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A Quantitative Comparison of Single-Dye Tracking Analysis Tools Using Monte Carlo Simulations

Author

Listed:
  • Laura Weimann
  • Kristina A Ganzinger
  • James McColl
  • Kate L Irvine
  • Simon J Davis
  • Nicholas J Gay
  • Clare E Bryant
  • David Klenerman

Abstract

Single-particle tracking (SPT) is widely used to study processes from membrane receptor organization to the dynamics of RNAs in living cells. While single-dye labeling strategies have the benefit of being minimally invasive, this comes at the expense of data quality; typically a data set of short trajectories is obtained and analyzed by means of the mean square displacements (MSD) or the distribution of the particles’ displacements in a set time interval (jump distance, JD). To evaluate the applicability of both approaches, a quantitative comparison of both methods under typically encountered experimental conditions is necessary. Here we use Monte Carlo simulations to systematically compare the accuracy of diffusion coefficients (D-values) obtained for three cases: one population of diffusing species, two populations with different D-values, and a population switching between two D-values. For the first case we find that the MSD gives more or equally accurate results than the JD analysis (relative errors of D-values

Suggested Citation

  • Laura Weimann & Kristina A Ganzinger & James McColl & Kate L Irvine & Simon J Davis & Nicholas J Gay & Clare E Bryant & David Klenerman, 2013. "A Quantitative Comparison of Single-Dye Tracking Analysis Tools Using Monte Carlo Simulations," PLOS ONE, Public Library of Science, vol. 8(5), pages 1-9, May.
    • Handle: RePEc:plo:pone00:0064287
    DOI: 10.1371/journal.pone.0064287
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