Dear Jorge, the plots available from XDSGUI in the "statistics" tab are helpful in this respect (see https://journals.iucr.org/j/issues/2023/05/00/yr5110/index.html and in particular Fig 4). In particular, delta-CC1/2 and R_d are sensitive to radiation damage. Pls note that sometimes a few iterations are needed. With that I mean that you inspect the delta-CC1/2 plot with _all_ data first, and then remove the final frames if their delta-CC1/2 is negative. Then you re-scale (i.e. run JOB=CORRECT) and re-do the calculations in the "statistics" tab, and check again. Another way to identify "damaged" data is to compare (squared) Fcalc from a good model with the intensities, as a function of rotation angle. This calculation can be done with XDSCC12, but is not (yet) easy to do in XDSGUI. It is documented at https://wiki.uni-konstanz.de/xds/index.php/Xdscc12#Correlation_against_a_reference_data_set_(-r_%3Creference%3E_option) .
Feel free to contact me offline, to discuss, and share / assess (raw) data. Best wishes, Kay On Mon, 30 Oct 2023 09:23:32 -0400, Jorge Iulek <jiu...@gmail.com> wrote: >Dear all, > > I have found many fundamental studies on image processing and >refinement indexes concerning the decision on cutting resolution for a >dataset, always meant to get better models, the final objective. Paired >refinement has been a procedure mostly indicated. > I have been searching studies alike concerning, in these days of >thousands of collected images and strong x ray beams, the cutting (or >truncation) of the (sequentially due to rotation method) recorded images >in a dataset due to radiation damage. Once again, I understand the idea >is to always produce better models. > On one hand, the more images one uses, the higher the multiplicity, >what (higher multiplicity) leads to better averaged intensity (provided >scaling makes a good job), on the other hand, the more images one uses, >lower intensity (due to the radiation damage) equivalent reflections >come into play for scaling, etc. How to balance this? I have seen a case >in which truncating images with some radiation damage led to worse >CC(1/2) and <I/sigI> (at the same high resolution shell, multiplicities >around 12.3 and then 5.7), but this might not be the general finding. In >a word, are there indicators of the point where to truncate more >precisely the images such that the dataset will lead to a better model? >I understand tracing a sharp borderline might not be trivial, but even a >blurred borderline might help, specially in the moment of image processing. > I find that in >https://ccp4i2.gitlab.io/rstdocs/tasks/aimless_pipe/scaling_and_merging.html#estimation-of-resolution >there is a suggestion to try refinement with both truncating and not >truncating. > Sure other factors come into play here, like diffraction anisotropy, >crystal internal symmetry, etc., but to start one might consider just >the radiation damage due to exposure to x rays. Yes, further on, it >would be nice the talk evolves to those cases when we see peaks and >valleys along the rotation due to crystal anisotropy, whose average >height goes on diminishing. > Comments and indications to papers and material to study are welcome. >Thanks. > Yours, > >Jorge > >######################################################################## > >To unsubscribe from the CCP4BB list, click the following link: >https://www.jiscmail.ac.uk/cgi-bin/WA-JISC.exe?SUBED1=CCP4BB&A=1 > >This message was issued to members of www.jiscmail.ac.uk/CCP4BB, a mailing >list hosted by www.jiscmail.ac.uk, terms & conditions are available at >https://www.jiscmail.ac.uk/policyandsecurity/ ######################################################################## To unsubscribe from the CCP4BB list, click the following link: https://www.jiscmail.ac.uk/cgi-bin/WA-JISC.exe?SUBED1=CCP4BB&A=1 This message was issued to members of www.jiscmail.ac.uk/CCP4BB, a mailing list hosted by www.jiscmail.ac.uk, terms & conditions are available at https://www.jiscmail.ac.uk/policyandsecurity/
