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training-notebooks

A set of Notebooks to demonstrate how to access the images and metadata from OMERO.

To build the image run, in this repository:

$ docker build -t training-notebooks .

The image contains the dependencies required to connect to OMERO 5.5.x.

To start the image in Jupyter:

$ docker run -it  -p 8888:8888 training-notebooks

To start the image in Jupyterlab:

$ docker run -it  -p 8888:8888 -e JUPYTER_ENABLE_LAB=true training-notebooks

To update a notebook while this is running: In another terminal, get the container ID and copy a notebook e.g. idr0002.ipynb

$ docker ps
$ docker cp CellProfiler/idr0002.ipynb <container_id>:/home/jovyan/notebooks/CellProfiler/idr0002.ipynb

Now refresh the notebook in the browser.

To restart a container and get the URL to open in your browser:

$ docker restart <container_id>
$ docker logs <container_id>

The notebooks in this repository are meant to exemplify how to access data in OMERO.

Notebook Lang Description
OMERO example Py Shows how to connect to OMERO and read data.
Calculate Sharpness Py Calculates sharpness of images and generates heatmaps.
Illumination Correction Py Correct the selected image.
R-OMERO example R Shows how to connect to OMERO and manipulate data using R.
idr0021 ROIs R Read OMERO.table data, performs some basic statistics on it and create a plot.
Statistics Fruit Fly Py Process Images stored in OMERO using CellProfiler.
idr0002 Py Process a plate from idr0002 using CellProfiler.
SimpleFRAP Py Process a dataset measuring the intensity in a named Channel within a ROI.

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A set of Python Notebooks to demonstrate how to access the images and metadata from OMERO

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  • Jupyter Notebook 87.4%
  • Python 10.1%
  • Dockerfile 1.6%
  • Other 0.9%