Added spatialproteomics

[MeyerBender]

Checklist for adding packages

Mandatory

Name of the tool: spatialproteomics

Short description: Spatialproteomics is an interoperable toolbox for analyzing highly multiplexed fluorescence image data. This analysis involves a sequence of steps, including segmentation, image processing, marker quantification, cell type classification, and neighborhood analysis.

How does the package use scverse data structures (please describe in a few sentences): Spatialproteomics has a backend fully based on spatialdata. It also offers an alternative backend based on xarray (to enable synchronization of shared data dimensions beyond the current capabilities of spatialdata), from which users can export data into anndata or spatialdata format.

• The code is publicly available under an OSI-approved license
• The package provides versioned releases
• The package can be installed from a standard registry (e.g. PyPI, conda-forge, bioconda)
• Automated tests cover essential functions of the package and a reasonable range of inputs and conditions
• Continuous integration (CI) automatically executes these tests on each push or pull request
• The package provides API documentation via a website or README
• The package uses scverse datastructures where appropriate (i.e. AnnData, MuData or SpatialData and their modality-specific extensions)
• I am an author or maintainer of the tool and agree on listing the package on the scverse website

Recommended

• Please announce this package on scverse communication channels (zulip, discourse, twitter)

• Please tag the author(s) these announcements. Handles (e.g. @scverse_team) to include are:

  • Zulip: Matthias Meyer-Bender, Harald Voehringer
  • Bluesky: @matthiasmeybe.bsky.social
  • Twitter: @MatthiasMeyBe, @harald_voeh

• The package provides tutorials (or "vignettes") that help getting users started quickly

• The package uses the scverse cookiecutter template.

[mikkelnrasmussen]

Hi @MeyerBender,

Thanks for submitting this very cool package! Everything looks good to me, and I really appreciate the thoroughness you’ve put into the documentation, tutorials, tests, and overall structure.

Best,
Mikkel