[Chimera-users] Fo-Fc electron density maps

Elaine Meng meng at cgl.ucsf.edu
Mon Jun 30 09:46:55 PDT 2014


Hi Oliver and Egor,
Even if using commands, it's not necessary to split the data into two maps; analogous to the GUI approach, you can simply show two contour levels on the same data set.

For example:

volume #1 level 2.0 color green level -2.0 color red

(where you would adjust the levels to something reasonable for your data, and #1 would be whatever model is your volume data set)
Best,
Elaine
----------
Elaine C. Meng, Ph.D. 
UCSF Computer Graphics Lab (Chimera team) and Babbitt Lab
Department of Pharmaceutical Chemistry
University of California, San Francisco

On Jun 28, 2014, at 3:14 PM, Oliver Clarke <olibclarke at gmail.com> wrote:

> Dear Egor,
> 
> In addition to Elaine’s suggestion of unchecking “Cap high values at box faces", I use the following aliases to make difference maps more familiar in style to a crystallographer:
> 
> First, to just normalize the map to RMS (as per coot etc) and adjust to get a mesh, turn capping, mesh lighting off etc:
> 
> alias normalize_to_rms vop scale $1 rms 1; close $1; volume # capfaces false; sop cap off; volume # style mesh; volume # meshlighting false; volume # square mesh false
> 
> Second, to split the map into two maps (one positive, one negative), which can then be colored green and red respectively:
> 
> alias split_diff_map vop threshold $1 minimum 0; vop threshold $1 maximum 0; close $1; sop cap off; volume # style mesh; volume # meshlighting false; volume # squaremesh false;
> 
> I add these two lines in a “chimera_aliases.com” file, which you can  tell Chimera to read at startup under Favorites—>Preferences—>Command Line.
> 
> You can then run these commands from the chimera command line, e.g. normalize_to_rms #1 or split_diff_map #1 if your map number is 1. Then just adjust the contours and colors in the volume viewer and you are good to go.
> 
> I don’t know how to automatically color the resultant maps, because there does not seem an obvious way to predict their model numbers, but I am sure there is a way to do that too, perhaps via some python trickery.
> 
> This is all kind of a work around of course - there may be a way to color a map by density value (such that all positive regions are green, and all negate regions are red), but I couldn’t figure out how to do it.
> 
> Best,
> Oliver.




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