biosigner

This package is for version 3.9 of Bioconductor; for the stable, up-to-date release version, see biosigner.

Signature discovery from omics data


Bioconductor version: 3.9

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")):

Installation

To install this package, start R (version "3.6") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("biosigner")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("biosigner")
Vignette Title HTML R Script
Reference Manual PDF
NEWS Text

Details

biocViews Classification, FeatureExtraction, Lipidomics, Metabolomics, Proteomics, Software, Transcriptomics
Version 1.12.0
In Bioconductor since BioC 3.3 (R-3.3) (8 years)
License CeCILL
Depends Biobase, ropls
Imports methods, e1071, randomForest
System Requirements
URL
See More
Suggests BioMark, BiocGenerics, BiocStyle, golubEsets, hu6800.db, knitr, rmarkdown, testthat
Linking To
Enhances
Depends On Me
Imports Me
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Build Report Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package biosigner_1.12.0.tar.gz
Windows Binary biosigner_1.12.0.zip
Mac OS X 10.11 (El Capitan) biosigner_1.12.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/biosigner
Source Repository (Developer Access) git clone [email protected]:packages/biosigner
Bioc Package Browser https://code.bioconductor.org/browse/biosigner/
Package Short Url https://bioconductor.org/packages/biosigner/
Package Downloads Report Download Stats
Old Source Packages for BioC 3.9 Source Archive