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gnu: Add r-scgate.
* gnu/packages/bioconductor.scm (r-scgate): New variable. Change-Id: I441bbea5a68882f5f619dea72abdf84619c9d02f
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@ -10314,6 +10314,49 @@ (define-public r-scdblfinder
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comprehensive scDblFinder method.")
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(license license:gpl3)))
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;; This is a CRAN package, but it depends on packages from Bioconductor.
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(define-public r-scgate
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(package
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(name "r-scgate")
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(version "1.6.0")
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(source
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(origin
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(method url-fetch)
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(uri (cran-uri "scGate" version))
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(sha256
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(base32 "0h12d36zjc6fvxbhkxrzbpvw49z9fgyn1jc941q70ajw1yqi2hhh"))))
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(properties `((upstream-name . "scGate")))
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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-dplyr
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r-ggplot2
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r-ggridges
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r-patchwork
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r-reshape2
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r-seurat
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r-ucell))
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(native-inputs (list r-knitr))
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(home-page "https://github.com/carmonalab/scGate")
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(synopsis
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"Marker-based cell type purification for single-cell sequencing data")
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(description
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"This package provides a method to purify a cell type or cell population
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of interest from heterogeneous datasets. scGate package automatizes
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marker-based purification of specific cell populations, without requiring
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training data or reference gene expression profiles. scGate takes as input a
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gene expression matrix stored in a Seurat object and a @acronym{GM, gating
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model}, consisting of a set of marker genes that define the cell population of
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interest. It evaluates the strength of signature marker expression in each
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cell using the rank-based method UCell, and then performs @acronym{kNN,
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k-nearest neighbor} smoothing by calculating the mean UCell score across
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neighboring cells. kNN-smoothing aims at compensating for the large degree of
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sparsity in scRNAseq data. Finally, a universal threshold over kNN-smoothed
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signature scores is applied in binary decision trees generated from the
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user-provided gating model, to annotate cells as either “pure” or “impure”,
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with respect to the cell population of interest.")
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(license license:gpl3)))
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;; This is a CRAN package, but it depends on packages from Bioconductor.
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(define-public r-scistreer
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(package
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