SpinX: Automated Spindle Tracking and Analysis

Fig. S1 describes data composition, Fig. S2 details SpinX pipelines for automated label generation, Fig. S3 evaluates automated label generation using SpinX, Fig. S4 explains data augmentation techniques, Fig. S5 evaluates two SpinX models using IoU metric, Fig. S6 evaluates two SpinX models using Loss of function metric, Fig. S7 are example segmentations from different architectures, Fig. S8 evaluates SpinX Stage 3 for accuracy manually, Fig. S9 on cell cortex eccentricity, Fig. S10 presents spindle length and width measured through SpinX, Fig. S11 outlines analytical solution for 3D Ray-tracing, Fig. S12 compares Refined and Old SpinX algorithms for recording spindle pole positions, Fig. S13 shows increased spindle rotation following CENP-E inhibition, Fig. S14 shows no increase in spindle rotation following MARK2 inhibition, and Fig. S15 presents change in MARK2-YFP localization following its inhibition. Video 1 summarizes SpinX spindle and cortex tracking features. Table S1 shows comparison of SpinX with previous software for spindle and cell cortex detection and tracking. Table S2 shows differences between SpinX-base and SpinX-optimized. Table S3 shows evaluation of SpinX-base and SpinX-optimized models. Table S4 shows evaluation of annotation. Table S5 shows spindle tracking evaluation. Table S6 shows parameters used for PSF simulation.