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| author | Ricardo Wurmus <rekado@elephly.net> | 2019-09-15 22:57:47 +0200 |
|---|---|---|
| committer | Ricardo Wurmus <rekado@elephly.net> | 2019-09-15 22:57:47 +0200 |
| commit | d80a15696bf07a35b523c062a592a4b210bd3fdf (patch) | |
| tree | 5c26cfec508abd3913f8229c0e90fae0ab5e2256 | |
| parent | 2a360cf6acde00f96dcca8bf6dcc2f4fa1563da1 (diff) | |
| download | patches-d80a15696bf07a35b523c062a592a4b210bd3fdf.tar patches-d80a15696bf07a35b523c062a592a4b210bd3fdf.tar.gz | |
gnu: Add r-variancepartition.
* gnu/packages/bioconductor.scm (r-variancepartition): New variable.
| -rw-r--r-- | gnu/packages/bioconductor.scm | 41 |
1 files changed, 41 insertions, 0 deletions
diff --git a/gnu/packages/bioconductor.scm b/gnu/packages/bioconductor.scm index ec3451b704..7ca6788dd8 100644 --- a/gnu/packages/bioconductor.scm +++ b/gnu/packages/bioconductor.scm @@ -6006,3 +6006,44 @@ same genome coordinate system.") "This package is designed to conduct transcriptome analysis for tiling arrays based on fast wavelet-based functional models.") (license license:gpl2+))) + +(define-public r-variancepartition + (package + (name "r-variancepartition") + (version "1.14.0") + (source + (origin + (method url-fetch) + (uri (bioconductor-uri "variancePartition" version)) + (sha256 + (base32 + "1ycapwb2mq57xibrzzjz9zwxqz4nwz9f3n5gskhlr5vcs7irkjd6")))) + (properties + `((upstream-name . "variancePartition"))) + (build-system r-build-system) + (propagated-inputs + `(("r-biobase" ,r-biobase) + ("r-colorramps" ,r-colorramps) + ("r-doparallel" ,r-doparallel) + ("r-foreach" ,r-foreach) + ("r-ggplot2" ,r-ggplot2) + ("r-gplots" ,r-gplots) + ("r-iterators" ,r-iterators) + ("r-limma" ,r-limma) + ("r-lme4" ,r-lme4) + ("r-lmertest" ,r-lmertest) + ("r-mass" ,r-mass) + ("r-pbkrtest" ,r-pbkrtest) + ("r-progress" ,r-progress) + ("r-reshape2" ,r-reshape2) + ("r-scales" ,r-scales))) + (home-page "https://bioconductor.org/packages/variancePartition/") + (synopsis "Analyze variation in gene expression experiments") + (description + "This is a package providing tools to quantify and interpret multiple +sources of biological and technical variation in gene expression experiments. +It uses a linear mixed model to quantify variation in gene expression +attributable to individual, tissue, time point, or technical variables. The +package includes dream differential expression analysis for repeated +measures.") + (license license:gpl2+))) |