README.md

Supporting code for the article:

J Yu and N Bagheri. (2021). Modular microenvironment components reproduce vascular dynamics de novo in a multi-scale agent-based model. Cell Systems. doi: 10.1016/j.cels.2021.05.007

Setup files

The setups directory contains all the setup files used for running simulations. Simulations were run using ARCADE v2.3.

The ROOT_LAYOUTS.xml setup file creates checkpoints for the different vascular root layouts that are then loaded for any simulations using those layouts. The case study VESSEL_COLLAPSE_stabilized.xml simulations uses modified code; see supplementary materials for details.

Simulation data

Raw simulation data and results are available on Mendeley Data:

• SITE ARCHITECTURE . http://dx.doi.org/10.17632/2n3mnkz7yc
• ESTIMATED HEMODYNAMICS . http://dx.doi.org/10.17632/pgzc9f6kn6
• EXACT HEMODYNAMICS . http://dx.doi.org/10.17632/8k7f7fcg7t
• VASCULAR DAMAGE . http://dx.doi.org/10.17632/grtx87d27y
• VASCULAR FUNCTION . http://dx.doi.org/10.17632/rgtddfyp97
• VESSEL COLLAPSE . http://dx.doi.org/10.17632/p8yzkdccg7

Pipeline notebooks

Parse simulation outputs

The parse_simulation_outputs notebook provides the functions and scripts for parsing simulation files (.json) into pickled numpy arrays (.pkl). These parsed results are included with the raw simulation data.

Analyze data & results

The analyze_data_results notebook provides functions and scripts for running basic analysis on simulation data and parsed results. All resulting .json and .csv files are provided in the analysis directory.

Note that if you are using Python 3.9, the required version of networkx will throw the error: ImportError: cannot import name 'gcd' from 'fractions'. Go to the networkx/algorithms/dag.py file in your virtual environment (venv/lib/python3.9/site-packages/networkx/algorithms/dag.py) and change the line from fractions import gcd to from math import gcd.

Generate figure inputs

The generate_figure_inputs notebook walks through all the steps necessary to generate figure input files from raw data, parsed files, and basic analysis files. All resulting files are provided in the analysis directory. Refer to figure section in notebook for more details.

To view figures, start a local HTTP server from the root folder, which can be done using Python or PHP:

$ python3 -m http.server
$ php -S 127.0.0.1:8000

Note that the links in the notebook to figures assume the local port 8000; if your server is running on a different port, the links to the figures from the notebook will not work. Instead, you can navigate to http://localhost:XXXX/ where XXXX is the port number and follow links to the figures.

Perform linear regression

The perform_linear_regression notebook works through the process of performing linear regression on the different combinations of metrics, properties, and measures. Regression results are compiled into a single file (included in the analysis directory) and used to generate the linear_regression figure.

Explore case study

The explore_case_study notebook explores the case study VESSEL_COLLAPSE simulation set. Raw simulation data and parsed results are available on Mendeley Data (see above) and compiled analysis files used to generate the case_study figure are provided in the analysis directory.