Package: biosigner
Type: Package
Title: Signature discovery from omics data
Version: 1.31.0
Date: 2023-05-28
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 <etienne.thevenot@cea.fr>
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:
    BioMark,
    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: 2016-05-03 10:14:01 UTC; admin-local
RoxygenNote: 7.2.3