Score cells for centrioles in IF data
Project description
CenFind
Cenfind is a command line interface written in Python to detect and assign centrioles in immunofluorescence images of human cells. Specifically, it orchestrates the detection of centrioles, the detection of the nuclei and the assignment of the centrioles to the nearest nucleus.
Getting started
- Install cenfind from PyPI:
pip install cenfind
- You need to download it from https://figshare.com/articles/software/Cenfind_model_weights/21724421
- Collect all images in a project folder inside a projections folder (<project_name>/projection/).
- Run
scorewith the path to the project, the path to the model, the index of the nuclei channel (usually 0 or 3), the channel to score:
cenfind score /path/to/dataset /path/to/model/ -n 0 -c 1 2 3
- Check that the predictions in the folders
visualisations/andstatistics/
For more information, please check the documentation (https://cenfind.readthedocs.io).
Citation
We appreciate citations as they help us obtain grant funding and let us discover its application range.
To cite Cenfind in publications, please use:
Bürgy, L., Weigert, M., Hatzopoulos, G. et al. CenFind: a deep-learning pipeline for efficient centriole detection in microscopy datasets. BMC Bioinformatics 24, 120 (2023). https://doi.org/10.1186/s12859-023-05214-2
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