openDVP - community empowered Deep Visual Proteomics

openDVP - community empowered Deep Visual Proteomics#

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opendvp is a python package containing different tools enabling users to perform deep visual proteomics. To perform quality control and image analysis of multiplex immunofluorescence. Also to integrate imaging datasets with proteomic datasets with Spatialdata. Lastly, it contains a powerful toolkit for label-free downstream proteomic analysis.

It is a package that leverages the scverse ecosystem, designed for easy interoperability with anndata, scanpy, decoupler, scimap, and other related packages.

Getting started#

openDVP is a framework that has both experimental and software aspects.

Please check our API documentation for detailed functionalities.

Installation#

You need at least Python 3.10 installed.

First time trying python?#

Click here for extra instructions

  1. IF you need software to run jupyter notebooks, I suggest you install Visual Studio Code.

  2. Install uv, a python environment manager, following instructions at installing uv.

  3. Create a local folder you would like to use for your project, and open that folder it in VSCode

  4. Open the terminal and run:

uv init

your project folder will be created, then run:

uv add opendvp

OR to install spatialdata capabilities:

uv add 'opendvp[spatialdata]'

There are three alternatives to install openDVP:#

  1. Install the latest stable release from PyPI with minimal dependencies:

pip install openDVP

  1. Install the latest stable release from PyPI with spatialdata capabilities:

pip install 'openDVP[spatialdata]'

  1. Install the latest development version from github:

pip install git+https://github.com/CosciaLab/openDVP.git@main

Tutorials#

Contact#

For questions about openDVP and the DVP workflow you are very welcome to post a message in the discussion board. For issues with the software, please post issues on Github Issues.

Citation#

Not yet available.

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