Sequence of steps necessary to detemine single particle structure using negative stain data

  1. Convert scanned tiff micrographs into spider files. The files can be examined using e2display.py.

    • i. Run sxcopyfromtif.py . ( Type & to send the program to background so as to free the current window:

    • sxcopyfromtif.py & )

    • ii. Set foc=f because all the stain micrographs are scanned from films.
    • iii. Make sure the output directory exists. Create the output directory before running the program, if the output directory does not exist.
    • iv. At this stage, one has to be aware about the pixel size `P_S` of scanned micrograph, or CCD frames.

    • $P_S=S/M$
    • S is the scan step size of scanner, or step size of CCD camera (S of CCD in Polara is `15*10^(-6)m`). The two NiKon scanners have identical scan step size : `6.35*10^(-6) m` M is the magnification at which the images are taken.

    • Warning: Don't use a name twice when one names raw images during taking micrographs in one project.
  2. Calculate power spectra of all micrographs, examine them, delete micrographs that show drift, have no Thon rings and so on... We will ignore defocus settings from this point on. As this is stain data, the pictures were collected sufficient close to focus so we do not have to worry about the CTF correction. At the same time, no micrographs far from focus should be used...

    • i. Calculate power spectrum using Welch's periodogram: Run sxwelch_psp.py.

    • ii.Properly set mask radius (10 pixels or more ) will help one to identify drifts or astigmatism in the power spectra.
    • iii. One dimensional power spectra(having roo_ as prefix) allow one to identify resolution easier.
    • iv. We determined that the micrographs are taken at around 0.5 micron(5000Angstrons) under focus. So the first CTF zero appears around 14 Angtrons in power spectrum.
  3. Run the automated particle program, particles from each micrograph are in a separate stack file in spider format.

    • i. Run sxauto_picking.py

    • ii.The template file has to be created before using this command.
    • iii. Properly set n_plt helps one to reduce output trash particles.
    • iv. Select a noise image from an arbitary micrograph. Save the coordinate file in text tile as noisedoc.spi.
  4. Screen all stack files and delete windows that do not contain particles. This is done using program e2display.py:

    • i. v2 <stackfile>

    • ii. middle-click on the image display
    • iii. select 'del' mode from the instpector window
    • iv. click on the particles you want to get rid of
    • v. when done, write the results to a new stack file
    • vi. delete input stack file.
      • Warning: deleted particles vanish permanently. However, assuming the micrographs are still around and one knows the parameters of the automated particle program in #3, the original stack files can be easily recreated.

  5. Convert individual stack files into one stack file that has to be in hdf format and should have the following attributes set:

    • Will add them later
  6. Run 2-D alignment programs, first sxali2d_c, next sxali2d_e.

  7. Run 2-D classification sxk_means and sxk_means_groups

  8. Run multi-reference 2-D alignment, sxali2d_m

  9. Determine the initial structure (Phil).
  10. Run 3-D projection alignment sxali3d_d.

Stain (last edited 2013-07-01 13:12:23 by localhost)