Job: Orientation Diagnostics
A new job in CryoSPARC v4.4+ to diagnose the presence of preferred orientation
Description
Orientation Diagnostics is a job (new in CryoSPARC v4.4) that can aid in diagnosing the presence of preferred orientation. It includes and builds upon 3DFSC (Tan et al., 2017) and Fourier Sampling (Baldwin & Lyumkis, 2020).
By default, Orientation Diagnostics reports a single number: the conical FSC area ratio, or cFAR. cFAR values below 0.5 generally indicate the presence of preferred orientation. cFAR accounts for both the viewing direction distribution and the signal content present within each particle by quantifying the variance of directional half-map Fourier correlations across the viewing sphere.
If particles are supplied, the job will also report the Sampling Compensation Factor or SCF* (Baldwin & Lyumkis, 2020 — see below for more information about the significance of the star). SCF* values below 0.81 generally indicate the presence of preferred orientation. SCF* characterizes the sampling of Fourier shells by considering the viewing directions of all particles, without accounting for the signal content contained therein. A junk particle is given equal weight to a real particle.
We provide a short summary of the two metrics below. Please see the detailed definitions at the end of this job guide or the Orientation Diagnostics tutorial for more information.
cFAR and SCF* at a glance...
Range | Anisotropy Threshold | A function of… | |
---|---|---|---|
cFAR | [0, 1] higher is better | 0.5 | alignments & particle images |
SCF* | [0, 1] higher is better | 0.81 | alignments only |
cFAR | SCF* | Conclusion |
---|---|---|
↑ | ↑ | No orientation bias |
↑ | ↓ | ? (inconclusive, perhaps a pathological alignment distribution) |
↓ | ↑ | Anisotropy due to junk or other contaminants |
↓ | ↓ | Anisotropy due to junk and/or preferred orientation |
Input
Volume
[Optional] Particles
If supplied, Fourier sampling (and its associated metric, SCF*) will be computed along with other per-particle diagnostics
[Optional] Mask
If supplied, half-maps will be masked prior to the computation of conical FSCs
Common Parameters
Conical FSC
Number of Directions
The conical FSC Area Ratio (cFAR) metric is relatively robust to number of conical axis directions. However, reducing this number can speed up the job for volumes with large box sizes. Increasing this number will create denser spherical plots.
Sampling Compensation Factor
Symmetry
Particle viewing directions will be expanded to account for symmetry. This parameter should be set to the symmetry applied in the upstream refinement.
Output
3DFSC volume
A volume of radial cFSC curves interpolated at each 3D voxel location
Common Next Steps
Particle picking (to find missing views)
More details about cFAR and SCF*
cFSC Weighted Area-under-Curve (wAuC)
Given a conical Fourier shell correlation, , (where is the Fourier radius in wave number and is the conical axis), we define the wAuC as
\begin{align}\text{wAuC}(\hat{v}) &\overset{\Delta}{=} \sum_r w_r C_r(\hat{v}) \\ &= \sum_r 4 \pi r^2 C_r(\hat{v}). \end{align}
In this weighted sum, the Fourier radius, , ranges from the DC component to the radius at which first crosses 0.143. Intuitively, for each Fourier radius , the correlation between the half maps is multiplied by the surface area of the Fourier shell at . The final result is proportional to the ‘mass’ of the cone in units of correlation.
cFSC Area Ratio (cFAR)
We define the cFSC as the ratio of the minimum to the maximum over , or
Sampling Compensation Factor (SCF*) (Baldwin and Lyumkis, 2020)
SCF* measures orientation bias in particle viewing directions — it allows CryoSPARC to convert a potentially difficult-to-parse viewing distribution into a single metric.
SCF* is computed from the statistics of ‘Fourier sampling’. Given a single particle, Fourier sampling is a binary function that indicates which ‘slab’ (i.e., a stack of slices) of Fourier voxels are affected when the particle is used in back-projection. Summing this sampling over many particles allows one to see if large chunks of Fourier space are poorly sampled or missing completely. The degree to which this occurs is measured by the Sampling Compensation Factor—a single number that quantifies the extent to which anisotropic viewing direction distributions attenuate the global FSC value.
Plot Explanations
cFSC wAuC vs. conical axis
The wAuC of a cFSC curve is a proxy for directional signal content. If wAuC is relatively constant when the conical axis is varied, then the signal is isotropic in viewing direction. This plot helps illustrate the variation in cFSC wAuC and can aid in diagnosing the ‘structure’ of anisotropy.
cFSC resolution vs. conical axis
This plot is similar to the plot above, but visualizes the 0.143 crossing, rather than wAuC, of each cFSC curve.
Summary of cFSC curves
We summarize all cFSC curves in this plot, visualizing statistics as a function of spatial frequency rather than conical axis.
cFSC summaries within azimuth/elevation regions
To add back in a coarse notion of directionality to the above plot, we reproduce the same statistics for twelve different regions of axis space. This plot can help identify differences in cFSC variance to further elucidate the source of anisotropy.
3DFSC volume
The 3DFSC volume (Tan et. al, 2017) is another way to summarize cFSC curves by storing them in a volume whose voxels are interpolated from cFSC values at the nearest conical axis. In this plot, we visualize the 3DFSC volume via central slices. The ‘sphericity’ of the volume (which is output by the job) is a proxy for anisotropy.
Fourier Sampling
(Only generated if particles are connected). These plots visualize the Fourier sampling accumulated over a random subset of the particle viewing directions (default: 10000) — Fourier sampling is anti-podally symmetric (and hence only has ~ bins) so we visualize only the hemisphere, following the original publication (Baldwin, P. R., & Lyumkis, D., 2020). N.B., the elevation / azimuth plot on the left should be visually similar to the Posterior Precision plot as posterior precision measures Fourier sampling modulated by the CTF.
Particle scale factor vs. viewing direction
(Only generated if particles are connected and per-particle scales are not all 1.0). This figure visualizes the average particle scale for a set of viewing directions (uniformly sampled on the viewing sphere).
References
Tan et al. (2017), Addressing preferred specimen orientation in single-particle cryo-EM through tilting. Nat Methods 14(8), 793-796.
Baldwin, P. R., & Lyumkis, D. (2020). Non-uniformity of projection distributions attenuates resolution in Cryo-EM. Progress in biophysics and molecular biology 150, 160-183.
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