IsoMaTrix: a framework to visualize the isoclines of matrix games and quantify uncertainty in structured populations

Jeffrey West; Yongqian Ma; Artem Kaznatcheev; Alexander R A Anderson

doi:10.1093/bioinformatics/btaa1025

IsoMaTrix: a framework to visualize the isoclines of matrix games and quantify uncertainty in structured populations

Bioinformatics. 2021 Apr 1;36(22-23):5542-5544. doi: 10.1093/bioinformatics/btaa1025.

Authors

Jeffrey West¹, Yongqian Ma², Artem Kaznatcheev^{3

4}, Alexander R A Anderson¹

Affiliations

¹ Integrated Mathematical Oncology Department, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL 33612, USA.
² Department of Physics & Astronomy, University of Southern California, Los Angeles, CA 90089-1191, USA.
³ Department of Translational Hematology & Oncology Research, Cleveland Clinic, Cleveland, OH, USA.
⁴ Department of Computer Science, University of Oxford, Oxford, UK.

Abstract

Summary: Evolutionary game theory describes frequency-dependent selection for fixed, heritable strategies in a population of competing individuals using a payoff matrix. We present a software package to aid in the construction, analysis and visualization of three-strategy matrix games. The IsoMaTrix package computes the isoclines (lines of zero growth) of matrix games, and facilitates direct comparison of well-mixed dynamics to structured populations on a lattice grid. IsoMaTrix computes fixed points, phase flow, trajectories, (sub)velocities and uncertainty quantification for stochastic effects in spatial matrix games. We describe a result obtained via IsoMaTrix's spatial games functionality, which shows that the timing of competitive release in a cancer model (under continuous treatment) critically depends on the initial spatial configuration of the tumor.

Availability and implementation: The code is available at: https://github.com/mathonco/isomatrix.

Supplementary information: Supplementary data are available at Bioinformatics online.

Abstract

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