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author | Ricardo Wurmus <rekado@elephly.net> | 2023-07-19 09:50:08 +0200 |
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committer | Ricardo Wurmus <rekado@elephly.net> | 2023-07-19 09:56:55 +0200 |
commit | b2750695f72519286cb0530431396767588cc67d (patch) | |
tree | 8d02fc1faa6a882770e769562e836f67af99be3d /gnu/packages/bioconductor.scm | |
parent | 1f53bfb7d73638e5187df6f0e976b5f5eb091b0d (diff) | |
download | guix-b2750695f72519286cb0530431396767588cc67d.tar.gz guix-b2750695f72519286cb0530431396767588cc67d.zip |
gnu: Add r-gsva.
* gnu/packages/bioconductor.scm (r-gsva): New variable.
Diffstat (limited to 'gnu/packages/bioconductor.scm')
-rw-r--r-- | gnu/packages/bioconductor.scm | 40 |
1 files changed, 40 insertions, 0 deletions
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") |