DOI: 10.5068/d1pd72
title: Data from: Pacemaker translocations and power laws in 2D stem cell-derived cardiomyocyte cultures

description: 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.
description: Dataset was collected in the manner described in the manuscript.
 No post-processing (e.g. signal filtering or smoothing) was applied to the
 recorded field potentials. Data processing is largely limited to
 calculation of pacemaker (time lag) data combined with application of the
 algorithm for detecting pacemaker translocations. The algorithm employs a
 distance threshold-based method to identify when the pacemaker moves
 (translocates).  Refer to the original manuscript for more
 information.
description: The values given here are pacemaker translocation quiescent
 periods, as measured in beats.  Full recapitulation of the analysis would
 likely require access to MEA recordings. For 30 recordings, the file sizes
 equal approx. 7.5gb of data (in .mcd form; near 60gb in text form). If you
 want access to this data, please do not hesitate to contact the
 corresponding authors.  We will be happy to share the data with you in the
 form of a freely-accessible Box link.