ColiCoords is a python project for analysis of fluorescence microscopy data from rodlike cells. The project is aimed to be an open, well documented platform where users can easily share data through compact hdf5 files and analysis pipelines in the form of Jupyter notebooks.
ColiCoords is available on PyPi and Conda Forge. Currently, python >= 3.6 is required.
Installation by Conda.:
conda install -c conda-forge colicoordsFor installation via PyPi a C++ compiler is required for installing the dependency mahotas. Alternatively, mahotas can be installed separately from Conda.
To install ColiCoords from pypi:
pip install colicoordsAlthough ColiCoords features automated testing, there are likely to be bugs. Users are encouraged to report them via the Issues page on GitHub.
Contact: [email protected]
Several examples of ColiCoords usage can be found in the examples directory.
If you you use ColiCoords (or any modified version) for scientific publication or other purposes, please cite:
Smit, J. H., Li, Y., Warszawik, E. M., Herrmann, A. & Cordes, T. ColiCoords: A Python package for the analysis of bacterial fluorescence microscopy data. PLOS ONE 14, e0217524 (2019).
If you use the CNN module please also cite:
Falk, T. et al. U-Net: deep learning for cell counting, detection, and morphometry. Nat Methods 16, 67–70 (2019).
ColiCoords up to v0.1.4 was developed by Jochem Smit within ongoing projects of the Cordes Lab. The project was financed until 01-08-2018 by an ERC Starting Grant (No. 638536 - SM-IMPORT to Thorben Cordes) and an ERC Advanced Grant (No. 694610 - SUPRABIOTICS to Andreas Herrmann).