LineageTracker: A statistical scoring method for tracking cell lineages in large cell populations with low temporal resolution

摘要

Automated high-throughput analysis of single-cell timecourse data presents a major bottleneck in live cell imaging. We present LineageTracker, an ImageJ framework to track expression of fluorescent gene reporters over multiple cell divisions. It is able to perform automatic segmentation and tracking, and allows viewing and editing of tracks. The main feature of the tracking algorithm is a statistical scoring method which takes into account characteristic intensity and size changes to classify dividing and non-dividing cells. By including such dynamic features, the method can identify dividing cells in time series with 30 min frame intervals, and handle large cell displacements between frames. We created a manually validated data set of mouse C2C12 cells expressing a fluorescent protein targeted to the cell nucleus which we will make available for benchmarking different segmentation and tracking methods.