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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.

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 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).

Metadata

Release files for colicoords 0.1.5

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

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Source distribution for colicoords 0.1.5
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Table of built distributions (wheels) for colicoords 0.1.5
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colicoords-0.1.5-py2.py3-none-any.whl Python 2, Python 3 none any Details

Total release size: 53.4 MB

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