Tweezepy

Tweezepy performs maximum likelihood–based force calibration for single-molecule force spectroscopy (SMFS) by estimating the drag coefficient (γ) and trap spring constant (κ) from video-tracked three-dimensional trajectories of micron-scale beads used in magnetic and optical tweezers.

Key Features:

• Maximum Likelihood Estimation (MLE): Derives parameter estimates and their uncertainties from single-bead trajectories using MLE.
• Power Spectral Density (PSD) analysis: Analyzes the PSD of bead motion to extract calibration parameters.
• Allan Variance (AV) analysis: Uses AV to characterize noise and thermal-motion statistics relevant to calibration.
• Drag coefficient (γ) estimation: Estimates the hydrodynamic drag coefficient γ from thermal bead motion.
• Trap spring constant (κ) estimation: Estimates the optical/magnetic trap spring constant κ from bead trajectories.
• Correction for spectral distortions: Accounts for spectral distortions that bias parameter estimates.
• Camera exposure time correction: Corrects for biases introduced by finite camera exposure time in video tracking.
• Parasitic noise handling: Accounts for parasitic noise sources affecting trajectory-based calibration.
• Alternative to least-squares fitting: Mitigates systematic biases typical of least-squares fitting methods.
• Support for tweezers data: Operates on trajectories acquired in magnetic and optical tweezers experiments.

Scientific Applications:

• Force calibration in SMFS: Calibrates forces applied to micron-scale beads in single-molecule force spectroscopy experiments.
• Thermal-motion parameter estimation: Quantifies thermal-motion-derived parameters such as γ and κ for biophysical analyses.
• Bias correction in calibration: Corrects for spectral distortions, camera exposure effects, and parasitic noise in calibration results.
• Tweezers experimental setup calibration: Provides calibrated parameters for magnetic and optical tweezers measurements.
• Uncertainty quantification: Supplies uncertainty estimates for calibrated parameters for use in downstream analyses.

Methodology:

Apply maximum likelihood estimation (MLE) to power spectral density (PSD) and Allan variance (AV) analyses of video-tracked 3D bead trajectories, with corrections for spectral distortions, camera exposure time, and parasitic noise to estimate γ and κ and their uncertainties while avoiding least-squares fitting biases.