A complementary set of tools is provided in several graphical user interfaces that serve detailed analyses of the data, including the plotting of polymers (Figure

1c) and the statistical treatment of polymer contour lengths (see Additional file

1: Figure S2 and Note S2). For instance, the user can plot a histogram of the distribution of polymer contour lengths, and Gaussian fitting of the distribution can be done within the GUI. Also available is the possibility to derive an axial elastic modulus from three distinct models for the cross-sectional geometry of the polymer. Importantly, multiple control functions are included. First, the ability to adapt the fitting of the chain contour by setting a user-defined "fitting parameter" (see Additional file

1: Figure S1 and Note S1). In practice, this allows preserving the accuracy of the measurements at any given resolution providing it meets minimum requirements (see Additional file

1: Note S1 for details). Second, two independent tests[

3,

8] to determine whether or not the polymers have fully equilibrated in 2D, which can influence the choice of the model used to be fitted to data (see next section, where these two tests are described in detail). Third, a Monte-Carlo-based method described previously[

3] was implemented into another graphical user interface (

*Synchains*) to generate

*in silico* polymers with user-defined persistence lengths (Additional file

1: Figure S3 and Note S3). In short, if P is the persistence length, then the small angles θ between discrete segments located at a distance

*ℓ* apart have a probability density P:

$\mathrm{P}{\left(\mathrm{\theta}\left(\ell \right)\right)}_{2\mathrm{D}}\phantom{\rule{0.5em}{0ex}}\mathit{\alpha}\phantom{\rule{1em}{0ex}}{e}^{-\frac{\mathrm{P}{\mathit{\theta}}^{2}}{2\ell}}$

(4)