~ruther/guix-local

15c41340672a7da29d016e0bef502d1806debfd4 — Kjartan Oli Agustsson 1 year, 14 days ago 492035d
gnu: python-scanorama: Run guix style

* gnu/packages/bioinformatics.scm (python-scanorama): Run guix style.

Change-Id: I43bfbe845f6e54dab94c6e0055ee811f70026ab4
Signed-off-by: Sharlatan Hellseher <sharlatanus@gmail.com>
1 files changed, 17 insertions(+), 19 deletions(-)

M gnu/packages/bioinformatics.scm
M gnu/packages/bioinformatics.scm => gnu/packages/bioinformatics.scm +17 -19
@@ 20668,27 20668,25 @@ matrices.")
  (package
    (name "python-scanorama")
    (version "1.7.2")
    (source (origin
              (method url-fetch)
              (uri (pypi-uri "scanorama" version))
              (sha256
               (base32
                "0il7bf4c7vli2dm2jx7dskh3ymgv8nmk0y90jzgfrnqjzh250x5w"))))
    (source
     (origin
       (method url-fetch)
       (uri (pypi-uri "scanorama" version))
       (sha256
        (base32 "0il7bf4c7vli2dm2jx7dskh3ymgv8nmk0y90jzgfrnqjzh250x5w"))))
    (build-system pyproject-build-system)
    (propagated-inputs
     (list python-annoy
           python-fbpca
           python-geosketch
           python-intervaltree
           python-matplotlib
           python-numpy
           python-scikit-learn
           python-scipy))
    (native-inputs
     (list python-setuptools
           python-wheel))
    (propagated-inputs (list python-annoy
                             python-fbpca
                             python-geosketch
                             python-intervaltree
                             python-matplotlib
                             python-numpy
                             python-scikit-learn
                             python-scipy))
    (native-inputs (list python-setuptools python-wheel))
    (home-page "https://github.com/brianhie/scanorama")
    (synopsis "Panoramic stitching of heterogeneous single cell transcriptomic data")
    (synopsis
     "Panoramic stitching of heterogeneous single cell transcriptomic data")
    (description
     "Scanorama enables batch-correction and integration of heterogeneous
scRNA-seq datasets, which is described in the paper \"Efficient integration of