Center Map : Center map of remaining density.

Usage in command line

	sp_signalsubtract.py centershift --cvol1=map_center_1 --cvol2=map_center_2 --shiftparams=shift_parameters --diffimgs=images_to_subtract --outdir=output_subtraction_directory --volradius=map_radius --apix=pixel_size --verbosity=verbosity_level

sp_signalsubtract comprises the steps needed to subtract masked regions from a map in order to focus on the remaining features from that map. There are six steps for this process (five within SPHIRE):

1. Average and low-pass filter a map for segmentation

2. Locate regions to be subtracted

3. Mask a soft mask of the region to be excluded

4. Compute re-projections of map to be subtracted, and subtract them from the original images

5. Compute reconstruction of density remaining after signal-subtraction

6. Center map of the remaining density :

sp_signalsubtract.py --mode centershift --cvol1=centered_halfmap_1 --cvol2=centered_halfmap_2 --shiftparams=meridien_parameters --diffimgs bdb:output_subtraction_directory#all_subtracted --outdir=output_subtraction_directory --apix=pixel_size --volradius=structure_radius

As inputs “–cvol1” and “–cvol2”, use the half-maps generated by the previous reconstruction step. For “–shiftparams”, use the Meridien parameters for the iteration used for those reconstructions. e.g., of the form “final_params_015.txt”. For “–diffimgs”, use the signal-subtracted image stack from above.

The reconstruction will be roughly centered by alignment to a Gaussian blob of radius specified by the flag “–volradius”. (Additional centering options will be provided in the future.) If the pixel size is provided (–apix), the units of radius will be assumed to be in Angstroms. If the pixel size is not provided, the radius will be assumed to be in units of voxels. If your structure is not globular, try the shortest dimension.

The output centered parameter file will be combine the Meridien parameters with the centering parameters. The output reconstruction will not use smear information, and may be noisier than the reconstruction from the previous step. Simply make sure that the centering was adequate. The better the centering, the smaller the required shifts will be in subsequent refinements.

--cvol1

First map to average and center. (default None)

--cvol2

Second map to average and center. (default None)

--shiftparams

Meridien parameters to combine with centering parameters. (default None)

--diffimgs

Images from signal subtraction to reconstruct. (default None)

--outdir

Directory where outputs will be written. (default required string)

--volradius

Radius to use for centering reconstruction. If the structure is not globular, try the shortest dimension. (default None)

--apix

Pixel size in Angstroms. (default None)

--verbosity

Verbosity level

Controls how much information will be written to the screen. (default 2)

vol001_average.hdf

Reconstruction of subtracted particles

vol002_inverted.hdf

Negative of above reconstruction, subtracted region shouldn't have significant densities

vol003_centered.hdf

Centered reconstruction

params004_to_be_centered.txt

Original parameters

params005_centered.txt

Parameters after centering

Reconstruction (filtered) before centering

Reconstruction after centering

Tapu Shaikh

Category 1:: APPLICATIONS

sphire/bin/sp_signalsubtract.py

Beta:: Under evaluation and testing. Please let us know if there are any bugs.