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SpringSaLaDpy

Python package to run SpringSaLaD, analyze and vizualize its output

SpringSaLaDpy is a lightweight command line interface (CLI) for SpringSaLaD. SpringSaLaDpy comes with

The original SpringSaLaD is GUI application that requires installation and generates mostly raw data, without visualization and with limited analysis capabilities. SpringSaLaDpy adds

Workflow

The user selects a SpringSaLaD input file, usually generated with SpringSaLaD GUI. This file can be simulated through SpringSaLaDpy or the SpringSaLaD GUI. Both methods will produce the same simulation results. SpringSaLaDpy helps to understand and visualize the input file and allows updating initial counts and kinetic rates. In either case, the simulations output a folder of results containing CSV and text data files describing the state of the simulation at each point in time.

From here, the user will pick an analysis function and select arguments for data to analyze (e.g. specific time point during the simulation) and outputs to display (e.g., an argument could be a range over which to display a distribution of cluster sizes). The simulation data are processed and outputs are put into the pyStat folder. Lastly, SpringSaLaDPy uses these pyStat files to make the visualization and display it for the user.

SpringSaLaDpy input: model specification in SpringSaLaD format

The model specifications generated by SpringSaLaD GUI.

SpringSaLaDpy outputs

Describing and visualizing of molecular clusters

analysis.ipynb provides human-readable description and visualization of the model specification generated by SpringSaLaD GUI without the need to invoke GUI:

If the model was previously simulated, SpringSaLaDpy provides customizable screenshots of cluster distribution at requested timepoints:

Cluster composition at specific timepoints

SpringSaLaDpy can process simulation results and plot cluster distribution at specific time point(s). The first plot shows the fraction of total molecules in the clusters of different sizes: one can see that 14% of all molecules are in clusters of size 4, while the next most popular cluster size 5 accumulates 12%. Note the dashed vertical line - it is the mean of the distribution, callesd average cluster occupancy. The next plot demonstrated the fraction of molecules in monomers and dimers (1-2 molecules), small clusters (2-3 molecules), and relatively large (more than 3 molecules) clusters.

Cluster properties of specific molecules

The next plot demonstrates the cluster composition - distribution of Nck, Nephrin and NWasp in clusters of different size. One can zoom in on specific clusters.

Timecourses for cluster properties

SpringSaLaDpy can process simulation results and plot time plots of:

Change of spatial properties of clusters over time

SpringSaLaDpy computes and plots

Cluster properties - bonds saturation

SpringSaLaDpy will analyze and plot the frequency of molecules in clusters with a given number of bonds.

Data storage for post-processing

All the simulation outputs are written to the folder …. The statistical data generated by SpringSaLaDpy and used to plot figures is stored in pyStat folder within the model folder.