Hi community.
I’m running into a recurring issue with my cryoSPARC refinement and would appreciate any advice.
The problem:
Despite dropping particle count to ~80k and multiple rounds of 2D cleaning, I still get extra surrounding faces/density in refined maps. The core seems okay in ab-initio, but refinement degrades it. Both of them have good viewing direction distribution.
2D classification class averages:
Ab-initio result:
Homo refinement:
What I’ve tried:
Any suggestions would be greatly appreciated!
your 2D suggest extreme compositional heterogeneity - many different protein forms. these failed refinements are the expected result, and though the euler distribution looks great in theory, in practice it suggests failed alignment and you actually want 4-6 distinct patches to cover the angles and as evidence that it could well-assign repeating views to a common stucture. I would suggest a large dataset, ab initio with many models, an improved picking strategy, and maybe a more pure sample in the first place.
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Hi CryoEM2,
Thanks so much for the suggestion! I gave it a shot and ran ab initio with 6 models on ~1M particles, each using roughly 200k particles. It does seem to be helping with the junk, but I’m still seeing some faceted artifacts in the reconstructions, and the resolution has dropped compared to my previous run.
