Job: Homogeneous Refinement
Homogeneous refinement.
Last updated
Homogeneous refinement.
Last updated
Rapidly refine a single homogeneous structure, using a particle stack an initial reference, to high-resolution and validate using the gold-standard FSC. Support refinement with higher-order aberration (beam tilt, spherical aberration, trefoil, tetrafoil) correction, per-particle defocus refinement on the fly.
As of CryoSPARC v3.3, Homogeneous Refinement also supports and .
Particles
Initial model
Mask (optional)
Refinement box size (Voxels): This determines the size of the internally stored volume. If this is null, the full particle size is used, otherwise images are automatically downsampled. This can be decreased to reduce memory requirements and increase speed, at the expense of omitting higher-resolution information.
Symmetry Parameters:
Symmetry: This is the symmetry string corresponding to the enforced point-group symmetry to use during refinement. The allowed point group symmetry enforced are:
Cyclic (Cn, e.g. C2, C6, etc.)
Dihedral (Dn, e.g. D4, D7, etc.)
Tetrahedral (T)
Octahedral (O)
Icosahedral (I)
Symmetry relaxation method: Controls the method used for symmetry relaxation. Leave as 'none' to disable symmetry relaxation. Set to 'maximization' to enable symmetry relaxation without pose marginalization. Set to 'marginalization' to enable symmetry relaxation with pose marginalization within a symmetry mode. Note that when symmetry relaxation is enabled with a point group of order N, particles will only contribute to one of the N symmetry-related modes. Note if this is set to maximization or marginalization, this overrides the value of the 'Adaptive Marginalization' parameter. Refer to the for an in-depth guide to this feature.
Do symmetry alignment: Activate this to align the input structure to the conventional symmetry axes used by CryoSPARC.
Re-estimate greyscale level of input reference: This can be enabled to estimate the multiplicative factor that correctly re-scales the reference to match the greyscale of the images. It is recommended to keep this on, especially if the input references are imported from elsewhere rather than generated within CryoSPARC.
Number of extra final passes: Normally, refinement terminates when the gold standard FSC resolution stops improving. However, extra iterations can be forced by setting this parameter to the desired number of extra iterations.
Maximum align resolution (A): This can be set to limit the resolution of information used for alignment. By default, information up to the gold standard FSC resolution is used for alignment, but higher resolution information can be ignored by setting this parameter. This can occasionally help prevent the build up of high-frequency overfit noise.
Initial lowpass resolution (A): The resolution to which the initial reference is lowpass filtered can be controlled by setting this parameter to the desired resolution in Angstroms. For smaller molecules, it may help to decrease this value to around 20 Å.
GSFSC split resolution (A): The resolution to which each half-set is considered independent can be controlled by setting this parameter.
Force re-do GS split: Force re-splitting the particles into two random gold-standard halves. If this is not set, split is preserved from input alignments (if connected).
Adaptive Marginalization: Efficiently marginalize over poses and shifts using an auto-tuning adaptive sampling strategy. Can improve results on small molecules.
Minimize over per-particle scale: This enables estimation of per-particle scale factors during Expectation-Maximization. This can help if ice thicknesses varied greatly during data collection. The iteration at which per-particle scale estimation begins can be controlled by setting the Scale min/use start iter parameter to the desired iteration number.
B-Factor for plotting: This sets the b-factor used during map sharpening and plotting. Negative values sharpen the structure, and positive values blur the structure. By default, Guinier estimation determines the b-factor used at each iteration.
Computational minibatch size: This controls the number of images in each minibatch, which influences the amount of memory that needs to be allocated for each batch. If GPU memory is limited, the minibatch size can be decreased to prevent memory allocation errors; if there is ample GPU memory, this could be increased.
Mask (dynamic, static, none): This controls the type of masking to use. This can be set to the following options:
dynamic, in which case a dynamic mask will be generated based on the reference at each iteration according to the dynamic masking parameters below.
static, in which case an initial mask must be provided, and it will be used unmodified at each iteration.
none, in which case no mask will be used during the refinement.
Dynamic masking parameters:
Dynamic mask near (A): This controls the distance (away from the thresholded reference) at which the mask is dilated. At the near distance, the mask value is 1.0.
Dynamic mask far (A): This controls the distance (away from the thresholded reference) at which the mask is softly reduced to 0.0.
Dynamic mask start resolution (A): When the map reaches this resolution (in Angstroms), dynamic masking will start.
Cache particle images on SSD: Particle images can be copied to the SSD for much faster read times during refinement, which dramatically speeds up the job. If this is enabled, particle images will remain cached on the SSD for future jobs using the same particle stack and running on the same node.
Refined 3D map
Half-maps
Mask used in refinement
Mask used in FSC calculation
Gold-standard FSC curve
Plots, including orientation distribution
Refer to Job: Homogeneous Refinement (Legacy) for a description of the legacy version of Homogeneous Refinement. Note that the legacy job does not support higher-order aberration correction, adaptive marginalization, or Ewald Sphere correction.
Download and inspect map
Launch a job to sharpen the volume with different b-factors
Launch a job to generate templates from the reference, and iterate particle picking using the