https://github.com/cwilliamokafornta/tim23_ws44_htpimageanalysis_omero
Implementation of bio-image analysis with python in Omero
https://github.com/cwilliamokafornta/tim23_ws44_htpimageanalysis_omero
Science Score: 13.0%
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Repository
Implementation of bio-image analysis with python in Omero
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- Host: GitHub
- Owner: cwilliamOkafornta
- License: bsd-2-clause
- Default Branch: main
- Size: 2.6 MB
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Metadata Files
README.md
Trends in Microscopy 2023
Workshop 44
High throughput data analysis and management with Cellprofiler and OMERO
Workshop provider:
Thomas Zobel & Sarah Weischer
Münster Imaging Network, Cells in Motion Interfaculty Centre,
University of Münster, Germany
Abstract
The image data management system OMERO allows to organize and store data according to the FAIR principles. To perform image analysis, however, the image data often is downloaded to the local analysis station causing unnecessary duplication of data. Consequently, upload of analysis results, including reporting on analysis metadata (e.g. used analysis pipelines) has to be performed manually.

During this workshop we will present fully integrated data analysis solutions employing OMERO and commonly applied image analysis tools (e.g., CellProfiler, Fiji) using existing python interfaces (OMERO Python language bindings, ezOmero, Cellprofiler Python API).
Workshop topics:
1 Data import to OMERO and preparation for analysis
2 Automated data download/injection into analysis pipeline
3 Automated data analysis using image analysis pipelines (e.g., Cellprofiler)
4 Upload of the resulting images (including tags and metadata) and measurement results (omero.tables)
5 Explorative data analysis using omero.parade/omero.parade-crossfilter
During the hands-on session workshop participants will learn to analyze provided example datasets, execute the full workflow and perform easy adjustments of the pipeline (e.g. generation of new project/datasets, selection of image channels or ROIs for analysis, key:value pair annotation, file tagging, changes in file format), followed by explorative data analysis using omero.parade.
Analysed Image Data:
The data used for this workshop has been published and is publicly available in the Image Data Ressource (IDR).
https://idr.openmicroscopy.org/webclient/?show=screen-1651
Publication Title
RNAi screens for Rho GTPase regulators of cell shape and YAP/TAZ localisation in triple negative breast cancer.
Screen Description
Human RhoGEF/RhoGAP siGenome siRNA screen on highly metastatic triple negative breast cancer cell line LM2
Authors
Pascual-Vargas P, Cooper S, Sero J, Bousgouni V, Arias-Garcia M, Bakal C
DOI: 10.1038/sdata.2017.18 https://doi.org/10.1038/sdata.2017.18
In this repo you will find:
Upload: - JN1, Omero - JN2 (from disk, back-up) - Environment installation
- Presentation
Owner
- Name: Chukwuebuka Okafornta
- Login: cwilliamOkafornta
- Kind: user
- Location: Dresden, Germany
- Twitter: Williamonia
- Repositories: 1
- Profile: https://github.com/cwilliamOkafornta