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author | Mădălin Ionel Patrașcu <madalinionel.patrascu@mdc-berlin.de> | 2022-06-17 11:29:29 +0200 |
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committer | Ricardo Wurmus <rekado@elephly.net> | 2022-06-30 15:35:27 +0200 |
commit | c6d792f34cc1af122d9089451a2b784d405d1923 (patch) | |
tree | 716d589aa4662673645bc44fefcc6db80767e1af /gnu/packages/bioconductor.scm | |
parent | dd74da619059465d67a804948e750c0470cfc6f8 (diff) | |
download | guix-c6d792f34cc1af122d9089451a2b784d405d1923.tar.gz |
gnu: Add r-amaretto.
* gnu/packages/bioconductor.scm (r-amaretto): New variable.
Diffstat (limited to 'gnu/packages/bioconductor.scm')
-rw-r--r-- | gnu/packages/bioconductor.scm | 52 |
1 files changed, 52 insertions, 0 deletions
diff --git a/gnu/packages/bioconductor.scm b/gnu/packages/bioconductor.scm index 20f277b119..28000c70f1 100644 --- a/gnu/packages/bioconductor.scm +++ b/gnu/packages/bioconductor.scm @@ -2011,6 +2011,58 @@ conditions or various species. @code{AMOUNTAIN} aims to search active modules in multi-layer WGCN using a continuous optimization approach.") (license license:gpl2+))) +(define-public r-amaretto + (package + (name "r-amaretto") + (version "1.12.0") + (source (origin + (method url-fetch) + (uri (bioconductor-uri "AMARETTO" version)) + (sha256 + (base32 + "111dk19b9910icksyr592cvhc5gwvgknr5q4887j9yxbajd7hcmx")))) + (properties `((upstream-name . "AMARETTO"))) + (build-system r-build-system) + (propagated-inputs + (list r-biocfilecache + r-callr + r-circlize + r-complexheatmap + r-curatedtcgadata + r-doparallel + r-dplyr + r-dt + r-foreach + r-ggplot2 + r-glmnet + r-gridextra + r-httr + r-impute + r-knitr + r-limma + r-matrix + r-matrixstats + r-multiassayexperiment + r-rcpp + r-readr + r-reshape2 + r-rmarkdown + r-tibble)) + (native-inputs (list r-knitr)) + (home-page "https://bioconductor.org/packages/AMARETTO") + (synopsis "Regulatory network inference and driver gene evaluation") + (description + "This package @code{AMARETTO} represents an algorithm that integrates copy +number, DNA methylation and gene expression data to identify a set of driver +genes by analyzing cancer samples and connects them to clusters of co-expressed +genes, which we define as modules. @code{AMARETTO} can be applied in a pancancer +setting to identify cancer driver genes and their modules on multiple cancer +sites. @code{AMARETTO} captures modules enriched in angiogenesis, cell cycle +and EMT, and modules that accurately predict survival and molecular subtypes. +This allows @code{AMARETTO} to identify novel cancer driver genes directing +canonical cancer pathways.") + (license license:asl2.0))) + (define-public r-aneufinder (package (name "r-aneufinder") |