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Documentation

PLOS One Paper

BioRxiv Paper

Paper code

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.:

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.

Contact: jhsmit@gmail.com

Examples

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

pipeline

Citation

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).

Acknowledgement

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).