Figure 2.

Dependence of estimated diffusion constant ${\mathit{D}}_1$ (slow subpopulation) on simulation parameters and inference method. Each panel (A–I) corresponds to a combination of simulation parameters $D_1$ and $D_2$, as indicated by the green and blue labels outside the plot panels, respectively. Within each panel 4 values of the fraction sizes $\alpha$ were chosen and synthetic simulations were performed on all parameter combinations. For each parameter combination ($D_1$, $D_2$ and $\alpha$) 30 simulations with 2000 tracks of 20 frames duration (see Table 1 for all simulation parameters) were executed and the resulting data was analyzed with the GMM and SQD method, yielding two different estimates for the value of $D_1$(GMM: black boxplots; SQD: cyan boxplots). On each box, the central mark is the median, the edges of the box are the 25^th and 75^th percentiles, the whiskers extend to the most extreme data points not considered outliers and the outliers are plotted as individual circles. The green horizontal lines indicate the true value for $D_1$in the simulation. The black dashed lines indicate the lower limit $D_{loc}=\frac{{\mathrm{\sigma }}_{loc}^2}{2\mathrm{\Delta }t}=0.0225\frac{\mu m^2}{s}$ for an estimate of the diffusion constant, given a finite localization precision ${\mathrm{\sigma }}_{loc}=30nm$ and a frame rate of $\mathrm{\Delta }t=20ms$ used in our simulations.