Reproducible Research Platform Demo Project Player Bundle

Reproducible Research Platform Project Demo A small study estimating the population growth rate from microscopy images using basic image analysis. Overview This RRP project repository is a simple demonstration project that illustrates how to mounted data from the research data management system (RDMS) openBIS ELN-LIMS. In our example micrsocpy data is managed in the RDMS and annotated with respective metadata. Using their permID the data is directly available in the RRP project for analysis and our mini study. The main outcome of this example is: How to perform a small study within RRP with the example of determining the population growth rate from microscopy images. The data originates from [1], and results are compared to [2]. Features Integration with RRP and openBIS ELN--LIMS: Mounts data (microscopy) form the research data management system openBIS in RRP for direct use. Reproducible workflow: Notebook documents interaction with data. Visualization: Generates visualizations of the results. 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 open and run the Jupyter notebook run_demo_analysis.ipynb Workflow Overview Reproducible workflow: Run the mini study. Visualization: Results such as segmentation masks, number of cells, report are stored in the RRP result folder. Directory Structure ├── .binder/ # Environment specifications, Python version, packages etc. ├── .rrp/ # Specification of required data from RDMS openBIS ELN-LIMS (Microscopy data) ├── resources # Folder containing references and splash image. ├── LICENSE # License ├── README.md # This file └── run_demo_analysis.ipynb # Notebook demonstrating mounted data. 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 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: Petersen, J. & Russell, P. Growth and the environment of Schizosaccharomyces pombe. Cold Spring Harb. Protoc. 2016, 210–226 (2016) doi:https://doi.org/10.1101/pdb.top079764.