Number of 2D classes
to 5, andForce Max over poses/shifts
to true.Filament diameter (A)
: The estimated diameter of the filament, in AngstromsSeparation distance between segments (diameters)
: The distance between adjacent picks along a filament, in terms of multiples of the filament diametercurvature
: This is the estimated curvature (1/Ã…) of the filament at the pick location. Local curvature is useful to prune out the most bent locations along a filament, without removing all picks from that filamentsinuosity
: This is the ratio between the actual filament contour length, and the straight line start-to-end distance. Filament sinuosity is useful to remove entire filaments that may correspond to contaminants or aggregated filamentsLocal Power
: under 1296550Curvature
: under 0.0004Sinuosity
: under 1.08Align filament classes vertically (BETA)
parameter in any 2D classification job.Number of 2D classes
: 100Align filament classes vertically (BETA)
: TrueBatchsize per class
: 400 (since these filaments are rather small)filament
in-plane rotation estimates, which are written to either during filament tracing or 2D classification. Note that this generates a "cylindrical" density from the input particles – for filaments with highly oblong cross sections (e.g. amyloid filaments), Ab-Initio Reconstruction may produce a better initial model. We have generally seen that for filaments that are approximately cylindrical, and have constant diameter, directly running a helical refinement from the particles is more successful than running an ab-initio reconstruction job. Conversely, for filaments that are distinctly not cylindrical, ab-initio reconstruction can take advantage of the diversity of views along the helical axis, and often results in a better initial model.symmetry_candidates.cs
file.map_sym_sharp.mrc