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.
pip install cenfind
score with 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
visualisations/ and statistics/For more information, please check the documentation (https://cenfind.readthedocs.io).
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
FAQs
Score cells for centrioles in IF data
We found that cenfind demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 2 open source maintainers collaborating on the project.
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