DOI: 10.5281/zenodo.13949357
title: Data for paper 'Formation of motile cell clusters in heterogeneous model tumors: The role of cell-cell alignment' (PRE, 2024)

description: The data provided in this repository is generated for the publication ‘Formation of motile cell clusters in heterogeneous model tumors: The role of cell-cell alignment’ by Quirine J.S. Braat, Cornelis Storm and Liesbeth M.C. Janssen and published in Physical Review E.

The data is generated using the Cellular Potts Model in CompuCell3D [1] that can be retrieved from GitHub. The simulations contain a more detailed description of the data, and the data provided here can be reproduced using the appropriate simulation code and parameters. These can be found on GitHub via https://github.com/QBraat/Cluster-Formation-Alignment.

The data in this repository has been divided into the following sets: 



EmptyLayer_Random.zip. this data set belongs to section III.A and section III.C and contains detailed information about the cells’ positions, orientation as a function of time for the active cells in free space.

EmptyLater_Random_single.zip. this data set belongs to section III.A and contains processed data about the order parameter and cluster size as a function of time for the active cells in free space.

ConfluentLayer_Random_single.zip. this data set belongs to section III.B and contains the processed data about the order parameter and cluster size as a function of time for the active cells in a confluent layer. 

ConfluentLayer_Random_FiniteSize.zip. this data set belongs to the data in the  supplementary information.

ConfluentLayer_Random_InitialBlock.zip. this data set belongs to the data in the supplementary information.


Other than these sets, there is an additional data set ‘ConfluentLayer_Random.zip’, which contains the detailed information about the cells’ positions, orientation etc. as a function of time for the confluent layer simulations in section III.B and section III.C. This data set has not been included as it contains a significantly large amount of data, but can be received upon request from the authors.

Detailed information about the data set

Each data point in the paper is generated by running 200 simulations using the simulation code for a set of parameters. For each combination of parameters (tau, gamma), we either got the full dynamic information (Full) or only the dynamic evolution of the mean cluster size and the steady state values for the mean cluster size and order parameter (Single).

Confluent layer (fraction = 0.25)






tau / gamma



1.0



0.5



0.2



0.1



0.05



0.02



0.01



0.005



0.001



0.001





500 mcs



Full



Single



Single



Full



Single



Single



Full



Full



Single



Full





2500 mcs



Full



Single



Single



Full



Single



Single



Full



Full



Single



Full





4000 mcs



Full



Single



Single



Full



Single



Single



Full



Full



Single



Full





 

Empty layer (fraction = 0.25) 






tau / gamma



1.0



0.5



0.2



0.1



0.05



0.02



0.01



0.005



0.001



0.001





500 mcs



Full



Full



Full



Full



Full



Full



Full



Full



Full



Full





2500 mcs



Full



Full



Full



Full



Full



Full



Full



Full



Full



Full





4000 mcs



Single



Single



Single



Single



Single



Single



Single



Single



Single



Single





 

Other simulations 

Apart from the main results, we also ran simulations with different parameter settings to get more insights into the dynamic behavior.






Simulations



Settings



Storage type





Different fraction active cells



Confluent layer, fraction = 0.1, other parameters as before



Single





No alignment



Confluent Layer + Empty Layer, fraction = 0.25, gamma = 0, tau = 2500 mcs



Full





Initially aligned cluster



Fully aligned cluster, Confluent Layer + Empty Layer, gamma = 1.0, 0.01, 0.001 and tau = 2500 mcs



Full





Finite-size effects



Confluent Layer, number of cells = 100, 400, 9000, 1600, 2500 cells



Single





 

Data format

When the simulations are run with full data export, the following files are generated: 



data_cells_<settings>.dat: 



mcs: time stamp in Monte Carlo Steps (MCS) 

cell.id: number of the cell 

cell.type: type of the Cells (active = 2, passive = 1) 

xCOM: x-coordinate of the center of mass 

yCOM: y-coordinate of the center of mass 

zCOM: z-coordinate of the center of mass (always equal to 0 in 2D) 

pol_angle: angle with respect to the x-axis of the active force orientation. 

cluster.id: number of the cluster to which the cells belongs.



data_clusters_<settings>.dat: 



mcs: time stamp in Monte Carlo Steps (MCS)

cluster_id: number of the cluster (corresponding to the number cluster.id in data_cells_<settings>.dat 

cluster_size: number of cells in the given cluster 



metadata_<settings>.dat: 



Information about the full set of simulation parameters




When the simulations are run with single data export, the following files are generated: 



single_export_<settings>.dat: 



steadyS: steady state value of the mean cluster size (mean calculated after 60000 mcs)

steadyS_std: standard deviation of the steady state value of the mean cluster size

steadyP: steady state value of the polarity order parameter 

steadyP_std: standard deviation of the steady state value of the polarity order parameter 



St-single-export_<settings>.dat: 



mcs: time stamp in Monte Carlo Steps (MCS)

St: mean cluster size at given time stamp

St_std: standard deviation of the mean cluster size at a given time stamp 



S-max-single-export_<settings>.dat



mcs: time stamp in Monte Carlo Steps (MCS)

Smax: largest cluster detected at a given time stamp



metadata_<settings>.dat: 



Information about the full set of simulation parameters