Tomo refinement 2: Bayesian polishing

relion has also implemented the analogous to Bayesian polishing for tomography. This procedure refines the projections that map 3D space onto the images of the tilt series. Optionally, the beam-induced motion trajectories of the particles and deformations can also be estimated. For a complete description of the arguments, check the relion_tomo_align program.

If you are running this job without following the tutorial, please note the requirements for the reference map and FSC data as described in Reference map and FSC data.

Running the job

Select the Bayesian polishing job-type and set on the I/O tab:

Input optimisation set::

CtfRefine/job027/optimisation_set.star

OR: use direct entries?:

No

One of the 2 reference half-maps::

Reconstruct/job028/half1.mrc

Reference mask::

mask_align.mrc

Input postprocess STAR:

PostProcess/job029/postprocess.star

On the Polish tab, set:

Box size for estimation (pix):

512

Max position error (pix):

5

Align by shift only?:

No

Alignment model:

(Does not apply)

On the Motion tab, set:

Fit per-particle motion?:

Yes

Sigma for velocity (Å/dose):

0.2

Sigma for divergence (Å):

5000

Use Gaussian decay:

No

On the Running tab, set:

Number of MPI procs::

5

Number of threads::

12

Note that the per-particle motion estimation increases the processing time significantly. On our system it took around 2 hours.

Analysing the results

In the output folder Polish/job030 you will find new tomograms.star and particles.star files including the corrected tilt series alignment and particle positions and a trajectory set file motion.star with particle trajectories. To assess the result, we generate new particles with the Extract subtomos job using the resulting optimisation_set.star file, followed by Reconstruct particle and Post-processing. Compared to the previous FSC estimation, we observe a clear improvement and a resolution of 3.65Å.