Hej all,
I’ve been using 3D variability analysis in clustering mode with great success on a very tricky protein. The workflow is NU refinement, symmetry expansion with C3, then 3D variability in cluster mode. I now want to refine some of the clusters with NU refinement to get a final refinement with FSC, but how do I deal with my symmetry expanded particles? After all, they are not supposed to be used in normal refinement due to overestimation of resolution…
-Do I use NU refine on the output particles (i.e. still symmetry expanded) but in C1?
-Do I use “remove duplicates” to “reverse” the symmetry expansion? Is there a consensus on what cut off distance would be appropriate so I don’t loose neighbouring particles but only expanded particles?
-Or would I have to run 3D variability on non-expanded particles?
I searched for an answer here and in the tutorial and paper etc, but I’m still unclear on what workflow I should use. I guess the same question would apply to intermediate 3D variability mode if you output the particles.
Many thanks in advance,
Claudia
Hi Claudia,
You have a couple of options - like you say, you can remove duplicates - a cut off of half your particle diameter should be fine - and then proceed to NU, but if you have pseudo-symmetry that may lose you some of your gains from the classification you have performed using 3D-VA.
Probably the easiest though is to go directly from 3D-VA clustering to local refinement in C1 (still using the symmetry expanded particles). Local refinement using symmetry expanded particles is fine, but I would avoid global NU-refine, as this can superimpose duplicate particles, and lead to FSC funkiness.
Cheers
Oli
2 Likes
Hi @ClaudiaKielkopf ,
I agree with Oli – asymmetric (C1) local refinement is best for this use case. It can be used anytime you only want alignments to be searched locally, which is exactly the case with symmetry expanded particles (to prevent superimposing the same particle twice, as Oli mentioned). Since you have C3 symmetry, you shouldn’t have to worry about the alignment search radius being too large (assuming perfectly aligned particles, the alignments would have to deviate by 120º in order to superimpose duplicated particles).
Best,
Michael
Just to add @ClaudiaKielkopf - if you have pseudo-C3, I would also try symmetry relaxation in Relion starting from a consensus C3 refinement for this data. Symmetry relaxation is not yet available in cryosparc, but hopefully will be in future.
Hej Oli, hej Michael,
thank you very much for your advice and input! I’m sticking with local refinement for now, I’m indeed seeing pseudo-symmetry (I should have added, it’s a very thin elongated protein and I can see in 3DV that it bends to the left and the right). I’ll look into symmetry relaxation as well at some stage, I’ve only ever considered relaxation when there is a symmetry mismatch.
Best,
Claudia