[Add package] dvp-io

[lucas-diedrich]

Add dvp-io as ecosystem package.

Checklist

Mandatory

Name of the tool: dvp-io

Short description: Read/write functions to and from spatialdata for Deep Visual Proteomics experiments.
dvp-io implements read/write functionalities for spatial proteomics data generated with the Deep Visual Proteomics workflow (DVP), which combines image analysis, laser microdissection, and MS-based proteomics. The package enables users to read various microscopy image formats and ingest them into spatialdata, export cell segmentation masks for laser microdissection, and integrate proteomics measurements with image modalities and annotations.

How does the package use scverse data structures (please describe in a few sentences):
The package enables the ingestion of DVP data into the spatialdata framework (especially Image2DModel, ShapesModel, and TablesModel) and heavily uses spatialdata's functionalities.

• 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 [^1]
• Continuous integration (CI) automatically executes these tests on each push or pull request [^2]
• The package provides API documentation via a website or README[^3]
• 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: @Lucas Diedrich
  • Discourse:
  • Mastodon:
  • Bluesky: @mannlab.bsky.social @lucas-diedrich.bsky.social
  • Twitter: @labs_mann @lucas__1406

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

• The package uses the scverse cookiecutter template.