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