Install CellProfiler and OMERO Python bindings¶
In this section, we show how to install CellProfiler in a Conda environment. We will use the CellProfiler API to analyze data stored in an OMERO server.
CellProfiler currently runs on Python 2.7. It does not yet support Python 3.
We recommend to install the dependencies using Conda.
Conda manages programming environments in a manner similar to
You can install the various dependencies following the steps below (Option 1) or build locally a Docker Image
repo2docker (Option 2). When the installation is done, you should be ready to use the CellProfiler API and OMERO, see Getting started with CellProfiler and OMERO.
The installation below is needed to run the scripts and/or notebooks. If you wish to start your own environment without the scripts/notebooks, copy locally into an
environment.yml file the content of
binder/environment.yml, remove or add the dependencies you need and run the commands below to create a conda environment.
Install Miniconda if necessary.
If you do not have a local copy of the omero-guide-cellprofiler repository, first clone the repository:
$ git clone https://github.com/ome/omero-guide-cellprofiler.git
Go into the directory:
$ cd omero-guide-cellprofiler
Create a programming environment using Conda:
$ conda create -n cellprofiler python=2.7
Install CellProfiler, its dependencies and
omero-pyin order to connect to an OMERO server using an installation file:
$ conda env update -n cellprofiler --file binder/environment.yml
Activate the environment:
$ conda activate cellprofiler
Alternatively you can create a local Docker Image using
$ repo2docker .
When the Image is ready:
- Copy the URL displayed in the terminal in your favorite browser
- Click the
Newbutton on the right-hand side of the window
A Terminal will open in a new Tab
A Conda environment has already been created when the Docker Image was built
To list all the Conda environment, run:
$ conda env list
The environment with CellProfiler and the OMERO Python bindings is named
kernel, activate it:
$ conda activate kernel