Supplementary data for: "Sarcomere dynamic instability and stochastic heterogeneity drive robust cardiomyocyte contraction"

Data and analysis code for "Sarcomere dynamic instability and stochastic heterogeneity drive robust cardiomyocyte contraction" by Haertter et al., eLife (2026). Reviewed preprint prior to revision: https://doi.org/10.7554/eLife.97321.1. Revised preprint: ttps://www.biorxiv.org/content/10.1101/2024.05.28.596183 This repository contains: • Raw high-speed confocal microscopy movies (66 fps) of hiPSC-derived cardiomyocytes on elastic substrates with varying stiffness (5 kPa to 85 kPa)• Pre-analyzed Line-of-Interest (LOI) data stored as JSON files for rapid reconstruction of analysis results• Complete dataframe ("data_motion.pkl") with aggregated motion analysis results from all movies• Python scripts to unzip LOI data and recreate the results dataframe using SarcAsM Quick Start 1. Install SarcAsM: `pip install sarc-asm`2. Unzip LOI data: `python unzip_data.py`3. Run analysis: Execute the Python code examples in the README.md to analyze individual LOIs or batch-process all movies Contents by Condition 25 representative movies per substrate stiffness condition, each with:- Raw `.tif` movie file (confocal stack time series)- Zipped folder containing pre-analyzed LOI data (JSON format)- Extracted sarcomere trajectories and automated analysis results Documentation Complete analysis workflow documentation is provided in README.md, including step-by-step examples for:- Loading and analyzing individual movies- Performing motion analysis on LOIs- Correlation and heterogeneity analysis- Batch processing and dataframe export For questions, refer to the SarcAsM documentation: https://sarcasm.readthedocs.io/ or contact us.