This is the development version of biosigner; for the stable release version, see biosigner.
Signature discovery from omics dataBioconductor version: Development (3.22)
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] ORCID: 0000-0003-1019-4577
Maintainer: Etienne A. Thevenot <etienne.thevenot at cea.fr>
Citation (from within R, entercitation("biosigner")): Installation
To install this package, start R (version "4.5") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
# The following initializes usage of Bioc devel
BiocManager::install(version='devel')
BiocManager::install("biosigner")
For older versions of R, please refer to the appropriate Bioconductor release.
DocumentationTo view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("biosigner")Follow Installation instructions to use this package in your R session.
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