Big-FISH is a python package for the analysis of smFISH images. It includes various methods to manipulate microscopic images, detect spots and segment relevant area of the cells. The package allows the user to extract specific signal from images and build a coordinate representation of the cells. The ultimate goal is to ease large scale statistical analysis and quantification.
| Cell image (smFISH channel) and its coordinates representation |
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Big-FISH requires Python 3.6 or newer. Additionally, it has the following dependencies:
- numpy (>= 1.16.0)
- scipy (>= 1.2.0)
- scikit-learn (>= 0.20.2)
- scikit-image (>= 0.14.2)
- matplotlib (>= 3.0.2)
- pandas (>= 0.24.0)
- mrc (>= (0.1.5)
- pip (>= 18.1)
To avoid dependency conflicts the use of a dedicated virtual or conda environment should be a considered option.
Use the package manager pip to install Big-FISH. In a terminal run the command:
pip install bigfishClone the project's Github repository and install it locally with the following commands:
git clone [email protected]:fish-quant/big-fish.git
cd big-fish
pip install .Big-FISH provides a toolbox for the full analysis pipeline of smFISH images:
- Use
bigfish.stacksubpackage for I/O operations, preprocessing and postprocessing. - Use
bigfish.segmentationsubpackage for nucleus and cell segmentation. - Use
bigfish.detectionsubpackage for mRNAs detection. - Use
bigfish.plotsubpackage for plotting routines. - Use
bigfish.classificationsubpackage for pattern recognition tasks.
Several examples are developed in the examples directory.
If you have any question relative to the repository, please open an issue. You can also contact Arthur Imbert or Florian Mueller.
Version 0.4.0:
- Refactor
bigfish.classificationsubpackage. - Add pattern recognition examples.
Version 0.5.0:
- Switch to tensorflow 2.0.0.
- Integrate a deep learning model for segmentation.
Version 1.0.0:
- Complete code coverage.
- Add sphinx documentation.
You can access the latest sources with the commands:
git clone [email protected]:fish-quant/big-fish.git
git checkout developPull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
Please make sure to update tests as appropriate if you open a pull request. You can install exacts dependencies and specific version of pytest by running the following command:
pip install -r requirements_dev.txtTo perform unitary tests, run :
pytest bigfish