biosigner

DOI: 10.18129/B9.bioc.biosigner  

Signature discovery from omics data

Bioconductor version: Release (3.17)

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 [aut], Etienne A. Thevenot [aut, cre]

Maintainer: Etienne A. Thevenot <etienne.thevenot at cea.fr>

Installation

To install this package, start R (version "4.3") 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")

 

HTML	R Script	biosigner-vignette
PDF		Reference Manual
Text		NEWS

Details

biocViews	Classification, FeatureExtraction, Lipidomics, MassSpectrometry, Metabolomics, Proteomics, Software, Transcriptomics
Version	1.28.0
In Bioconductor since	BioC 3.3 (R-3.3) (7.5 years)
License	CeCILL
Depends
Imports	Biobase, methods, e1071, grDevices, graphics, MultiAssayExperiment, MultiDataSet, randomForest, ropls, stats, SummarizedExperiment, utils
LinkingTo
Suggests	BioMark, BiocGenerics, BiocStyle, golubEsets, hu6800.db, knitr, omicade4, rmarkdown, testthat
SystemRequirements
Enhances
URL	http://dx.doi.org/10.3389/fmolb.2016.00026
Depends On Me
Imports Me	multiSight
Suggests Me	phenomis
Links To Me
Build Report

Package Archives

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

Source Package	biosigner_1.28.0.tar.gz
Windows Binary	biosigner_1.28.0.zip
macOS Binary (x86_64)	biosigner_1.28.0.tgz
macOS Binary (arm64)	biosigner_1.27.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/biosigner
Source Repository (Developer Access)	git clone git@git.bioconductor.org: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 3.17	Source Archive