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A global sampler of single particle tracking solutions for single molecule microscopy

Author

Listed:
  • Michael Hirsch
  • Richard Wareham
  • Ji W Yoon
  • Daniel J Rolfe
  • Laura C Zanetti-Domingues
  • Michael P Hobson
  • Peter J Parker
  • Marisa L Martin-Fernandez
  • Sumeetpal S Singh

Abstract

The dependence on model-fitting to evaluate particle trajectories makes it difficult for single particle tracking (SPT) to resolve the heterogeneous molecular motions typical of cells. We present here a global spatiotemporal sampler for SPT solutions using a Metropolis-Hastings algorithm. The sampler does not find just the most likely solution but also assesses its likelihood and presents alternative solutions. This enables the estimation of the tracking error. Furthermore the algorithm samples the parameters that govern the tracking process and therefore does not require any tweaking by the user. We demonstrate the algorithm on synthetic and single molecule data sets. Metrics for the comparison of SPT are generalised to be applied to a SPT sampler. We illustrate using the example of the diffusion coefficient how the distribution of the tracking solutions can be propagated into a distribution of derived quantities. We also discuss the major challenges that are posed by the realisation of a SPT sampler.

Suggested Citation

  • Michael Hirsch & Richard Wareham & Ji W Yoon & Daniel J Rolfe & Laura C Zanetti-Domingues & Michael P Hobson & Peter J Parker & Marisa L Martin-Fernandez & Sumeetpal S Singh, 2019. "A global sampler of single particle tracking solutions for single molecule microscopy," PLOS ONE, Public Library of Science, vol. 14(10), pages 1-21, October.
  • Handle: RePEc:plo:pone00:0221865
    DOI: 10.1371/journal.pone.0221865
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    References listed on IDEAS

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    1. Durbin, James & Koopman, Siem Jan, 2012. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, edition 2, number 9780199641178.
    2. Raibatak Das & Christopher W Cairo & Daniel Coombs, 2009. "A Hidden Markov Model for Single Particle Tracks Quantifies Dynamic Interactions between LFA-1 and the Actin Cytoskeleton," PLOS Computational Biology, Public Library of Science, vol. 5(11), pages 1-16, November.
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