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| author | zimoun <zimon.toutoune@gmail.com> | 2021-05-21 22:26:07 +0200 |
|---|---|---|
| committer | Ricardo Wurmus <rekado@elephly.net> | 2021-05-31 15:38:00 +0200 |
| commit | 621aa3b442341c81305d2d56835203ff517a7bb9 (patch) | |
| tree | fc9d8cf290325f1ce50f50c7685a2db80f9fae98 | |
| parent | 900ef8fb1ea8a85966a1a81ea01a9f3670fc8c58 (diff) | |
| download | guix-patches-621aa3b442341c81305d2d56835203ff517a7bb9.tar guix-patches-621aa3b442341c81305d2d56835203ff517a7bb9.tar.gz | |
gnu: r-sva: Move to (gnu packages bioconductor).
* gnu/packages/bioinformatics.scm (r-sva): Move from here...
* gnu/packages/bioconductor.scm (r-sva): ...to here.
| -rw-r--r-- | gnu/packages/bioconductor.scm | 31 | ||||
| -rw-r--r-- | gnu/packages/bioinformatics.scm | 31 |
2 files changed, 31 insertions, 31 deletions
diff --git a/gnu/packages/bioconductor.scm b/gnu/packages/bioconductor.scm index 8e0182691b..a4d99dd929 100644 --- a/gnu/packages/bioconductor.scm +++ b/gnu/packages/bioconductor.scm @@ -3790,6 +3790,37 @@ typically represent genomic ranges of interest and the columns represent samples.") (license license:artistic2.0))) +(define-public r-sva + (package + (name "r-sva") + (version "3.38.0") + (source + (origin + (method url-fetch) + (uri (bioconductor-uri "sva" version)) + (sha256 + (base32 + "1hpzzg3qrgkd8kwg1m5gq94cikjgk9j4l1wk58fxl49s6fmd13zy")))) + (build-system r-build-system) + (propagated-inputs + `(("r-edger" ,r-edger) + ("r-genefilter" ,r-genefilter) + ("r-mgcv" ,r-mgcv) + ("r-biocparallel" ,r-biocparallel) + ("r-matrixstats" ,r-matrixstats) + ("r-limma" ,r-limma))) + (home-page "https://bioconductor.org/packages/sva") + (synopsis "Surrogate variable analysis") + (description + "This package contains functions for removing batch effects and other +unwanted variation in high-throughput experiment. It also contains functions +for identifying and building surrogate variables for high-dimensional data +sets. Surrogate variables are covariates constructed directly from +high-dimensional data like gene expression/RNA sequencing/methylation/brain +imaging data that can be used in subsequent analyses to adjust for unknown, +unmodeled, or latent sources of noise.") + (license license:artistic2.0))) + (define-public r-systempiper (package (name "r-systempiper") diff --git a/gnu/packages/bioinformatics.scm b/gnu/packages/bioinformatics.scm index ca0952895c..cb0fe505cb 100644 --- a/gnu/packages/bioinformatics.scm +++ b/gnu/packages/bioinformatics.scm @@ -8964,37 +8964,6 @@ resolution 5hmC data from experimental protocols such as oxBS-Seq and TAB-Seq.") (license license:artistic2.0))) -(define-public r-sva - (package - (name "r-sva") - (version "3.38.0") - (source - (origin - (method url-fetch) - (uri (bioconductor-uri "sva" version)) - (sha256 - (base32 - "1hpzzg3qrgkd8kwg1m5gq94cikjgk9j4l1wk58fxl49s6fmd13zy")))) - (build-system r-build-system) - (propagated-inputs - `(("r-edger" ,r-edger) - ("r-genefilter" ,r-genefilter) - ("r-mgcv" ,r-mgcv) - ("r-biocparallel" ,r-biocparallel) - ("r-matrixstats" ,r-matrixstats) - ("r-limma" ,r-limma))) - (home-page "https://bioconductor.org/packages/sva") - (synopsis "Surrogate variable analysis") - (description - "This package contains functions for removing batch effects and other -unwanted variation in high-throughput experiment. It also contains functions -for identifying and building surrogate variables for high-dimensional data -sets. Surrogate variables are covariates constructed directly from -high-dimensional data like gene expression/RNA sequencing/methylation/brain -imaging data that can be used in subsequent analyses to adjust for unknown, -unmodeled, or latent sources of noise.") - (license license:artistic2.0))) - (define-public r-raremetals2 (package (name "r-raremetals2") |