This title appears in the Scientific Report :
2020
Please use the identifier:
http://hdl.handle.net/2128/25483 in citations.
Please use the identifier: http://dx.doi.org/10.1016/j.jsb.2020.107579 in citations.
Permutation testing of Fourier shell correlation for resolution estimation of cryo-EM maps
Permutation testing of Fourier shell correlation for resolution estimation of cryo-EM maps
Fourier shell correlation (FSC) has become a standard quantity for resolution estimation in electron cryo-microscopy. However, the resolution determination step is still subjective and not fully automated as it involves a series of map interventions before FSC computation and includes the selection...
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Personal Name(s): | Beckers, Maximilian (Corresponding author) |
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Sachse, Carsten (Corresponding author) | |
Contributing Institute: |
Strukturbiologie; ER-C-3 |
Published in: | Journal of structural biology, 212 (2020) 1, S. 107579 - |
Imprint: |
San Diego, Calif.
Elsevier
2020
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PubMed ID: |
32693019 |
DOI: |
10.1016/j.jsb.2020.107579 |
Document Type: |
Journal Article |
Research Program: |
Functional Macromolecules and Complexes |
Link: |
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Publikationsportal JuSER |
Please use the identifier: http://dx.doi.org/10.1016/j.jsb.2020.107579 in citations.
Fourier shell correlation (FSC) has become a standard quantity for resolution estimation in electron cryo-microscopy. However, the resolution determination step is still subjective and not fully automated as it involves a series of map interventions before FSC computation and includes the selection of a common threshold. Here, we apply the statistical methods of permutation testing and false discovery rate (FDR) control to the resolution-dependent correlation measure. The approach allows fully automated and mask-free resolution determination based on statistical thresholding of FSC curves. We demonstrate the applicability for global, local and directional resolution estimation and show that the developed criterion termed FDR-FSC gives realistic resolution estimates based on statistical significance while eliminating the need of any map manipulations. The algorithms are implemented in a user-friendly GUI based software tool termed SPoC (https://github.com/MaximilianBeckers/SPOC). |