Difference between revisions of "Hints for improving a refinement"

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where <tt>myTable</tt> is probably a subtable of your all-particle table... If you have a global table embracing many tomograms, with many geometric entities (filaments)  inside each one, you probably want to analize them separately, creating subtables attending to column 20 (tomogram) or column 21 (model)
 
where <tt>myTable</tt> is probably a subtable of your all-particle table... If you have a global table embracing many tomograms, with many geometric entities (filaments)  inside each one, you probably want to analize them separately, creating subtables attending to column 20 (tomogram) or column 21 (model)
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==Refining against tight masks==
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In the final stages of a refinement, it makes sense to define a tight mask that is close to the density of interest.

Revision as of 09:09, 19 May 2016


Ok, you did your average and you are not yet satisfied. Looks like you should be able to get better results?

Classification

Do you have a single class? If you are aligning two or more classes together, the alignment would get stuck at some point (funnily enough, in this circumstances the FSC can easily lie about the attained resolution, even when using a golden standard procedure!). A first approach to diagnose this is to check the cross correlation of the alignment (in column 10 of the table). A simple inspection of the histogram can be very revealing, especially if you detect different behaviours when considering particles stemming from different tomograms (column 20) or models (column 21).

The next of level approach would be running a PCA on the last refined table. You probably want to start this approach using as classification mask the alignment mask that was used by the alignment project.

Remember that a quick way to check the results of a classification project is by looking at the histograms of the eigencomponents.

 ddb myProject:eigentable -ws eigentable
 o = dpkpca.eigentable.showHistograms(eigentable);

or by plotting the correlation between the eigencomponents and the tilt (in column 8)

 o = dpkpca.eigentable.showScatterEigencomponents(eigentable,8);

Geometrical validation

If you have a priori geometrical information, use it. This will be very different for different geometries. Some hints: You can check if the refinement moved your particles away from the membranes or filaments where they were supposed to lay. You can check if the normals are pointing in roughly the correct direction on membranes, or that you don't have sudden changes of polarities in a filament. If you are oversampling the surfaces of viruses, you should check that your final tables after cleaning overlapping particles look decent (regularly distributed).

For visualization purposes you probably want to use dtplot with the profile corrected_oriented_positions, i.e.:

dtplot(myTable,'pf','corrected_oriented_positions');

or

dtplot file.tbl -pf corrected_oriented_positions;


where myTable is probably a subtable of your all-particle table... If you have a global table embracing many tomograms, with many geometric entities (filaments) inside each one, you probably want to analize them separately, creating subtables attending to column 20 (tomogram) or column 21 (model)

Refining against tight masks

In the final stages of a refinement, it makes sense to define a tight mask that is close to the density of interest.