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trackpy-particle-trackinglisted

Python library for single-particle tracking (SPT) in video microscopy via the Crocker-Grier algorithm. Locate particles (fluorescent spots, colloids, vesicles, cells) per frame, link into trajectories, filter short tracks, and compute MSD for diffusion analysis. 2D/3D with subpixel accuracy; reads TIF stacks, AVI, image series via pims. Use for quantitative SPT and diffusion coefficient extraction from fluorescence or brightfield video.
jaechang-hits/SciAgent-Skills · ★ 193 · Code & Development · score 79
Install: claude install-skill jaechang-hits/SciAgent-Skills
# trackpy ## Overview trackpy is a Python library for single-particle tracking (SPT) in video microscopy. It implements the Crocker-Grier algorithm to locate bright spots in each frame with subpixel precision, then links those positions across frames into continuous trajectories. From trajectories, trackpy computes mean squared displacement (MSD), diffusion coefficients, and motion classifications (confined, normal, directed). It handles 2D fluorescence videos, 3D confocal z-stacks, and large image sequences via memory-efficient streaming through the pims image reader library. ## When to Use - You have a fluorescence microscopy video of labeled particles (quantum dots, fluorescent beads, vesicles, receptors) and need to extract individual trajectories and diffusion coefficients. - You want to measure particle mobility: compute MSD curves and distinguish Brownian diffusion, directed motion, or confined motion from single-particle tracks. - You are analyzing colloid dynamics, lipid membrane diffusion, intracellular cargo transport, or virus-cell interactions where you need per-particle trajectory data. - You need 3D tracking from confocal z-stack time series to capture out-of-plane motion of particles or organelles. - You want to apply drift correction to remove stage drift before computing intrinsic particle motion statistics. - You need ensemble MSD averaged across hundreds of tracks to extract population-level diffusion behavior with statistical power. - Use `TrackMate`