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authorRicardo Wurmus <rekado@elephly.net>2019-03-27 15:45:20 +0100
committerRicardo Wurmus <rekado@elephly.net>2019-03-27 16:17:20 +0100
commit305050b56d5df003f986cbca5fedb4b9b5cd45bb (patch)
tree740236be0ad3203ae8a9e8f5d4ae1bf5035a0d40 /gnu
parent11f226e124e51de8a7ca873c699badbb74be057c (diff)
downloadguix-305050b56d5df003f986cbca5fedb4b9b5cd45bb.tar.gz
guix-305050b56d5df003f986cbca5fedb4b9b5cd45bb.zip
gnu: Add r-dose.
* gnu/packages/bioconductor.scm (r-dose): New variable.
Diffstat (limited to 'gnu')
-rw-r--r--gnu/packages/bioconductor.scm34
1 files changed, 34 insertions, 0 deletions
diff --git a/gnu/packages/bioconductor.scm b/gnu/packages/bioconductor.scm
index 86c15c08ea..0c7be1c7d5 100644
--- a/gnu/packages/bioconductor.scm
+++ b/gnu/packages/bioconductor.scm
@@ -2779,3 +2779,37 @@ analysis. Using the fast algorithm allows to make more permutations and get
more fine grained p-values, which allows to use accurate stantard approaches
to multiple hypothesis correction.")
(license license:expat)))
+
+(define-public r-dose
+ (package
+ (name "r-dose")
+ (version "3.8.2")
+ (source
+ (origin
+ (method url-fetch)
+ (uri (bioconductor-uri "DOSE" version))
+ (sha256
+ (base32
+ "1gh7dhvfc71kawxcfx8xqlir7mwvg5mmz4lqrdrvw5knvi2h3mfa"))))
+ (properties `((upstream-name . "DOSE")))
+ (build-system r-build-system)
+ (propagated-inputs
+ `(("r-annotationdbi" ,r-annotationdbi)
+ ("r-biocparallel" ,r-biocparallel)
+ ("r-do-db" ,r-do-db)
+ ("r-fgsea" ,r-fgsea)
+ ("r-ggplot2" ,r-ggplot2)
+ ("r-gosemsim" ,r-gosemsim)
+ ("r-qvalue" ,r-qvalue)
+ ("r-reshape2" ,r-reshape2)
+ ("r-s4vectors" ,r-s4vectors)))
+ (home-page "https://guangchuangyu.github.io/software/DOSE/")
+ (synopsis "Disease ontology semantic and enrichment analysis")
+ (description
+ "This package implements five methods proposed by Resnik, Schlicker,
+Jiang, Lin and Wang, respectively, for measuring semantic similarities among
+@dfn{Disease ontology} (DO) terms and gene products. Enrichment analyses
+including hypergeometric model and gene set enrichment analysis are also
+implemented for discovering disease associations of high-throughput biological
+data.")
+ (license license:artistic2.0)))