Some of my NU refinements end up with the wrong hand of the protein. To change the hand, I use the Volume tools job to flip the hand, but then I end up with an unsharpened map. What would be work flow to achieve the same sharpening as in the refinement that would result in a map suitable for analysis and model building?
Flip hand -> Local Resolution estimation -> Local filtering -> Sharpening ?
Thank you for the help!
You can use the volume tools job to flip the hand of the sharpened map directly. If you drag the
map_sharp output result from the refinement into the
map input to the volume tools job, then it will flip the hand of the sharpened map and you can use that directly. You can also flip the hand of the half-maps individually if you want to do further processing with them (e.g. sharpen to specific b-factor, etc.). Check out our guide page on the job builder, and the “Fine-tuned control over Individual Results” section shows what this looks like for the case of local resolution estimation.
Thank you for the information, I wasn’t aware I can drag the individual components of the output.
Could you explain a bit more about the local filtering? Are NU-refinement maps locally filtered and how does the filtering affect the map?
Spatially non-uniform filtering is used to regularize the half-maps each iteration. The refinement iterates through the Expectation (alignment), Maximization (reconstruction), and Regularization steps until convergence. The actual maps that are output each iteration are those directly after the maximization – so the
map_sharp outputs for non-uniform refinement are raw reconstructions without local filtering done. The regularization step thus is intended to produce more accurate alignments. @apunjani may be able to comment more on the algorithmic differences; you can also check out the Nature Methods paper for a more detailed description.
As far as we are aware, there doesn’t seem to be a standard post-processing procedure, so local filtering may or may not be helpful for model building. Doing local resolution estimation --> local filtering --> sharpening might produce a map that looks a bit more interpretable than just the globally filtered map
PS: if you’re using the legacy version, there are a few differences between the new and legacy versions, and there’s a thread discussing the other map outputs (
map_filtered.mrc here: How is the Non-Uniform Refinement map_filtered map created). We generally suggest the “NEW” version be used as we’ve obtained superior map quality with it.