2015Heymann Alignability
Citation
Heymann, B. Validation of 3DEM Reconstructions: The phantom in the noise AIMS Biophysics, 2015, 2, 21-35
Abstract
Validation is a necessity to trust the structures solved by electron microscopy by single particle techniques. The impressive achievements in
single particle reconstr
uction fuel its expansion beyond a small community of image pr ocessing experts. This poses th e risk of inappropriate data processing with dubious results. Nowh ere is it more clearly
illustrated than in the recovery of a
reference density map from pure noi se aligned to that map—a phantom
in the noise. Appropriate use
of existing validating methods such as resolu tion-limited alignment and the processing of independent data sets (“gold standard”) avoid this pitfall. However, these methods can be undermined by biases introduced in various subtle ways. How can we test that a map is a coherent structure present in the images selected from the micrographs? In stead of viewing the phantom emerging from noise as a cautionary tale, it should be used as a defi ning baseline. Any map is always recoverable from noise images, provided a sufficie nt number of images are aligned and used in reconstruction. However, with smalle r numbers of images, the expected coherence in the real particle images should yield better reconstr uctions than equivalent number s of noise or background images, even without masking or imposing resolution limits as potential biases. The validation test proposed is therefore a simple alignment of a limited number of micrograph and noise images against the final reconstruction as reference, demons trating that the micrograph images
yield a better reconstruction. I
examine synthetic cases to relate the resolution of a reconstruction to the alignment error as a function of the signal-to-noi se ratio. I also administer ed the test to real cases of publicly available data. Adopting such a test can ai d the microscopist in assessing the usefulness of the micrographs taken before committing to lengthy processing with questionable outcomes.
Keywords
Validation
