gnu: Add r-biosigner.

* gnu/packages/bioconductor.scm (r-biosigner): New variable.
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Ricardo Wurmus 2019-06-10 10:58:39 +02:00
parent a9fac3f4d3
commit 075a90946b
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@ -4642,3 +4642,38 @@ validity of the model by permutation testing, detect outliers, and perform
feature selection (e.g. with Variable Importance in Projection or regression feature selection (e.g. with Variable Importance in Projection or regression
coefficients).") coefficients).")
(license license:cecill))) (license license:cecill)))
(define-public r-biosigner
(package
(name "r-biosigner")
(version "1.12.0")
(source
(origin
(method url-fetch)
(uri (bioconductor-uri "biosigner" version))
(sha256
(base32
"1643iya40v6whb7lw7y34w5sanbasvj4yhvcygbip667yhphyv5b"))))
(build-system r-build-system)
(propagated-inputs
`(("r-biobase" ,r-biobase)
("r-e1071" ,r-e1071)
("r-randomforest" ,r-randomforest)
("r-ropls" ,r-ropls)))
(native-inputs
`(("r-knitr" ,r-knitr)
("r-rmarkdown" ,r-rmarkdown)
("pandoc" ,ghc-pandoc)
("pandoc-citeproc" ,ghc-pandoc-citeproc))) ; all for vignettes
(home-page "https://bioconductor.org/packages/biosigner/")
(synopsis "Signature discovery from omics data")
(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 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.")
(license license:cecill)))