to assess the relevance of the variables for the prediction performances of the classifier. The approach can be run in parallel with the PLS-DA, Random Forest, and SVM binary classifiers. The signatures and the corresponding 'restricted' models are returned, enabling future predictions on new datasets. A Galaxy implementation of the package is available within the Workflow4metabolomics.org online infrastructure for computational metabolomics.
Author: Philippe Rinaudo <phd.rinaudo at gmail.com>, Etienne Thevenot <etienne.thevenot at cea.fr>
Maintainer: Philippe Rinaudo <phd.rinaudo at gmail.com>, Etienne Thevenot <etienne.thevenot at cea.fr>
Citation (from within R,
enter citation("biosigner")):
To install this package, start R and enter:
## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("biosigner")
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("biosigner")
| R Script | Vignette Title | |
| Reference Manual | ||
| Text | NEWS |
| biocViews | Classification, FeatureExtraction, Lipidomics, Metabolomics, Proteomics, Software, Transcriptomics |
| Version | 1.4.0 |
| In Bioconductor since | BioC 3.3 (R-3.3) (1.5 years) |
| License | CeCILL |
| Depends | |
| Imports | methods, e1071, randomForest, ropls, Biobase |
| LinkingTo | |
| Suggests | BioMark, RUnit, BiocGenerics, BiocStyle, golubEsets, hu6800.db, knitr, rmarkdown |
| SystemRequirements | |
| Enhances | |
| URL | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Build Report |
Follow Installation instructions to use this package in your R session.
| Source Package | biosigner_1.4.0.tar.gz |
| Windows Binary | biosigner_1.4.0.zip |
| Mac OS X 10.11 (El Capitan) | biosigner_1.4.0.tgz |
| Source Repository | git clone https://git.bioconductor.org/packages/biosigner |
| Package Short Url | http://bioconductor.org/packages/biosigner/ |
| Package Downloads Report | Download Stats |
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