.. Doppio Tomography Tutorial documentation master file, created by sphinx-quickstart on Tue Feb 18 13:09:38 2025. You can adapt this file completely to your liking, but it should at least contain the root `toctree` directive. High resolution 3D refinement =========================================== In this step, we'll do a high resolution 3D refinement using the particles that we obtained from the last particle selection step. The high resolution refinement needs subtomograms and a reference obtained at bin 1 level. Below tables summarizes our input parameters for the **Extract**, **Reconstruct particle**, and the **3D refinement** jobs. Extraction of pseudosubtomograms (*relion.pseudosubtomo*) ---------------------------------------------------------------- ====================================== ======================================== Input params. Bin 1 ====================================== ======================================== Input optimisation set: Input tomogram set: ``Tomograms/job006/tomograms.star`` Input particle set: ``Select/job017/particles.star`` Box size (binned pix): 512 Cropped box size (binned pix): 192 Binning factor: 1 **Outputs:** Pseudosubtomograms star file: ``Extract/job018/optimisation_set.star`` ====================================== ======================================== Reconstruct particle (*relion.reconstructparticletomo*) -------------------------------------------------------------- ====================================== ======================================== Input params. Bin 1 ====================================== ======================================== Input optimisation set: ``Extract/job018/optimisation_set.star`` Input tomogram set: Input particle set: Box size (binned pix): 512 Cropped box size (binned pix): 192 Binning factor: 1 Symmetry: ``C6`` **Outputs:** 3D reference density map: ``Reconstruct/job019/merged.mrc`` half1 density map: ``Reconstruct/job019/half1.mrc`` half2 density map: ``Reconstruct/job019/half2.mrc`` ====================================== ======================================== 3D refinement (auto-refine) -------------------------------- ====================================== ================================================== Input params. Bin 1 ====================================== ================================================== Input optimisation set: ``Extract/job018/optimisation_set.star`` Reference map: ``Reconstruct/job019/half1.mrc`` Reference mask (optional): ``align_mask.mrc`` (note below) Ref. map is on absolute greyscale? Yes Resize reference if needed? Yes Initial low-pass filter (A): 5.5 Symmetry: ``C6`` Do CTF-correction? Yes Ignore CTFs until first peak? No Mask diameter (A): 230 Mask individual particles with zeros? Yes Use solvent-flattened FSCs? Yes Use Blush regularisation? No Initial angular sampling: 1.8 Initial offset range (pix): 5 Initial offset step (pix): 1 Local searches from auto-sampling: 1.8 Relax symmetry: Use finer angular sampling faster? No Prior width on tilt angle (deg): 10 Use parallel disc I/O? Yes Number of pooled particles: 30 Skip padding? No Skip gridding? Yes Pre-read all particles into RAM? No Copy particles to scratch directory: Combine iterations through disc? No Use GPU acceleration? Yes Number of MPI procs: 5 Number of threads: 8 **Outputs:** Achieved Resolution (A) 5.18 Refined particles ``Refine3D/job020/run_data.star`` Optimisation set ``Refine3D/job020/run_optimisation_set.star`` Refined averaged density map: ``Refine3D/job020/run_class001.mrc`` half1 density map: ``Refine3D/job020/run_half1_class001_unfil.mrc`` half2 density map: ``Refine3D/job020/run_half2_class001_unfil.mrc`` ====================================== ================================================== **Reference mask** In the high-resolution 3D refinement, we often use a mask to improve the final alignment. The alignement mask covers the region of interest, and in this case, the diameter of the mask is roughly about 230 A and it covers only the HIV capsid and excludes the matrix. We have used a disc-shaped mask generated from a custom Python script (explained elsewhere) but you may use other tools to generate your own masks. As the mask is used in the alignement, make it simple and less detailed. We include below screenshots for your reference. .. figure:: ../_static/images/STA/align_mask.png :alt: Example image :width: 100% :align: center Orthogonal views of alignment mask (``align_mask.mrc``) **Solvent mask** In the Postprocessing step below, we use another mask called ``fsc_mask.mrc`` to exclude the solvent area from the HIV hexemer. This covers only the central hexemer as you see in the screenshots below: .. figure:: ../_static/images/STA/fsc_mask.png :alt: Example image :width: 100% :align: center Orthogonal views of solvent mask (``fsc_mask.mrc``) Removing further duplicate particles ------------------------------------ During refinement, particles's positions change. It is a good idea to furhter check for duplicated particles. We have removed duplicated particles within 50 A radius after the high resolution refinement. Removal of duplicates (*relion.select.removeduplicates*) ---------------------------------------------------------------- ====================================== ======================================== Input params. Values ====================================== ======================================== OR select from particles.star: ``Refine3D/job020/run_data.star`` Minimum inter-particle distance (A) 50 **Outputs:** Particle star file: ``Select/job021/particles.star`` ====================================== ======================================== Reconstruct particle (*relion.reconstructparticletomo*) -------------------------------------------------------------- ====================================== ======================================== Input params. Values ====================================== ======================================== Input optimisation set: Input tomogram set: ``Tomograms/job006/tomograms.star`` Input particle set: ``Select/job021/particles.star`` Box size (binned pix): 512 Cropped box size (binned pix): 192 Binning factor: 1 Symmetry: ``C6`` **Outputs:** 3D reference density map: ``Reconstruct/job022/merged.mrc`` half1 density map: ``Reconstruct/job022/half1.mrc`` half2 density map: ``Reconstruct/job022/half2.mrc`` ====================================== ======================================== Post processing (*relion.postprocess*) ---------------------------------------- ====================================== ============================================= Input params. Values ====================================== ============================================= One of the 2 unfiltered half-maps: ``Reconstruct/job022/half1.mrc`` Solvent mask: ``fsc_mask.mrc`` **Outputs:** Postprocessed map: ``Postprocess/job023/postprocess.mrc`` Postprocessed masked-map: ``Postprocess/job023/postprocess_masked.mrc`` ====================================== ============================================= At the end of post-processing we obtained a map with 5.08 A resolution as confirmed by the gold-standard FSC curve below. .. figure:: ../_static/images/STA/pp_bin1_views.png :alt: Example image :width: 100% :align: center Left- FSC curve; Right- Density view of the postprocessed-masked map We refer you to the Relion documentation for more details. `Relion 3D refinement documentation `_.