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| author | Navid Afkhami <navid.afkhami@mdc-berlin.de> | 2023-03-10 16:16:12 +0000 |
|---|---|---|
| committer | Ricardo Wurmus <rekado@elephly.net> | 2023-03-10 17:47:24 +0100 |
| commit | f7682c247504d252cf86b274ffe7b8f62670b497 (patch) | |
| tree | 76d38c9d0e4d04ae77548520fa65a76a208035b6 | |
| parent | f437b1118014b813b7c6cf8b9b0deb87108b807e (diff) | |
| download | guix-f7682c247504d252cf86b274ffe7b8f62670b497.tar guix-f7682c247504d252cf86b274ffe7b8f62670b497.tar.gz | |
gnu: Add r-hdcytodata.
* gnu/packages/bioconductor.scm (r-hdcytodata): New variable.
Co-authored-by: Ricardo Wurmus <rekado@elephly.net>
| -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 d603bd42c1..5ed8eda3b9 100644 --- a/gnu/packages/bioconductor.scm +++ b/gnu/packages/bioconductor.scm @@ -1482,6 +1482,47 @@ genomation package. Included are Chip Seq, Methylation and Cage data, downloaded from Encode.") (license license:gpl3+))) +(define-public r-hdcytodata + (package + (name "r-hdcytodata") + (version "1.18.0") + (source (origin + (method url-fetch) + (uri (bioconductor-uri "HDCytoData" version 'experiment)) + (sha256 + (base32 + "1fn8q6ds10z3ymdarkfyh88pcqnrry9yhzammp84vf86f0bl8mrc")))) + (properties `((upstream-name . "HDCytoData"))) + (build-system r-build-system) + (arguments + (list + #:phases + '(modify-phases %standard-phases + (add-after 'unpack 'set-HOME + (lambda _ + (setenv "HOME" "/tmp"))) + (add-after 'unpack 'avoid-internet-access + (lambda _ + (setenv "GUIX_BUILD" "yes") + (substitute* "R/zzz.R" + (("createHubAccessors.*" m) + (string-append + "if (Sys.getenv(\"GUIX_BUILD\") == \"\") {" m "}")))))))) + (propagated-inputs + (list r-experimenthub r-flowcore r-summarizedexperiment)) + (native-inputs (list r-knitr)) + (home-page "https://github.com/lmweber/HDCytoData") + (synopsis + "Set of high-dimensional flow cytometry and mass cytometry benchmark datasets") + (description + "HDCytoData contains a set of high-dimensional cytometry benchmark +datasets. These datasets are formatted into SummarizedExperiment and flowSet +Bioconductor object formats, including all required metadata. Row metadata +includes sample IDs, group IDs, patient IDs, reference cell population or +cluster labels and labels identifying spiked in cells. Column metadata +includes channel names, protein marker names, and protein marker classes.") + (license license:expat))) + (define-public r-italicsdata (package (name "r-italicsdata") |