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01/06: gnu: Add r-scannotatr.


From: guix-commits
Subject: 01/06: gnu: Add r-scannotatr.
Date: Tue, 15 Mar 2022 18:08:56 -0400 (EDT)

rekado pushed a commit to branch master
in repository guix.

commit fdbc472bd1c8b15195192196f1ef049fe3094110
Author: zimoun <zimon.toutoune@gmail.com>
AuthorDate: Tue Mar 8 20:06:12 2022 +0100

    gnu: Add r-scannotatr.
    
    * gnu/packages/bioconductor.scm (r-scannotatr): New variable.
---
 gnu/packages/bioconductor.scm | 37 +++++++++++++++++++++++++++++++++++++
 1 file changed, 37 insertions(+)

diff --git a/gnu/packages/bioconductor.scm b/gnu/packages/bioconductor.scm
index bd77cc21d4..2161a162ab 100644
--- a/gnu/packages/bioconductor.scm
+++ b/gnu/packages/bioconductor.scm
@@ -4387,6 +4387,43 @@ differential expression analysis, RNAseq data and 
related problems.")
     ;; Any version of the LGPL
     (license license:lgpl3+)))
 
+(define-public r-scannotatr
+  (package
+    (name "r-scannotatr")
+    (version "1.0.0")
+    (source
+     (origin
+       (method url-fetch)
+       (uri (bioconductor-uri "scAnnotatR" version))
+       (sha256
+        (base32 "08jq04ckjw8a5y753almc5bl8vnn4j6qp2zb7bb9w3ql3ddy7b21"))))
+    (properties `((upstream-name . "scAnnotatR")))
+    (build-system r-build-system)
+    (propagated-inputs
+     (list r-annotationhub
+           r-ape
+           r-caret
+           r-data-tree
+           r-dplyr
+           r-e1071
+           r-ggplot2
+           r-kernlab
+           r-proc
+           r-rocr
+           r-seurat
+           r-singlecellexperiment
+           r-summarizedexperiment))
+    (native-inputs (list r-knitr))
+    (home-page "https://github.com/grisslab/scAnnotatR";)
+    (synopsis "Pretrained models for prediction on single cell RNA-sequencing 
data")
+    (description
+     "This package comprises a set of pretrained machine learning models to
+predict basic immune cell types.  This enables to quickly get a first
+annotation of the cell types present in the dataset without requiring prior
+knowledge.  The package also lets you train using own models to predict new
+cell types based on specific research needs.")
+    (license license:expat)))
+
 (define-public r-scdblfinder
   (package
     (name "r-scdblfinder")



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