_            _    _        _         _
      /\ \         /\ \ /\ \     /\_\      / /\
      \_\ \       /  \ \\ \ \   / / /     / /  \
      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
 / / /      / / /___/ / /     \ \ \ /_/\__/ / /
/_/ /      / / /____\/ /       \ \_\\ \/___/ /
\_\/       \/_________/         \/_/ \_____\/
r-spatialexperimentio 1.2.0
Propagated dependencies: r-spatialexperiment@1.18.1 r-singlecellexperiment@1.30.1 r-s4vectors@0.46.0 r-purrr@1.0.4 r-dropletutils@1.28.0 r-data-table@1.17.4 r-arrow@21.0.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://github.com/estellad/SpatialExperimentIO
Licenses: Artistic License 2.0
Synopsis: Read in Xenium, CosMx, MERSCOPE or STARmapPLUS data as SpatialExperiment object
Description:

Read in imaging-based spatial transcriptomics technology data. Current available modules are for Xenium by 10X Genomics, CosMx by Nanostring, MERSCOPE by Vizgen, or STARmapPLUS from Broad Institute. You can choose to read the data in as a SpatialExperiment or a SingleCellExperiment object.

r-spatialfeatureexperiment 1.12.1
Propagated dependencies: r-zeallot@0.2.0 r-terra@1.8-50 r-summarizedexperiment@1.38.1 r-spdep@1.3-11 r-spatialreg@1.3-6 r-spatialexperiment@1.18.1 r-singlecellexperiment@1.30.1 r-sfheaders@0.4.4 r-sf@1.0-21 r-s4vectors@0.46.0 r-rlang@1.1.6 r-rjson@0.2.23 r-matrix@1.7-3 r-lifecycle@1.0.4 r-ebimage@4.50.0 r-dropletutils@1.28.0 r-data-table@1.17.4 r-biocparallel@1.42.0 r-biocneighbors@2.2.0 r-biocgenerics@0.54.0 r-biobase@2.68.0
Channel: guix-bioc
Location: guix-bioc/packages/s.scm (guix-bioc packages s)
Home page: https://github.com/pachterlab/SpatialFeatureExperiment
Licenses: Artistic License 2.0
Synopsis: Integrating SpatialExperiment with Simple Features in sf
Description:

This package provides a new S4 class integrating Simple Features with the R package sf to bring geospatial data analysis methods based on vector data to spatial transcriptomics. Also implements management of spatial neighborhood graphs and geometric operations. This pakage builds upon SpatialExperiment and SingleCellExperiment, hence methods for these parent classes can still be used.

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