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[bug#55124,2/2] gnu: Add r-adimpute.

Message ID 20220426113623.15268-2-madalinionel.patrascu@mdc-berlin.de
State New
Headers show
Series [bug#55124,1/2] gnu: Add r-saver. | expand


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Commit Message

Mădălin Ionel Patrașcu April 26, 2022, 11:36 a.m. UTC
* gnu/packages/bioconductor.scm (r-adimpute): New variable.
 gnu/packages/bioconductor.scm | 48 +++++++++++++++++++++++++++++++++++
 1 file changed, 48 insertions(+)
diff mbox series


diff --git a/gnu/packages/bioconductor.scm b/gnu/packages/bioconductor.scm
index fa862d736f..a861c2e576 100644
--- a/gnu/packages/bioconductor.scm
+++ b/gnu/packages/bioconductor.scm
@@ -1616,6 +1616,54 @@  (define-public r-adam
 functionally associated genes} (GFAG).")
     (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
+novel methods to address this issue:
+@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
     (name "r-aneufinder")