Once you have performed object tracking, there are many tasks that you may wish to perform with that tracking data. This page lists a number of scripts that can be downloaded that perform various post-processing tasks on FAST's track output.

If you are more comfortable with programming languages other than Matlab, these scripts will convert the tracking data structures into something more to your liking.

• matlab_to_df.R: Converts procTracks to an R dataframe.

Many experiments consist of mixtures of distinct populations of cells; these scripts allow you to automatically separate out and label these populations.

• splitFluoPopulationsTracks.m: Splits tracks into populations based on fluorescence levels in two channels.
• labelStartAndEndFluoCells.m: Splits tracks into populations based on fluorescence levels in a single channel from images taken at the start and end of a timelapse series. Permits population assignment with minimal phototoxicity.

Often, we are interested in the time at which a cell performs a particular action. These scripts will help you to detect these 'events' and assign them to FAST's internal representation.

These functions allow you to extract or adjust data associated with your tracks.

• meanIntInEllipse.m: Creates an elliptical mask based on the specified object's geometry and measures the intensity of an image within that mask.