macrohet

Fast-growing intracellular Mycobacterium tuberculosis populations evade antibiotic treatment

WORK IN PROGRESS (tidying code up pending publication) This repository accompanies the manuscript exploring single-cell heterogeneity in Mtb-infected macrophages using time-lapse microscopy, tracking and single-cell growth rate analysis.

GitHub Pages for this project (figures + interactive plots are work in progress, pending publication): nthndy.github.io/macrohet

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Contents

• notebooks/: Reproducible analysis notebooks for data loading, segmentation, tracking, and quantification
• macrohet/: Python module with core analysis functions
• data/: Subset of image data with associated segmentation and tracks
• models/: Bespoke segmentation model and btrack tracking parameters
• docs/: HTML manuscript and supporting content (hosted via GitHub Pages)
• environment.yml: Conda environment specification
• .pre-commit-config.yaml: Code formatting and linting hooks
• README.md: Project overview and usage instructions

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Installation and reproducibility

Clone the repository:

git clone https://github.com/nthndy/macrohet.git
cd macrohet
pip install -e .

Create and activate the environment:

mamba env create -f environment.yml
conda activate macrohet

This project uses a development version of btrack that includes compatibility with pydantic ≥2, required by napari. To ensure compatibility with both tracking and visualisation components, btrack is installed directly from GitHub via pyproject.toml or the environment.yml file. Parts of the image tiling and stitching pipeline were adapted from Volker Hilsenstein’s DaskFusion project, used under the MIT License. Details of the hardware and software used to generate the analyses in this repository are provided in reproducibility.md.

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Contact

For questions or access to underlying data/code, please contact:

Nathan J. Day
Host–Pathogen Interactions in Tuberculosis Laboratory
The Francis Crick Institute
nathan.day@crick.ac.uk
@nthndy.bsky.social
github.com/nthndy