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Cryo-electron Microscopy

Cryo-electron Microscopy

Conventional electron microscopy (EM) involves dehydration, fixation, and staining of biological samples, which distorts the native state of biological molecules and results in several artifacts. Also, the high-energy electron beam damages the sample and makes it difficult to obtain high-resolution images. These issues can be addressed using cryo-EM, which uses frozen samples and gentler electron beams. The technique was developed by Jacques Dubochet, Joachim Frank, and Richard Henderson, for...

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Related Experiment Video

Updated: Dec 24, 2025

Cryo-EM and Single-Particle Analysis with Scipion

Cryo-EM and Single-Particle Analysis with Scipion

Published on: May 29, 2021

Confidence maps: statistical inference of cryo-EM maps.

Maximilian Beckers¹, Colin M Palmer², Carsten Sachse¹

¹Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL), Meyerhofstrasse 1, 69117 Heidelberg, Germany.

Acta Crystallographica. Section D, Structural Biology

|April 8, 2020

Summary

Confidence maps enhance cryo-EM interpretation by showing statistical significance against noise. This guide details their use in CCP-EM for better visualization of weak densities.

Keywords:

CCP-EM cryo-EM maps electron cryo-microscopy false-discovery rate family-wise error rate local resolution signal detection software

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Last Updated: Dec 24, 2025

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Area of Science:

Structural Biology
Biophysics
Computational Biology

Background:

Cryo-electron microscopy (cryo-EM) generates 3D density maps.
Interpreting these maps, especially weak or noisy densities, is challenging.
Confidence maps offer statistical significance information to aid interpretation.

Purpose of the Study:

To review the statistical concepts of confidence maps.
To provide practical guidance on interpreting and using confidence maps within the CCP-EM software.
To discuss limitations and potential extensions of confidence map usage.

Main Methods:

Statistical review of confidence map principles.
Practical demonstration of confidence map usage in CCP-EM.
Discussion of false-discovery rate (FDR) thresholding.
Exploration of alternative error criteria like family-wise error rate (FWER).

Main Results:

Confidence maps indicate statistical significance relative to background noise.
Thresholding confidence maps by false-discovery rate (FDR) highlights significant regions.
Common isosurface thresholds improve the rendering of weak and noisy densities.
CCP-EM provides tools for practical application and interpretation of confidence maps.

Conclusions:

Confidence maps are valuable for interpreting cryo-EM densities.
Practical guidance for CCP-EM users is provided.
Understanding confidence maps improves the analysis of challenging cryo-EM data.