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Detecting structural heterogeneity in single-molecule localization microscopy data

Author

Listed:
  • Teun A.P.M. Huijben

    (Department of Imaging Physics, Delft University of Technology)

  • Hamidreza Heydarian

    (Department of Imaging Physics, Delft University of Technology)

  • Alexander Auer

    (Faculty of Physics and Center for Nanoscience, Ludwig Maximilian University
    Max Planck Institute of Biochemistry)

  • Florian Schueder

    (Faculty of Physics and Center for Nanoscience, Ludwig Maximilian University
    Max Planck Institute of Biochemistry)

  • Ralf Jungmann

    (Faculty of Physics and Center for Nanoscience, Ludwig Maximilian University
    Max Planck Institute of Biochemistry)

  • Sjoerd Stallinga

    (Department of Imaging Physics, Delft University of Technology)

  • Bernd Rieger

    (Department of Imaging Physics, Delft University of Technology)

Abstract

Particle fusion for single molecule localization microscopy improves signal-to-noise ratio and overcomes underlabeling, but ignores structural heterogeneity or conformational variability. We present a-priori knowledge-free unsupervised classification of structurally different particles employing the Bhattacharya cost function as dissimilarity metric. We achieve 96% classification accuracy on mixtures of up to four different DNA-origami structures, detect rare classes of origami occuring at 2% rate, and capture variation in ellipticity of nuclear pore complexes.

Suggested Citation

  • Teun A.P.M. Huijben & Hamidreza Heydarian & Alexander Auer & Florian Schueder & Ralf Jungmann & Sjoerd Stallinga & Bernd Rieger, 2021. "Detecting structural heterogeneity in single-molecule localization microscopy data," Nature Communications, Nature, vol. 12(1), pages 1-8, December.
    • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-24106-8
    DOI: 10.1038/s41467-021-24106-8
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