Data from: Pacemaker translocations and power laws in 2D stem cell-derived cardiomyocyte cultures

This repository contains the minimal information necessary for the
analysis of pacemaker translocation quiescent periods. There is enough
data provided to conduct a thorough analysis for power law behavior in
pacemaker translocation activity using the powerlaw Python library,
available via pip and at PyPi (https://pypi.org/project/powerlaw/).
Additionally, this repository contains batch file information for the
original files used in analysis and provides access to a Box link
containing the original *.mcd format files of each microelectrode array
(MEA) recording used to produce the data. The translocation algorithm is
described in the associated manuscript. Article abstract: Power laws are
of interest to several scientific disciplines because they can provide
important information about the underlying dynamics (e.g. scale invariance
and self-similarity) of a given system. Because power laws are of
increasing interest to the cardiac sciences as potential indicators of
cardiac dysfunction, it is essential that rigorous, standardized
analytical methods are employed in the evaluation of power laws. This
study compares the methods currently used in the fields of condensed
matter physics, geoscience, neuroscience, and cardiology in order to
provide a robust analytical framework for evaluating power laws in stem
cell-derived cardiomyocyte cultures. One potential power law-obeying
phenomenon observed in these cultures is pacemaker translocations, or the
spatial and temporal instability of the pacemaker region, in a 2D cell
culture. Power law analysis of translocation data was performed using
increasingly rigorous methods in order to illustrate how differences in
analytical robustness can result in misleading power law interpretations.
Non-robust methods concluded that pacemaker translocations adhere to a
power law while robust methods convincingly demonstrated that they obey a
doubly truncated power law. The results of this study highlight the
importance of employing comprehensive methods during power law analysis of
cardiomyocyte cultures.