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authorRicardo Wurmus <rekado@elephly.net>2019-09-15 20:42:41 +0200
committerRicardo Wurmus <rekado@elephly.net>2019-09-15 20:42:41 +0200
commit853211a51b63315b096c98371618eec243feae38 (patch)
tree123559ff6d6e20117ca5135f78a5a5a8ad042055 /gnu/packages
parent739b2d10f0701f0df9a6cae411e02376d3e23813 (diff)
downloadguix-853211a51b63315b096c98371618eec243feae38.tar.gz
guix-853211a51b63315b096c98371618eec243feae38.zip
gnu: Add r-timeseriesexperiment.
* gnu/packages/bioconductor.scm (r-timeseriesexperiment): New variable.
Diffstat (limited to 'gnu/packages')
-rw-r--r--gnu/packages/bioconductor.scm39
1 files changed, 39 insertions, 0 deletions
diff --git a/gnu/packages/bioconductor.scm b/gnu/packages/bioconductor.scm
index baa1f71524..b458c62dbc 100644
--- a/gnu/packages/bioconductor.scm
+++ b/gnu/packages/bioconductor.scm
@@ -5505,3 +5505,42 @@ computing. While wavClusteR was designed for PAR-CLIP data analysis, it can
be applied to the analysis of other NGS data obtained from experimental
procedures that induce nucleotide substitutions (e.g. BisSeq).")
(license license:gpl2)))
+
+(define-public r-timeseriesexperiment
+ (package
+ (name "r-timeseriesexperiment")
+ (version "1.2.0")
+ (source
+ (origin
+ (method url-fetch)
+ (uri (bioconductor-uri "TimeSeriesExperiment" version))
+ (sha256
+ (base32
+ "1j11g7a2p0yk38fx6wd6152l1xynghj01pfxihalw601jwf1bl0y"))))
+ (properties
+ `((upstream-name . "TimeSeriesExperiment")))
+ (build-system r-build-system)
+ (propagated-inputs
+ `(("r-deseq2" ,r-deseq2)
+ ("r-dplyr" ,r-dplyr)
+ ("r-dynamictreecut" ,r-dynamictreecut)
+ ("r-edger" ,r-edger)
+ ("r-ggplot2" ,r-ggplot2)
+ ("r-hmisc" ,r-hmisc)
+ ("r-limma" ,r-limma)
+ ("r-magrittr" ,r-magrittr)
+ ("r-proxy" ,r-proxy)
+ ("r-s4vectors" ,r-s4vectors)
+ ("r-summarizedexperiment" ,r-summarizedexperiment)
+ ("r-tibble" ,r-tibble)
+ ("r-tidyr" ,r-tidyr)
+ ("r-vegan" ,r-vegan)
+ ("r-viridis" ,r-viridis)))
+ (home-page "https://github.com/nlhuong/TimeSeriesExperiment/")
+ (synopsis "Analysis for short time-series data")
+ (description
+ "This package is a visualization and analysis toolbox for short time
+course data which includes dimensionality reduction, clustering, two-sample
+differential expression testing and gene ranking techniques. The package also
+provides methods for retrieving enriched pathways.")
+ (license license:lgpl3+)))