branch master updated: gnu: Add r-gsva.

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     new b2750695f7 gnu: Add r-gsva.
b2750695f7 is described below

commit b2750695f72519286cb0530431396767588cc67d
Author: Ricardo Wurmus <rekado@elephly.net>
AuthorDate: Wed Jul 19 09:50:08 2023 +0200

    gnu: Add r-gsva.
    
    * gnu/packages/bioconductor.scm (r-gsva): New variable.
---
 gnu/packages/bioconductor.scm | 40 ++++++++++++++++++++++++++++++++++++++++
 1 file changed, 40 insertions(+)

diff --git a/gnu/packages/bioconductor.scm b/gnu/packages/bioconductor.scm
index 8549d2404d..4f1a4d61b1 100644
--- a/gnu/packages/bioconductor.scm
+++ b/gnu/packages/bioconductor.scm
@@ -7183,6 +7183,46 @@ testing and other simple calculations.")
 Enrichment Analysis} (GSEA).")
     (license license:artistic2.0)))
 
+(define-public r-gsva
+  (package
+    (name "r-gsva")
+    (version "1.48.2")
+    (source (origin
+              (method url-fetch)
+              (uri (bioconductor-uri "GSVA" version))
+              (sha256
+               (base32
+                "1y0dz9ayyrz4ylppa8f4m4b20yajzdl1sz4wpz8kcsfhh71ii64y"))))
+    (properties `((upstream-name . "GSVA")))
+    (build-system r-build-system)
+    (propagated-inputs (list r-biobase
+                             r-biocparallel
+                             r-biocsingular
+                             r-delayedarray
+                             r-delayedmatrixstats
+                             r-gseabase
+                             r-hdf5array
+                             r-iranges
+                             r-matrix
+                             r-s4vectors
+                             r-singlecellexperiment
+                             r-sparsematrixstats
+                             r-summarizedexperiment))
+    (native-inputs (list r-knitr))
+    (home-page "https://github.com/rcastelo/GSVA";)
+    (synopsis "Gene Set Variation Analysis for microarray and RNA-seq data")
+    (description
+     "Gene Set Variation Analysis (GSVA) is a non-parametric, unsupervised
+method for estimating variation of gene set enrichment through the samples of
+a expression data set.  GSVA performs a change in coordinate systems,
+transforming the data from a gene by sample matrix to a gene-set by sample
+matrix, thereby allowing the evaluation of pathway enrichment for each sample.
+This new matrix of GSVA enrichment scores facilitates applying standard
+analytical methods like functional enrichment, survival analysis, clustering,
+CNV-pathway analysis or cross-tissue pathway analysis, in a pathway-centric
+manner.")
+    (license license:gpl2+)))
+
 (define-public r-harshlight
   (package
     (name "r-harshlight")