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author | Ricardo Wurmus <rekado@elephly.net> | 2019-03-29 18:10:46 +0100 |
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committer | Ricardo Wurmus <rekado@elephly.net> | 2019-03-29 18:10:46 +0100 |
commit | ffe7029babb40481f50cf931b28e92c8f74dfe01 (patch) | |
tree | 8288aec8af1bc51fc2d8143a32b9170f843c7a9c /gnu/packages/bioconductor.scm | |
parent | f31e10f82e3bcfa74901f87b4a3d951758861804 (diff) | |
download | patches-ffe7029babb40481f50cf931b28e92c8f74dfe01.tar patches-ffe7029babb40481f50cf931b28e92c8f74dfe01.tar.gz |
gnu: Add r-aucell.
* gnu/packages/bioconductor.scm (r-aucell): New variable.
Diffstat (limited to 'gnu/packages/bioconductor.scm')
-rw-r--r-- | gnu/packages/bioconductor.scm | 35 |
1 files changed, 35 insertions, 0 deletions
diff --git a/gnu/packages/bioconductor.scm b/gnu/packages/bioconductor.scm index 2d74d2628c..6a7c98f625 100644 --- a/gnu/packages/bioconductor.scm +++ b/gnu/packages/bioconductor.scm @@ -3551,3 +3551,38 @@ text files).") "This package provides a framework for allele-specific expression investigation using RNA-seq data.") (license license:gpl3))) + +(define-public r-aucell + (package + (name "r-aucell") + (version "1.4.1") + (source + (origin + (method url-fetch) + (uri (bioconductor-uri "AUCell" version)) + (sha256 + (base32 + "1kdrs0521cyb8wlc4i3idfprrcy2f9w6kl56hfa94n0brmx62ya9")))) + (properties `((upstream-name . "AUCell"))) + (build-system r-build-system) + (propagated-inputs + `(("r-data-table" ,r-data-table) + ("r-gseabase" ,r-gseabase) + ("r-mixtools" ,r-mixtools) + ("r-r-utils" ,r-r-utils) + ("r-shiny" ,r-shiny) + ("r-summarizedexperiment" ,r-summarizedexperiment))) + (home-page "https://bioconductor.org/packages/AUCell/") + (synopsis "Analysis of gene set activity in single-cell RNA-seq data") + (description + "AUCell allows to identify cells with active gene sets (e.g. signatures, +gene modules, etc) in single-cell RNA-seq data. AUCell uses the @dfn{Area +Under the Curve} (AUC) to calculate whether a critical subset of the input +gene set is enriched within the expressed genes for each cell. The +distribution of AUC scores across all the cells allows exploring the relative +expression of the signature. Since the scoring method is ranking-based, +AUCell is independent of the gene expression units and the normalization +procedure. In addition, since the cells are evaluated individually, it can +easily be applied to bigger datasets, subsetting the expression matrix if +needed.") + (license license:gpl3))) |