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| -rw-r--r-- | gnu/packages/bioconductor.scm | 50 |
1 files changed, 50 insertions, 0 deletions
diff --git a/gnu/packages/bioconductor.scm b/gnu/packages/bioconductor.scm index f63bfa4a1f..2f2a60ad19 100644 --- a/gnu/packages/bioconductor.scm +++ b/gnu/packages/bioconductor.scm @@ -4974,3 +4974,53 @@ also beyond the realm of omics (e.g. spectral imaging). The methods implemented in mixOmics can also handle missing values without having to delete entire rows with missing data.") (license license:gpl2+))) + +(define-public r-depecher + (package + (name "r-depecher") + (version "1.0.3") + (source + (origin + (method url-fetch) + (uri (bioconductor-uri "DepecheR" version)) + (sha256 + (base32 + "0qj2h2a50fncppvi2phh0mbivxkn1mv702mqpi9mvvkf3bzq8m0h")))) + (properties `((upstream-name . "DepecheR"))) + (build-system r-build-system) + (arguments + `(#:phases + (modify-phases %standard-phases + (add-after 'unpack 'fix-syntax-error + (lambda _ + (substitute* "src/Makevars" + ((" & ") " && ")) + #t))))) + (propagated-inputs + `(("r-beanplot" ,r-beanplot) + ("r-biocparallel" ,r-biocparallel) + ("r-dosnow" ,r-dosnow) + ("r-dplyr" ,r-dplyr) + ("r-foreach" ,r-foreach) + ("r-ggplot2" ,r-ggplot2) + ("r-gplots" ,r-gplots) + ("r-mass" ,r-mass) + ("r-matrixstats" ,r-matrixstats) + ("r-mixomics" ,r-mixomics) + ("r-moments" ,r-moments) + ("r-rcpp" ,r-rcpp) + ("r-rcppeigen" ,r-rcppeigen) + ("r-reshape2" ,r-reshape2) + ("r-viridis" ,r-viridis))) + (home-page "https://bioconductor.org/packages/DepecheR/") + (synopsis "Identify traits of clusters in high-dimensional entities") + (description + "The purpose of this package is to identify traits in a dataset that can +separate groups. This is done on two levels. First, clustering is performed, +using an implementation of sparse K-means. Secondly, the generated clusters +are used to predict outcomes of groups of individuals based on their +distribution of observations in the different clusters. As certain clusters +with separating information will be identified, and these clusters are defined +by a sparse number of variables, this method can reduce the complexity of +data, to only emphasize the data that actually matters.") + (license license:expat))) |