This is an old revision of the document!
Average and Filter : Average and low-pass filter a map for segmentation.
Usage in command line
sp_signalsubtract.py avgfilt --avol1=map_to_average_1 --avol2=map_to_average_2 --outdir=output_subtraction_directory --apix=pixel_size --filtrad=filter_radius --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 :
sp_signalsubtract.py avgfilt --avol1=map_to_average_1 --avol2=map_to_average_2 --outdir=output_subtraction_directory --apix=pixel_size --filtrad=filter_radius
Generate a denoised map for segmentation. The input map(s) can be postprocessed (i.e., sharpened, masked, etc.), but it is important that the final map that is masked below (in Step 4) is not postprocessed.
Choose a low-pass filter radius so that a permissive (i.e., low) surface threshold can be used in Chimera. If too high a threshold is used during segmentation, then the resulting mask may not encapsulate the entire region of interest. If a low threshold is used on a not-post-processed high-resolution map, then disconnected “moon” densities will be included in the segmentation.
Note 1: If you already have an averaged map, or don't have two maps to average, skip the '–avol2' flag.
Note 2: Low-pass filter radius should be in units of Angstroms if pixel size (–apix) is provided. If pixel size is not provided, then the program expects the filter radius in units of absolute frequency (px^-1)
2. Locate regions to be subtracted
Category 1:: APPLICATIONS
Beta:: Under evaluation and testing. Please let us know if there are any bugs.