Data analysis of E. coli growth using ODity.bio

This is the full data analysis accompanying the pre-print Quantifying live bacterial densities using non-invasive optical measurements of E. coli. The analysis is wrapped in a Jupyter Notebook ODity growth measurements of Ecoli MG1655, which can be viewed with the in-line results in this repository, or ran from beginning-to-end to reproduce the conclusions of the paper. GitHub sometimes has trouble rendering Jupyter notebooks, so instead use the online nbviewer.

Publication figures can be found in the output_figures folder

Example of figure 3 from the pre-print.

Installation

Requirements

cufflinks==0.17.3
lmfit==1.0.2
matplotlib==3.1.3
numdifftools==0.9.39
numpy==1.18.1
pandas==1.0.1
plotly==4.10.0
scipy==1.4.1

Docker

To circumvent setting up all the dependencies in a Python environment, a Docker container is supplied on Docker Hub. The following four simple steps are required:

1. To get started download Docker https://docs.docker.com/get-started/
2. Pull down this repository using git clone https://github.com/EvdH0/ODity-growth-E-coli.git
3. Download the image docker pull evdh0/scipy-notebook-odity-ecoli:latest
4. Then use docker run -p 8888:8888 -v $(pwd):/home/jovyan/work evdh0/scipy-notebook-odity-ecoli to launch the container and start the Jupyter notebook on your local machine
5. Browse to http://127.0.0.1:8888/ and the notebook and data is accessible in the work folder

License

Apache License, Version 2.0, see LICENSE

Author

The notebook was written by Eric van der Helm.

Citation

van der Helm, E. & Redl, S. M. A. Quantifying live bacterial densities using non-invasive optical measurements of E. coli. bioRxiv (2021) doi:10.1101/2021.06.12.448182