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Estimate relative resolution

Recommendation

Please read the GUI overview and conduct the intro tutorial first.

OccuPy was not designed to accurately quantify local resolution, but rather to try to disregard contrast attenuation due to solely to variations in e.g. flexibility. It will however accurately estimate relative local resolution, which might inform you on what parts are consistent and favoured for alignment. This includes all effects, so think of it as a quality estimate of the map, rather than resolution.

Other tools are available to estimate resolution on an absolute scale, which might be more suitable to use. The benefit of OccuPy is that it is fast and easy to use and adjust, so that it's easier to use for qualitative map analysis.

This is not absolute resolution

You will not get a number that corresponds to the resolution at each point in the map. You will get a "quality" score that tells you how well resolved each region is, compared to the best resolved region.

1. First pass estimate

  1. Open the input map.
  2. Make sure that "occupancy" (just below the modifications options) is disabled, and estimate the scale.
  3. Click the button "Launch ChimeraX" to view the output.

2. Sanity check

  1. Check that the output log does not show any warnings (or errors).

3. Evaluate Kernel settings

Strong scatterers, variations in resolution, or any of a number of other factors may cause strong contrast. This means that the signal-to-noise ratio (SNR) is higher, which according to typical cryo-EM estimates more confidence in the estimated resolution, but not necessarily higher resolution. OccuPy evaluates contrast, which will be in proportion to SNR, which is thus not ideal for estimating resolution. It is thus prudent to be cautious, but OccuPy was built to be robust to outliers so with caution everything should be fine. Some settings may need be adjusted, nearly identically to that described in the tuorial to estimate occupancy. When you explore settings to increase the utility (and possibly also the fidelity) of the resolution estimate, note that this creates confirmation bias in the results based on your expectations. Always report the kernel settings used, which are documented in the full GUI log, or through command line by using --verbose.

To evaluate a new kernel setting, re-estimate the scale and inspect the "Scale" tab of the viewer. You can also re-name the file "scale_res_<input_file_name>.mrc" and open it manually in a ChimeraX-session opened through the GUI. Remember to use the chimeraX command-line tool to run "scale_color #1 #" to color the input map by the new scale.

3.1 Input lowpass

The input lowpass is inconsequential for the resolution estimation.

3.2 The Kernel radius and size

These define the region around each pixel where OccuPy determines the local scale. That is, the define what "local" means. The kernel size is the maximum box dimension, and the radius is that of a spherical mask placed at the center of that box. The kernel is determined as the intersection of these. the number of voxels in this intersection is shown as the number of samples.

Gist

The larger the kernel, the more samples and statistical certainty.
The larger the kernel, the more you average the estimate.
The kernel can typically be very small without problem.

Look at the "Scale" tab of the Occupy viewer. If your scale estimate...

  1. Looks like "blocks", then the kernel size is much smaller than the radius. This is not a problem, but you could reduce the radius to define a more spherical region around each map location.
  2. Looks much lower resolution that the input map, then you might do well to reduce the kernel size and radius.

3.3 Tau percentile

To reduce the influence of voxel-value outliers in the scale estimate, some voxel values are always "rejected". The tau percentile defines how many sample values should be rejected. The value of tau is optimally calculated based on your kernel settings (to reduce the probability of over- and under-estimating the scale), so you should not change it unless you have good reason to do so. Always report the kernel settings

Gist

Reducing the tau percentile will increase the resolution estimate (as in the estimate will indicate better resolution) of all regions, and vice versa.
Tau is automatically calculated to minimize both over- and under-estimation.

Look at the "Scale" tab of the viewer. In your scale estimate...

  1. is homogeneous and nearly all white, then you might have a very homogeneous resolution. If you want to push the relative resolution into a range where you might tell components apart, try increasing the tau percentile an re-estimate the scale.
  2. is only white for a very small region that does not correspond to what you would expect to be at "best resolution", try reducing the tau percentile. It might also be better to adjust the tile-size as we will soon discuss, and use the theoretically derived value for tau.

3.4 Tile size

OccuPy normalizes the estimated scale against a region of the map where it in some sense finds maximal contrast. The size of this region defines the size of the "best resolution" region. This region can be chosen smaller than you "best-resolution component", but if you make it too small then variations in atomic mass might start to affect the estimate.

Gist

Increasing the tile size will reduce the influence of high local mass, and vice versa.
Setting the tile-size too large will cause systematic over-estimation of local scale.

Look at the "Scale" tab of the viewer. In your scale estimate...

  1. is only white for a very small region that does not correspond to what you would expect to be at the best resolution, try increasing the tile-size.

4. Noise-level recalibration

OccuPy expects that the reconstruction is constructed from images which have been normalized such that the background (solvent) noise has zero mean. In this case, it is natural to expect zero occupancy to coincide with a pixel value of zero, which is thus implicitly assumed. This also makes the local scale estimate independent of the solvent (noise) model.

However, one may want to redefine zero scale to coincide with the noise distribution, as zero scale is expected to display solvent characteristics, especially when noise is high or resolution is low. Since version 0.1.11, OccuPy implements a noise-level recalibration option, which takes this into account. But this is not a one-stop solution to improve estimation in a high noise setting, since it demands an accurate solvent model, which may be difficult precisely in this circumstance.

Noise-level recalibration is accessible in the gui under "Optional/extra options", or on the command flag by adding the flag "--nlrc". Make sure to evaluate the solvent model and confidence estimate before relying on this option.

5. Final notes

  1. Because a reduced tile-size emphasizes variations in mass even when resolution is the same, a much reduced tile size is potentially useful to estimate relative mass or occupancy when the relative mass is known, but for resolution estimation it does not make much sense to reduce it too far.