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authorRicardo Wurmus <rekado@elephly.net>2018-08-29 17:05:46 +0200
committerRicardo Wurmus <rekado@elephly.net>2018-08-29 17:06:13 +0200
commitc7fe888b424faec05a0d55e8b9321d6852ffb1f2 (patch)
tree803f5f067fa7c08a13943440ca91a954475a3848
parent22b770ce0003b7d6fe98299292f8f5c0569f0712 (diff)
downloadguix-c7fe888b424faec05a0d55e8b9321d6852ffb1f2.tar
guix-c7fe888b424faec05a0d55e8b9321d6852ffb1f2.tar.gz
gnu: Add python-scanpy.
* gnu/packages/bioinformatics.scm (python-scanpy): New variable.
-rw-r--r--gnu/packages/bioinformatics.scm36
1 files changed, 36 insertions, 0 deletions
diff --git a/gnu/packages/bioinformatics.scm b/gnu/packages/bioinformatics.scm
index cb3c4bc1fd..3c300e48e9 100644
--- a/gnu/packages/bioinformatics.scm
+++ b/gnu/packages/bioinformatics.scm
@@ -13458,3 +13458,39 @@ conversions, region filtering, FASTA sequence extraction and more.")
spliced (back-spliced) sequencing reads, indicative of circular RNA (circRNA)
in RNA-seq data.")
(license license:gpl3))))
+
+(define-public python-scanpy
+ (package
+ (name "python-scanpy")
+ (version "1.2.2")
+ (source
+ (origin
+ (method url-fetch)
+ (uri (pypi-uri "scanpy" version))
+ (sha256
+ (base32
+ "1ak7bxms5a0yvf65prppq2g38clkv7c7jnjbnfpkh3xxv7q512jz"))))
+ (build-system python-build-system)
+ (propagated-inputs
+ `(("python-anndata" ,python-anndata)
+ ("python-igraph" ,python-igraph)
+ ("python-numba" ,python-numba)
+ ("python-joblib" ,python-joblib)
+ ("python-natsort" ,python-natsort)
+ ("python-networkx" ,python-networkx)
+ ("python-statsmodels" ,python-statsmodels)
+ ("python-scikit-learn" ,python-scikit-learn)
+ ("python-matplotlib" ,python-matplotlib)
+ ("python-pandas" ,python-pandas)
+ ("python-scipy" ,python-scipy)
+ ("python-seaborn" ,python-seaborn)
+ ("python-h5py" ,python-h5py)
+ ("python-tables" ,python-tables)))
+ (home-page "http://github.com/theislab/scanpy")
+ (synopsis "Single-Cell Analysis in Python.")
+ (description "Scanpy is a scalable toolkit for analyzing single-cell gene
+expression data. It includes preprocessing, visualization, clustering,
+pseudotime and trajectory inference and differential expression testing. The
+Python-based implementation efficiently deals with datasets of more than one
+million cells.")
+ (license license:bsd-3)))