opendvp 0.5.2

open-sourced Deep Visual Proteomics toolkit

OpenDVP

OpenDVP is an open-source framework designed to support Deep Visual Profiling (DVP) across multiple modalities using community-supported tools.

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Overview

OpenDVP empowers researchers to perform Deep Visual Proteomics using open-source software. It integrates with community data standards such as AnnData and SpatialData to ensure interoperability with popular analysis tools like Scanpy, Squidpy, and Scimap.

This repository outlines four major use cases for OpenDVP:

1. Image Processing and Analysis
2. Matrix Processing and Analysis
3. Quality Control with QuPath and Napari
4. Exporting to LMD (Laser Microdissection)

Installation

You can install openDVP via pip:

pip install opendvp

If you want to install with spatialdata capacity please run:

pip install 'opendvp[spatialdata]'

Motivation

Deep Visual Profiling (DVP) combines high-dimensional imaging, spatial analysis, and machine learning to extract complex biological insights from tissue samples. However, many current DVP tools are locked into proprietary formats, restricted software ecosystems, or closed-source pipelines that limit reproducibility, accessibility, and community collaboration.

• Work transparently across modalities and analysis environments
• Contribute improvements back to a growing ecosystem
• Avoid vendor lock-in for critical workflows

Community & Discussions

We are excited to hear from you and together we can improve spatial protemics. We welcome questions, feedback, and community contributions!
Join the conversation in the GitHub Discussions tab.

Citation

Please cite the corresponding bioarxiv for now, Coming Soon!

Demo data

A comprehensive tutorial of openDVP features is on the works, to test it, feel free to download our demo data.

https://zenodo.org/records/15397560