gnu: Add r-biosigner.
* gnu/packages/bioconductor.scm (r-biosigner): New variable.
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@ -4642,3 +4642,38 @@ validity of the model by permutation testing, detect outliers, and perform
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feature selection (e.g. with Variable Importance in Projection or regression
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feature selection (e.g. with Variable Importance in Projection or regression
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coefficients).")
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coefficients).")
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(license license:cecill)))
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(license license:cecill)))
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(define-public r-biosigner
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(package
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(name "r-biosigner")
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(version "1.12.0")
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(source
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(origin
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(method url-fetch)
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(uri (bioconductor-uri "biosigner" version))
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(sha256
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(base32
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"1643iya40v6whb7lw7y34w5sanbasvj4yhvcygbip667yhphyv5b"))))
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(build-system r-build-system)
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(propagated-inputs
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`(("r-biobase" ,r-biobase)
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("r-e1071" ,r-e1071)
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("r-randomforest" ,r-randomforest)
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("r-ropls" ,r-ropls)))
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(native-inputs
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`(("r-knitr" ,r-knitr)
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("r-rmarkdown" ,r-rmarkdown)
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("pandoc" ,ghc-pandoc)
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("pandoc-citeproc" ,ghc-pandoc-citeproc))) ; all for vignettes
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(home-page "https://bioconductor.org/packages/biosigner/")
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(synopsis "Signature discovery from omics data")
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(description
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"Feature selection is critical in omics data analysis to extract
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restricted and meaningful molecular signatures from complex and high-dimension
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data, and to build robust classifiers. This package implements a method to
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assess the relevance of the variables for the prediction performances of the
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classifier. The approach can be run in parallel with the PLS-DA, Random
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Forest, and SVM binary classifiers. The signatures and the corresponding
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'restricted' models are returned, enabling future predictions on new
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datasets.")
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(license license:cecill)))
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