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Create a coordinate system in rod-shaped cells.

Project description

travis appveyor Documentation Status binder codecov license doi



PLOS One Paper

BioRxiv Paper

Project Goals

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 colicoords

For 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 colicoords

Although ColiCoords features automated testing, there are likely to be bugs. Users are encouraged to report them via the Issues page on GitHub.



Several examples of ColiCoords usage can be found in the examples directory.



If you you use ColiCoords for scientific publication, 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).

Project details

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