Hi everyone,
I hope this message finds you well. I have a question regarding workflow optimization in CryoSPARC and would greatly appreciate your insights.
In my previous lab, I typically followed the following workflow for single-particle cryo-EM computations:
- Ab-Initio Reconstruction: Run Ab-Initio on the particles to generate 3-5 initial volumes.
- Hetero-Refine: Use all the particles and all of the generated volumes from the Ab-Initio step as inputs in a Hetero-Refine task, which helps reassign classes by leveraging both the particles and the multiple initial reconstructions.
- Non-Uniform Refinement (nu-Refine): Merge the best-performing class(-es) and input them into a Non-Uniform Refine task for higher-resolution refinement.
If the results are unsatisfactory, I repeat the cycle of Ab-Initio → Hetero-Refine → nu-Refine. Occasionally, I also include the refined volume from the previous round of nu-Refine as an additional input in the next Hetero-Refine task to improve particle selection.
However, at my new school, I’ve noticed that some colleagues use a different workflow: Ab-Initio → nu-Refine → Hetero-Refine, which is quite different from what I’m used to. This has left me wondering about the rationale behind this approach.
Could anyone who has tried or is familiar with this alternative workflow (Ab-Initio → nu-Refine → Hetero-Refine) share their experiences? Specifically:
- Does this workflow have specific advantages under certain conditions?
- When might it be more beneficial to run nu-Refine immediately after Ab-Initio, rather than Hetero-Refine?
Any advice or insights would be greatly appreciated! Thank you in advance for your help.
Best regards,
Zhe