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Using approximate Bayesian computation to quantify cell-cell adhesion parameters in a cell migratory process

Robert J. H. Ross, R. E. Baker, Andrew Parker, M. J. Ford, R. L. Mort, C. A. Yates
doi: https://doi.org/10.1101/068791
Robert J. H. Ross
1Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Radcliffe Observatory Quarter, Woodstock Road, Oxford, OX2 6GG
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R. E. Baker
1Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Radcliffe Observatory Quarter, Woodstock Road, Oxford, OX2 6GG
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Andrew Parker
1Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Radcliffe Observatory Quarter, Woodstock Road, Oxford, OX2 6GG
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M. J. Ford
2MRC Human Genetics Unit, MRC IGMM, Western General Hospital, University of Edinburgh, Edinburgh, EH4 2XU
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R. L. Mort
2MRC Human Genetics Unit, MRC IGMM, Western General Hospital, University of Edinburgh, Edinburgh, EH4 2XU
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C. A. Yates
3Centre for Mathematical Biology, Department of Mathematical Sciences, University of Bath, Claverton Down, Bath, BA2 7AY
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Abstract

In this work we implement approximate Bayesian computational methods to improve the design of a wound-healing assay used to quantify cell-cell interactions. This is important as cell-cell interactions, such as adhesion and repulsion, have been shown to play an important role in cell migration. Initially, we demonstrate with a model of an ideal experiment that we are able to identify model parameters for agent motility and adhesion, given we choose appropriate summary statistics. Following this, we replace our model of an ideal experiment with a model representative of a practically realisable experiment. We demonstrate that, given the current (and commonly used) experimental set-up, model parameters cannot be accurately identified using approximate Bayesian computation methods. We compare new experimental designs through simulation, and show more accurate identification of model parameters is possible by expanding the size of the domain upon which the experiment is performed, as opposed to increasing the number of experimental repeats. The results presented in this work therefore describe time and cost-saving alterations for a commonly performed experiment for identifying cell motility parameters. Moreover, the results presented in this work will be of interest to those concerned with performing experiments that allow for the accurate identification of parameters governing cell migratory processes, especially cell migratory processes in which cell-cell adhesion or repulsion are known to play a significant role.

Footnotes

  • ↵* ross{at}maths.ox.ac.uk

  • ↵† baker{at}maths.ox.ac.uk

  • ↵‡ parker{at}maths.ox.ac.uk

  • ↵§ matthew.ford{at}ed.ac.uk

  • ↵¶ richard.mort{at}igmm.ed.ac.uk

  • ↵∥ c.yates{at}bath.ac.uk

  • 5 This approach is in agreement with previous studies [24], which showed the most relevant information from the PCF summary statistic is perpendicular to the wound axis in a wound-healing assay.

  • 7 However, this does not necessarily mean the posterior distribution is a more accurate representation of the parameter distribution.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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Posted August 24, 2016.
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Using approximate Bayesian computation to quantify cell-cell adhesion parameters in a cell migratory process
Robert J. H. Ross, R. E. Baker, Andrew Parker, M. J. Ford, R. L. Mort, C. A. Yates
bioRxiv 068791; doi: https://doi.org/10.1101/068791
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Using approximate Bayesian computation to quantify cell-cell adhesion parameters in a cell migratory process
Robert J. H. Ross, R. E. Baker, Andrew Parker, M. J. Ford, R. L. Mort, C. A. Yates
bioRxiv 068791; doi: https://doi.org/10.1101/068791

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