[Workshop] Bioimage data management and analysis with OMERO
Description
Here we share the material used in a workshop held on May 13th, 2024, at the German Cancer Research Center in Heidelberg (on-premise)
Description:
Microscopy experiments generate information-rich, multi-dimensional data, allowing us to investigate biological processes at high spatial and temporal resolution. Image processing and analysis is a standard procedure to retrieve quantitative information from biological imaging. Due to the complex nature of bioimaging files that often come in proprietary formats, it can be challenging to organize, structure, and annotate bioimaging data throughout a project. Data often needs to be moved between collaboration partners, transformed into open formats, processed with a variety of software tools, and exported to smaller-sized images for presentation. The path from image acquisition to final publication figures with quantitative results must be documented and reproducible.
In this workshop, participants learn how to use OMERO to organize their data and enrich the bioimage data with structured metadata annotations.
We also focus on image analysis workflows in combination with OMERO based on the Fiji/ImageJ software and using Jupyter Notebooks. In the last part, we explore how OMERO can be used to create publication figures and prepare bioimage data for publication in a suitable repository such as the Bioimage Archive.
Module 1 (9 am - 10.15 am):
Basics of OMERO, data structuring and annotation
Module 2 (10.45 am - 12.45 pm):
OMERO and Fiji
Module 3 (1.45 pm - 3.45 pm):
OMERO and Jupyter Notebooks
Module 4 (4.15 pm - 6. pm):
Publication-ready figures and data with OMERO
The target group for this workshop
This workshop is directed at researchers at all career levels who plan to or have started to use OMERO for their microscopy research data management.
We encourage the workshop participants to bring example data from their research to discuss suitable metadata annotation for their everyday practice.
Prerequisites:
Users should bring their laptops and have access to the internet through one of the following options:
- eduroam
- institutional WiFi
- VPN connection to their institutional networks to access OMERO
Who are the trainers?
Dr. Riccardo Massei (Helmholtz-Center for Environmental Research, UFZ, Leipzig) - Data Steward for Bioimaging Data in NFDI4BIOIMAGE
Dr. Michele Bortolomeazzi (DKFZ, Single cell Open Lab, bioimage data specialist, bioinformatician, staff scientist in the NFDI4BIOIMAGE project)
Dr. Christian Schmidt (Science Manager for Research Data Management in Bioimaging, German Cancer Research Center, Heidelberg, Project Coordinator of the NFDI4BIOIMAGE project)
Notes (English)
Files
20240513_WorkshopSlides_Module01_public.pdf
Additional details
Software
- Repository URL
- https://github.com/rmassei/2024-jn-omero-pipeline
- Programming language
- Python
References
- Fuchs, V. A. F., Schmidt, C., & Boissonnet, T. (2024, Mai 6). [Workshop] FAIR data handling for microscopy: Structured metadata annotation in OMERO. Zenodo. https://doi.org/10.5281/zenodo.11109616
- Schmidt, C., Bortolomeazzi, M., Boissonnet, T., Fortmann-Grote, C., Dohle, J., Zentis, P., Kandpal, N., Kunis, S., Zobel, T., Weidtkamp-Peters, S., & Ferrando-May, E. (2023). I3D:bio's OMERO training material: Re-usable, adjustable, multi-purpose slides for local user training. Zenodo. https://doi.org/10.5281/zenodo.8323588
- Gerst, R., Cseresnyés, Z. & Figge, M.T. JIPipe: visual batch processing for ImageJ. Nat Methods 20, 168–169 (2023). https://doi.org/10.1038/s41592-022-01744-4
- Pouchin P, Zoghlami R, Valarcher R, Delannoy M, Carvalho M, Belle C, Mongy M, Desset S, Brau F. Easing batch image processing from OMERO: a new toolbox for ImageJ. F1000Res. 2022 Apr 5;11:392. doi: 10.12688/f1000research.110385.2. PMID: 35685190; PMCID: PMC9171289.
- https://thejacksonlaboratory.github.io/ezomero/index.html
- https://omero-rois.readthedocs.io/en/stable/#
- Schmied , C., Nelson, M.S., Avilov , et al. Community developed checklists for publishing images and image analyses. Nat Methods 21 , 170 181 (2024). https://doi.org/10.1038/s41592 023 01987 9
- Sarkans, U., Chiu, W., Collinson, L. et al. REMBI: Recommended Metadata for Biological Images—enabling reuse of microscopy data in biology. Nat Methods 18, 1418–1422 (2021). https://doi.org/10.1038/s41592-021-01166-8