gnu: Add r-adimpute.

* gnu/packages/bioconductor.scm (r-adimpute): New variable.

Signed-off-by: Ricardo Wurmus <rekado@elephly.net>
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Mădălin Ionel Patrașcu 2022-04-26 13:36:23 +02:00 committed by Ricardo Wurmus
parent b7cb4e2822
commit a45dfa8a73
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@ -1664,6 +1664,55 @@ (define-public r-adamgui
the @code{GFAGpathUi} function.")
(license license:gpl2+)))
(define-public r-adimpute
(package
(name "r-adimpute")
(version "1.4.0")
(source (origin
(method url-fetch)
(uri (bioconductor-uri "ADImpute" version))
(sha256
(base32
"1bkq1hd8sqg9r28r70a9vd3gb2nsmg6dybf002d621p88cdfjib2"))))
(properties `((upstream-name . "ADImpute")))
(build-system r-build-system)
(propagated-inputs
(list r-biocparallel
r-checkmate
r-data-table
r-drimpute
r-kernlab
r-mass
r-matrix
r-rsvd
r-s4vectors
r-saver
r-singlecellexperiment
r-summarizedexperiment))
(native-inputs (list r-knitr))
(home-page "https://bioconductor.org/packages/ADImpute")
(synopsis "Adaptive computational prediction for dropout imputations")
(description
"@dfn{Single-cell RNA sequencing} (scRNA-seq) methods are typically
unable to quantify the expression levels of all genes in a cell, creating a
need for the computational prediction of missing values (dropout imputation).
Most existing dropout imputation methods are limited in the sense that they
exclusively use the scRNA-seq dataset at hand and do not exploit external
gene-gene relationship information. The @code{ADImpute} package proposes two
methods to address this issue:
@enumerate
@item a gene regulatory network-based approach using gene-gene relationships
learnt from external data;
@item a baseline approach corresponding to a sample-wide average.
@end enumerate
@code{ADImpute} implements these novel methods and also combines them with
existing imputation methods like @code{DrImpute} and @code{SAVER}.
@code{ADImpute} can learn the best performing method per gene and combine the
results from different methods into an ensemble.")
(license license:gpl3+)))
(define-public r-aneufinder
(package
(name "r-aneufinder")