Noise Model Variance - Flat vs Ascending

Hello-

Sometimes (rarely) I see that the noise model during 3D refinment that is flat (left below)
.

I have seen this on 3 of around >150 data sets or so. These examples images above are both for sub 3A unbinned data sets.

For one case the raw movies were redone and particles reimported and the noise variance returned to ascending as a function of resolution similar to what is seen right above.

I was curious as to 1) why this is, 2) how might one overcome these issues when they arise and 3) any further or deeper insights anyone might have.

Thank you!
-Jon

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Hi @UNCuser,

Could I ask when you did the initial motion correction for the datasets that show this issue (i.e. that have the flat noise model)? In v3.0 and v3.1, there was a transient issue in Patch Motion Correction that caused dose weighting to be incorrectly applied in some cases (this was caused by the introduction of variable-dose support in v3.0). This was fixed as of March 29, 2021 in v3.2 and we noticed the issue through a similar observation to your own – so it would explain your observations if the raw data was motion corrected in v3.0 or 3.1.

For best results, I’d recommend re-doing the motion correction on these datasets. Empirically it’s generally seen that the noise variance increases at higher frequencies with most datasets.

Best,
Michael

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Just found this and it retrospectively explains a number of things we have observed - mainly that we had a few datasets for which we were seeing unusually large improvements from Bayesian polishing, and often from multiple rounds of Bayesian polishing (e.g. one improved from 2.7 to 2.2). Looking back at them, these datasets were ~late 2020 → ~early 2021, and they exhibited flat noise models like this, which changed to ascending after polishing. So I guess any data collected between Dec 2020 and March 2021 is worth reprocessing.

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Hi @olibclarke is the dataset you are referring to (2.7A → 2.2A) the same that you mentioned here: Use patch based motion correction as prior for local motion correction? - #5 by olibclarke ?
You are correct that it is worth re-doing motion correction for datasets originally processed between Dec 2020 and March 2021 (or on versions v3.0 and v3.1).

Yes indeed it is the same dataset

What are your typical gains from polish and CTF refinement?

It very much depends - for CTF refinement depends on particle size (for local CTF refinement) and data collection (for global CTF refinement). Gains from global CTF refinement can be minimal or huge, depending on beam tilt (and I would always recommend at least running one global CTF as a diagnostic). Gains from polishing usually on the order of 0.1Å plus or minus.

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What does a flat noise model variance implies, reading the discussion in this thread it was indicated that it could be due to an earlier version issue with motion correction, however, I still see the flat noise curve like the one on the left of the original post? I am using v3.3.1+220215 and had done a path motion correction. Interestingly in another unrelated dataset where I have smaller particles ~200 KDa (the flat one has 1.2 MDa complex), I have noise model variance as on the right graph.
Please help me understand this and do I need to change something in my motion correction as my current map is stuck at 3.5A. Many Thanks

Hello Oli, @olibclarke
What if after global CTF the noise variance remais accending? What will that mean?

Thanks,
Dmitry