A statistical analysis of particle trajectories in living cells

Abstract

Recent advances in molecular biology and fluorescence microscopy imaging have made possible the inference of the dynamics of single molecules in living cells. Such inference allows to determine the organization and function of the cell. The trajectories of particles in the cells, computed with tracking algorithms, can be modelled with diffusion processes. Three types of diffusion are considered : (i) free diffusion; (ii) subdiffusion or (iii) superdiffusion. The Mean Square Displacement (MSD) is generally used to determine the different types of dynamics of the particles in living cells (Qian, Sheetz and Elson 1991). We propose here a non-parametric three-decision test as an alternative to the MSD method. The rejection of the null hypothesis -- free diffusion -- is accompanied by claims of the direction of the alternative (subdiffusion or a superdiffusion). We study the asymptotic behaviour of the test statistic under the null hypothesis, and under parametric alternatives which are currently considered in the biophysics literature, (Monnier et al,2012) for example. In addition, we adapt the procedure of Benjamini and Hochberg (2000) to fit with the three-decision test setting, in order to apply the test procedure to a collection of independent trajectories. The performance of our procedure is much better than the MSD method as confirmed by Monte Carlo experiments. The method is demonstrated on real data sets corresponding to protein dynamics observed in fluorescence microscopy.

Revised introduction. A clearer and shorter description of the model (section 2)

References in corpus (4)

• Stochastic modeling in nanoscale biophysics: Subdiffusion within proteins
• Anomalous, non-Gaussian tracer diffusion in heterogeneously crowded environments
• Non-universal tracer diffusion in crowded media of non-inert obstacles
• Tracking rapid intracellular movements: A Bayesian random set approach

Cited by in corpus (9)

• Classification of particle trajectories in living cells: machine learning versus statistical testing hypothesis for fractional anomalous diffusion
• Fluid heterogeneity detection based on the asymptotic distribution of the time-averaged mean squared displacement in single particle tracking experiments
• Fisher information matrix for single molecules with stochastic trajectories
• Characterization of pedestrian contact interaction trajectories
• Persistence of temperature and precipitation: from local to global anomalies
• Effect of Pixelation on the Parameter Estimation of Single Molecule Trajectories
• Characterizing pedestrian contact interaction trajectories to understand spreading risk in human crowds
• Probabilistic reconstruction of truncated particle trajectories on a closed surface
• Limits of accuracy for parameter estimation and localisation in Single-Molecule Microscopy via sequential Monte Carlo methods