Example dataset and results for Tui, a multi-generational and expert-correctable tracker for cellular dynamics

This repository provides example datasets and tracking results used to demonstrate the functionality of Tui, a multigenerational and expert-correctable cell tracking framework designed to reconstruct complex lineage dynamics including mitosis and fusion events. The dataset includes both synthetic benchmark data and experimental live-cell imaging data, along with segmentation masks and example tracking outputs generated by the Tui framework. These files are intended to facilitate method reproducibility, benchmarking, and demonstration of the Tui tracking workflow. Contents 1. Synthetic_SEQ01_sample data.zip Synthetic benchmark dataset containing simulated cell trajectories with controlled lineage events, including six programmed fusion events. This dataset is designed to test the ability of tracking algorithms to correctly identify and reconstruct complex lineage structures such as: mitosis (1→2 events) fusion (2→1 events) appearance and disappearance of cells The synthetic data allow validation of tracking algorithms under known ground-truth conditions. 2. T98G_electrotaxis.zip Experimental dataset of T98G glioblastoma cells undergoing electrotaxis under electric field stimulation. The dataset includes: time-lapse microscopy images human-curated segmentation masks manually curated lineage tracking annotations These annotations provide expert-validated references for evaluating tracking performance in real biological experiments involving cell migration and division. 3. Example_results.zip Example tracking outputs generated using the Tui ILP-based tracking framework, including: reconstructed trajectories lineage relationships tracking graphs These results illustrate the reconstruction of multigenerational lineage structures and demonstrate the handling of complex events such as mitosis and fusion. Segmentation Variants For the T98G electrotaxis dataset, two segmentation sources are provided: Human-curated segmentation masks Automated masks generated using Detectron2 This allows comparison between tracking performance under expert annotations and automated segmentation pipelines. Intended Use These datasets are provided as example inputs and outputs for the Tui tracking framework, enabling users to: reproduce example tracking workflows benchmark alternative tracking algorithms evaluate tracking robustness under synthetic and experimental conditions explore multigenerational lineage reconstruction with fusion and mitosis events Related Software Tui: A multigenerational and expert-correctable tracker for cellular dynamics The software reconstructs lineage graphs using an integer linear programming (ILP) formulation capable of modeling: transition events mitosis fusion appearance and disappearance License Please cite the associated publication when using these datasets.