(address . guix-patches@gnu.org)(name . zimoun)(address . zimon.toutoune@gmail.com)
* gnu/packages/bioconductor.scm (r-depecher): New variable.
---
gnu/packages/bioconductor.scm | 44 +++++++++++++++++++++++++++++++++++
1 file changed, 44 insertions(+)
Toggle diff (54 lines)
diff --git a/gnu/packages/bioconductor.scm b/gnu/packages/bioconductor.scm
index 64625aedd4..7c9a3b7417 100644
--- a/gnu/packages/bioconductor.scm
+++ b/gnu/packages/bioconductor.scm
@@ -5013,3 +5013,47 @@ data sets: N-integration with variants of Generalised Canonical Correlation
Analysis and P-integration with variants of multi-group Partial Least
Squares.")
(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)
+ (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
+ "Determination of essential phenotypic elements 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)))
--
2.21.0