From a45dfa8a731c9ba2626ee7ca19e7d61f2e82925d Mon Sep 17 00:00:00 2001 From: Mădălin Ionel Patrașcu Date: Tue, 26 Apr 2022 13:36:23 +0200 Subject: gnu: Add r-adimpute. * gnu/packages/bioconductor.scm (r-adimpute): New variable. Signed-off-by: Ricardo Wurmus --- gnu/packages/bioconductor.scm | 49 +++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 49 insertions(+) (limited to 'gnu/packages/bioconductor.scm') diff --git a/gnu/packages/bioconductor.scm b/gnu/packages/bioconductor.scm index 67ee6079c6..f55416ef43 100644 --- a/gnu/packages/bioconductor.scm +++ b/gnu/packages/bioconductor.scm @@ -1664,6 +1664,55 @@ expression and fold change can be easily seen with aid of the plots made with 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") -- cgit v1.2.3