Package: biosigner Type: Package Title: Signature discovery from omics data Version: 1.41.0 Date: 2025-07-02 Authors@R: c(person("Philippe", "Rinaudo", email = "phd.rinaudo@gmail.com", role = c("aut")), person("Etienne A.", "Thevenot", email = "etienne.thevenot@cea.fr", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-1019-4577"))) Maintainer: Etienne A. Thevenot biocViews: Classification, FeatureExtraction, Transcriptomics, Proteomics, Metabolomics, Lipidomics, MassSpectrometry Description: 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. Imports: Biobase, methods, e1071, grDevices, graphics, MultiAssayExperiment, MultiDataSet, randomForest, ropls, stats, SummarizedExperiment, utils Suggests: BiocGenerics, BiocStyle, golubEsets, hu6800.db, knitr, omicade4, rmarkdown, testthat VignetteBuilder: knitr License: CeCILL Encoding: UTF-8 LazyLoad: yes URL: http://dx.doi.org/10.3389/fmolb.2016.00026 NeedsCompilation: no Packaged: 2026-07-04 00:47:58 UTC; root RoxygenNote: 7.3.2 Config/pak/sysreqs: cmake make libicu-dev libuv1-dev libssl-dev zlib1g-dev Repository: https://bioc.r-universe.dev Date/Publication: 2026-04-28 12:42:51 UTC RemoteUrl: https://github.com/bioc/biosigner RemoteRef: HEAD RemoteSha: dcefe5c9c0ade5446b2e0e27a0ea2ffd41a99d2e Author: Philippe Rinaudo [aut], Etienne A. Thevenot [aut, cre] (ORCID: )