Particles should be aligned again (see b12.ali) against the refined volume, as opposed to the reference volume.
All the files below are contained in occupancy.tar.gz
b01.dcf: B01.dcf uses the select files generated by b16.cla. It creates view files for each of the 83 projections.
b02.cpy: copies them into different directories.
b03.fit: (optional) shows sensitivity of the procedure. Particles must all have the same noise file.
Use SPIDER to create a spherical mask such that the desired ligand is contained within the sphere. Verify in explorer.
b05.pmk: projects the mask in the 83 directions.
b06.mth: Thresholds the 2D masks so they are binary again (they are not binary after being projected).
b09.clk: The main classifier batch file.
CA SI creates SEQ files
CA S (optional, if you would rather to classify on the pixel level) N = 5 factors (PIX#, IMC, EIG)
CL KM works directly on images. It needs the number of pixels under the mask, applies factor to every pixel.
2 specifies IMC; 1 to use SEQ made by CA SI
x40 = 2 = no. of classes
Calculate 2 averages according to class, the calculate resolution between averages.
AS DC creates avg*** and var*** files for both classes. You now have 83 x 2 averages, but which one has the ligand?
b10.sub: difference between averages & significance map
b11.fsm: always use the mask picstat002.ext
b11.stc: ?????? (unimportant)
b12.dcf: Finds which group (1 or 2) has the higher average. Then creates seltotal_h and seltotal_l, which contain the numbers of the aligned particles (in ali/sar*****), with high or low occupancy, respectively.
b23.bph: make the volume
The above routines do not use defocus. You can try to sort back into defocus groups.