STrack: A Tool to Simply Track Bacterial Cells in Microscopy Time-Lapse Images
Helena Todorov, Tania Miguel Trabajo, Jan Roelof van der Meer
Abstract
Automated image analysis of growing prokaryotic cell populations becomes indispensable with larger data sets, such as derived by time-lapse microscopy. The tracking of the same individual cells and their daughter lineages is cumbersome and prone to errors in image alignment or poor resolution. Here, we present a simplified but highly effective tool for non-specialists to engage in cell tracking. The tool can be downloaded and run as a contained script-structure requiring minimal user input. Run times are fast, in comparison to other equivalent tools, and outputs consist of cell tables that can be subsequently used for lineage analysis, for which we offer examples. By providing open code, training data sets, as well as simplified script execution, we aimed to facilitate wide usage and further tool development for image analysis.