Welcome to Track Analyzer’s documentation!
Track Analyzer is Python-based data visualization pipeline for tracking data. It does not perform any tracking, but visualizes and quantifies any kind of tracked data. It analyzes trajectories by computing standard quantities such as velocity, acceleration, diffusion coefficient, local density, etc. Trajectories can also be plotted on the original image in 2D or 3D using custom color coding.
Track Analyzer provides a filtering section that can extract subsets of data based on spatiotemporal criteria. The filtered subsets can then be analyzed either independently or compared. This filtering section also provides a tool for selecting specific trajectories based on spatiotemporal criteria which can be useful to perform fate mapping and back-tracking.
Track Analyzer is distributed as two versions: an installation-free web-base tool run on Galaxy, and full version run on a user-friendly Jupyter notebook. On both versions, Track Analyzer can be run without any programming knowledge using its graphical interface. The full version interface is launched by running a Jupyter notebook containing widgets allowing the user to load data and set parameters without writing any code.