Abstract
Confidence maps provide complementary information for interpreting cryo-EM densities as they indicate statistical significance with respect to background noise. They can be thresholded by specifying the expected false-discovery rate (FDR), and the displayed volume shows the parts of the map that have the corresponding level of significance. Here, the basic statistical concepts of confidence maps are reviewed and practical guidance is provided for their interpretation and usage inside the CCP-EM suite. Limitations of the approach are discussed and extensions towards other error criteria such as the family-wise error rate are presented. The observed map features can be rendered at a common isosurface threshold, which is particularly beneficial for the interpretation of weak and noisy densities. In the current article, a practical guide is provided to the recommended usage of confidence maps.
Highlights
The 3D structure obtained from an electron cryo-microscopy experiment corresponds to the Coulomb potential in 3D space of the macromolecule of interest in three dimensions (Frank, 2006)
To develop a more robust framework for associating the values of a cryo-EM map with significance, we have recently presented a statistical framework based on multiple hypothesis testing and false-discovery rate (FDR) control, which transforms the cryo-EM map into a new volume that we term a confidence map (Beckers et al, 2019)
Confidence maps provide complementary cryo-EM map information that is helpful for the interpretation of weak and ambiguous signal close to background-noise levels. In this CCP-EM Spring Symposium article, we review the basic principles of confidence maps and focus our presentation on practical aspects and extensions of the procedure as it is integrated in the CCP-EM software suite
Summary
The 3D structure obtained from an electron cryo-microscopy (cryo-EM) experiment corresponds to the Coulomb potential in 3D space of the macromolecule of interest in three dimensions (Frank, 2006). For the interpretation of high-resolution map features, a B-factor sharpening approach is applied and combined with a signal-to-noise based weighting of the amplitudes (Rosenthal & Henderson, 2003). Confidence maps provide complementary cryo-EM map information that is helpful for the interpretation of weak and ambiguous signal close to background-noise levels. In this CCP-EM Spring Symposium article, we review the basic principles of confidence maps and focus our presentation on practical aspects and extensions of the procedure as it is integrated in the CCP-EM software suite
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