Track analysis code for the article 'Automated Optimization of Bacterial Tracking Pipelines in Light Microscopy Using TrackMate 8'

This repository contains the code required to perform track analysis for the protocols described in the article 'Automated Optimization of Bacterial Tracking Pipelines in Light Microscopy Using TrackMate 8'. For convenience, this Python code is stored in a single repository, takes the shape of several Python notebooks, which can run all with on conda environment. They process TrackMate outputs and exemplify the use of the protocol for:

1. Detecting and quantifying growth dynamics and cell morphology in E. coli respiratory chain mutants.
2. Assessing how H. pilory bacteria motility is affected by mutations.
3. Evaluating the impact of environmental stresses on M. tuberculosis phenotypic variation of sub-populations. Lineage analyses rely pycellin.

Installation

To run this code, you need to create a conda environment with the following commands:

conda create -n bact_motility python=3.10
conda activate bact_motility
pip install pycellin
pip install scikit-learn
pip install statsmodels
pip install seaborn
pip install jupyter

then run it in a Jupyter lab environment or VSCode.