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gnu: Add r-cytonorm.
* gnu/packages/bioinformatics.scm (r-cytonorm): New variable.
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@ -14903,3 +14903,42 @@ (define-public r-spectre
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integration, exploration, and analysis of high-dimensional single-cell
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cytometry and imaging data.")
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(license license:expat))))
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(define-public r-cytonorm
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(let ((commit "e4b9d343ee65db3c422800f1db3e77c25abde987")
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(revision "1"))
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(package
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(name "r-cytonorm")
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(version (git-version "0.0.7" revision commit))
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(source
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(origin
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(method git-fetch)
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(uri (git-reference
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(url "https://github.com/saeyslab/CytoNorm")
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(commit commit)))
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(file-name (git-file-name name version))
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(sha256
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(base32
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"0h2rdy15i4zymd4dv60n5w0frbsdbmzpv99dgm0l2dn041qv7fah"))))
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(properties `((upstream-name . "CytoNorm")))
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(build-system r-build-system)
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(propagated-inputs
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`(("r-cytoml" ,r-cytoml)
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("r-dplyr" ,r-dplyr)
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("r-emdist" ,r-emdist)
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("r-flowcore" ,r-flowcore)
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("r-flowsom" ,r-flowsom)
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("r-flowworkspace" ,r-flowworkspace)
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("r-ggplot2" ,r-ggplot2)
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("r-gridextra" ,r-gridextra)
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("r-pheatmap" ,r-pheatmap)
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("r-stringr" ,r-stringr)))
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(home-page "https://github.com/saeyslab/CytoNorm")
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(synopsis "Normalize cytometry data measured across multiple batches")
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(description
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"This package can be used to normalize cytometry samples when a control
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sample is taken along in each of the batches. This is done by first
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identifying multiple clusters/cell types, learning the batch effects from the
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control samples and applying quantile normalization on all markers of
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interest.")
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(license license:gpl2+))))
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