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.
Bioconductor version: Release (3.4)
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 | 1.2.4 |
In Bioconductor since | BioC 3.3 (R-3.3) (1 year) |
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.
Package Source | biosigner_1.2.4.tar.gz |
Windows Binary | biosigner_1.2.4.zip |
Mac OS X 10.9 (Mavericks) | biosigner_1.2.4.tgz |
Subversion source | (username/password: readonly) |
Git source | https://github.com/Bioconductor-mirror/biosigner/tree/release-3.4 |
Package Short Url | http://bioconductor.org/packages/biosigner/ |
Package Downloads Report | Download Stats |
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