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`Documentation <https://colicoords.readthedocs.io/>`_
`PLOS One Paper <https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0217524>`_
`BioRxiv Paper <https://www.biorxiv.org/content/10.1101/608109v1>`_
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.
Installation
============
``ColiCoords`` is available on PyPi and Conda Forge. Currently, python >= 3.6 is required.
Installation by `Conda <https://conda.io/docs/>`_.:
.. code:: bash
conda install -c conda-forge colicoords
For installation via PyPi a C++ compiler is required for installing the dependency `mahotas <https://mahotas.readthedocs.io/en/latest/index.html>`_. Alternatively, ``mahotas`` can be installed separately from Conda.
To install ``ColiCoords`` from pypi:
.. code:: bash
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.
Contact: jhsmit@gmail.com
Examples
========
Several examples of `ColiCoords` usage can be found in the examples directory.
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Citation
========
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).
