Reproducible Research Platform Desktop Player Bundle

RRP Desktop

Reproducible Research Platform (RRP) project including a desktop environment

Overview

This RRP project repository demonstrates an alternative integrated development environment. It provides XFCE (or other desktop environments) for worfklows that depend on tools with graphical user interfaces.

The main outcome of this example is:

Example of napari as a GUI for the interaction with microscopy data.

Example of using a MATLAB based tool TracX.

Example of using the pyPOCQuant GUI.

This repository utilizes TracX [1], pyPOCQUANT [2], napari [3] for image analysis. Detailed explanations of these tools can be found in their respective publications.

Features

Integration with RRP and openBIS ELN-LIMS: Mounts data (microscopy data) from the research data management system openBIS in RRP for direct use.

Desktop: Keeping user habits allowing to work in a Desktop environment.

TracX, pyPOCQUANT, napari: Demonstrates workflows with GUIs for image processing and analysis.

Installation

Prerequisites

Local Docker installation.

Steps

Download and extract the .zip file

Run the play script for your operating system

Linux / macOS: play

Windows: play.bat or play.ps1

Usage

In RRP start the Desktop environment.

Workflow Overview

Visualization: View microscopy images with napari. This example opens data mounted from the RDMS openBIS for visualization. Start a Terminal and type:

python project/run_napari.py

Image processing: Quantify signals from images of lateral flow assays (e.g. Covid tests). This example opens data mounted from the RDMS openBIS for analysis. Start a Terminal and type the command below. It starts a GUI. (i) Click on "File>Load settings from file" and select the .config file from /home/jovyan/project/analysis/. (II) enter this path to Enter the input folder. (iii) Click "Run". The results will be available in a subfolder called pipeline per default shortly after.

python project/run_pypocquant.py

Cell tracking: Track cells from microscopy images and segmentation results (processed_data). This example opens data mounted from the RDMS openBIS for analysis. Start a Terminal and type the command below. It starts a GUI. (i) Click on Load configuration and select the ~/projectTracX_Yeast_Demo_Project.xml file. (ii) Click on Test run to track the cells and open a viewer for inspection.

python project/run_tracx.py

Directory Structure

├── .binder/ # Environment specifications, Python version, packages (napari) etc.
├── .rrp/ # Specification of openBIS server and required data from RDMS openBIS ELN-LIMS (e.g. microscopy data)
├── LICENSE # License
├── README.md # This file
├── run_napari.py # Script to demonstrate napari workflow
├── run_pypocquant.py # Script to demonstrate pyPOCQuant workflow
├── run_tracx.py # Script to demonstrate TracX workflow
└── TracX_Yeast_Demo_Project.xml # Demo config file for TracX

Contributing

We welcome contributions to improve this repository! Please follow these steps:

Fork the repository.

Create a new branch for your feature or bug fix.

Submit a pull request with a clear description of your changes.

Authors and acknowledgment

Andreas P. Cuny, ETH Zurich initial implementation

Additionally, we acknowledge https://github.com/jupyterhub/jupyter-remote-desktop-proxy

License

This project is licensed under the Apache 2.0 License. See LICENSE file for details.

Copyright © 2020-2025 ETH Zurich, Andreas P. Cuny, D-BSSE, CSB Group

References

1: Cuny, A. P., Ponti, A., Kündig, T., Rudolf, F. & Stelling, J. Cell region fingerprints enable highly precise single-cell tracking and lineage reconstruction. Nat. Methods 2021.10.26.465883 (2022) doi:https://doi.org/10.1038/s41592-022-01603-2.

2: Cuny, A. P., Rudolf, F. & Ponti, A. pyPOCQuant — A tool to automatically quantify Point-Of-Care Tests from images. SoftwareX 15, 100710 (2021).

3: Chiu, C.-L. & Clack, N. napari: a Python Multi-Dimensional Image Viewer Platform for the Research Community. Microsc. Microanal. 28, 1576–1577 (2022).