TomoAlign has been designed to deal with the beam-induced sample motion and 3D-CTF in cryoET. The package is especially suited for cryoET of thick specimens where fiducial markers are required for accurate tilt-series alignment and sample motion estimation.
The sample motion is modelled during tilt-series alignment by means of either polynomial surfaces or interpolation splines from the residuals. The IMOD alignment can be imported as the initial point in this step. The motion model is then integrated in the tomographic reconstruction to produce motion-corrected tomograms. In a subsequent step, motion-corrected subtilt-series centered on the particles of interest are extracted. In addition, the defocus of each particle at each tilt image is determined and can be corrected, resulting in motion-corrected and CTF-corrected subtilt-series from which the subtomograms can be computed. Alternatively, the CTF information can be passed on so that CTF correction can be carried out entirely within Relion. Subtomograms and CTF information can be directly fed into Relion for subsequent high-resolution subtomogram averaging.
The package also contains an alternative alignment approach for very thin samples: non-rigid tilt-series alignment. Here, the images of the tilt-series are warped to compensate for the motion. As a result, a pseudo-perfectly aligned tilt-series is produced, thereby enabling the use of standard programs for the subsequent tomographic reconstruction.
A detailed description of the procedures implemented in the package can be found in the following articles:
Primary publications to cite:
Cryo-tomography tilt-series alignment with consideration of the beam-induced sample motion
Journal of Structural Biology 202:200-209, 2018.
Consideration of sample motion in cryo-tomography based on alignment residual interpolation
Journal of Structural Biology 205:1-6, 2019.
TomoAlign: A novel approach to correcting sample motion and 3D CTF in CryoET
Journal of Structural Biology 213:107778, 2021.
SBGrid Webinar: (April 2019)
Tutorial: (March 2021)