Macromolecular complexes are intrinsically flexible and often challenging to purify for structure determination by single-particle cryo-electron microscopy (cryo-EM). Such complexes can be studied by cryo-electron tomography (cryo-ET) combined with subtomogram alignment and classification, which in exceptional cases achieves subnanometer resolution, yielding insight into structure-function relationships. However, it remains challenging to apply this approach to specimens that exhibit conformational or compositional heterogeneity or are present in low abundance. To address this, we developed emClarity ( https://github.com/bHimes/emClarity/wiki ), a GPU-accelerated image-processing package featuring an iterative tomographic tilt-series refinement algorithm that uses subtomograms as fiducial markers and a 3D-sampling-function-compensated, multi-scale principal component analysis classification method. We demonstrate that our approach offers substantial improvement in the resolution of maps and in the separation of different functional states of macromolecular complexes compared with current state-of-the-art software.
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