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DeepProfiler


codecov Requirements Status CII Best Practices CometML

Image-based profiling using deep learning

DeepProfiler is a set of tools that allow you to use deep learning for analyzing imaging data in high-throughput biological experiments. Please, see our Wiki documentation page for more details about how to use it.

Quick Guide

Clone or fork this repository and install it using:

pip install -e .

When running DeepProfiler you usually need to specify a root directory where your data is stored and a command that you want to run. For instance, to initialize your project, you can use:

python deepprofiler --root=/home/ubuntu/project --config=config.json setup

In the created directories, you will need to organize your input files, including metadata, images and single-cell locations. See more details about the project structure here.

Next, if you want to train a model, as specified in the configuration file, you can then run the following command:

python deepprofiler --root=/home/ubuntu/project/ --config filename.json train

And to extract single-cell embeddings, use:

python deepprofiler --root=/home/ubuntu/project/ --config filename.json profile

Find more information in the training and profiling section of our wiki.

Happy profiling!