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Tweezepy: A Python package for calibrating forces in single-molecule video-tracking experiments

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  • Ian L Morgan
  • Omar A Saleh

Abstract

Single-molecule force spectroscopy (SMFS) instruments (e.g., magnetic and optical tweezers) often use video tracking to measure the three-dimensional position of micron-scale beads under an applied force. The force in these experiments is calibrated by comparing the bead trajectory to a thermal motion-based model with the drag coefficient, γ, and trap spring constant, κ, as parameters. Estimating accurate parameters is complicated by systematic biases from spectral distortions, the camera exposure time, parasitic noise, and least-squares fitting methods. However, while robust calibration methods exist that correct for these biases, they are not always used because they can be complex to implement computationally. To address this barrier, we present Tweezepy: a Python package for calibrating forces in SMFS video-tracking experiments. Tweezepy uses maximum likelihood estimation (MLE) to estimate parameters and their uncertainties from a single bead trajectory via the power spectral density (PSD) and Allan variance (AV). It is well-documented, fast, easy to use, and accounts for most common sources of biases in SMFS video-tracking experiments. Here, we provide a comprehensive overview of Tweezepy’s calibration scheme, including a review of the theory underlying thermal motion-based parameter estimates, a discussion of the PSD, AV, and MLE, and an explanation of their implementation.

Suggested Citation

  • Ian L Morgan & Omar A Saleh, 2021. "Tweezepy: A Python package for calibrating forces in single-molecule video-tracking experiments," PLOS ONE, Public Library of Science, vol. 16(12), pages 1-18, December.
  • Handle: RePEc:plo:pone00:0262028
    DOI: 10.1371/journal.pone.0262028
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    References listed on IDEAS

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    1. Terence R. Strick & Vincent Croquette & David Bensimon, 2000. "Single-molecule analysis of DNA uncoiling by a type II topoisomerase," Nature, Nature, vol. 404(6780), pages 901-904, April.
    2. Helen Shen, 2014. "Interactive notebooks: Sharing the code," Nature, Nature, vol. 515(7525), pages 151-152, November.
    3. Helen Shen, 2014. "Interactive notebooks: Sharing the code," Nature, Nature, vol. 515(7525), pages 152-152, November.
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