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My guess is that the integration is roughly the same, unless the profiles are really poorly defined, but that the scaling that is suffering from using a lot of high-resolution weak data. We've integrated data to say I/sig = 0.5, and sometimes seem more problems with scaling. I then cut back to I/sig = 1 and it's fine. The major difficulty arises that if the crystal is dying, and the decay/scaling/absorption model isn't good enough. So that's definately a consideration when trying to get a more complete data set and higher resolution (so more redundancy). Bernie On Thu, March 22, 2007 12:21 pm, Jose Antonio Cuesta-Seijo wrote: > I have observed something similar myself using Saint in a Bruker > Smart6K detector and using denzo in lab and syncrotron detectors. > First the I over sigma never really drops to zero, no mater how much > over your real resolution limit you integrate. > Second, if I integrate to the visual resolution limit of, say, 1.5A, > I get nice dataset statistics. If I now re-integrate (and re-scale) > to 1.2A, thus including mostly empty (background) pixels everywhere, > then cut the dataset after scaling to the same 1.5A limit, the > statistics are much worse, booth in I over sigma and Rint. (Sorry, no > numbers here, I tried this sometime ago). > I guess the integration is suffering at profile fitting level while > the scaling suffers from general noise (those weak reflections > between 1.5A and 1.2A will be half of your total data!). > I would be careful to go much over the visual resolution limit. > Jose. > > ************************************** > Jose Antonio Cuesta-Seijo > Cancer Genomics and Proteomics > Ontario Cancer Institute, UHN > MaRs TMDT Room 4-902M > 101 College Street > M5G 1L7 Toronto, On, Canada > Phone: (416)581-7544 > Fax: (416)581-7562 > email: [log in to unmask] > ************************************** > > > On Mar 22, 2007, at 10:59 AM, Sue Roberts wrote: > >> I have a question about how the experimental sigmas are affected >> when one includes resolution shells containing mostly unobserved >> reflections. Does this vary with the data reduction software being >> used? >> >> One thing I've noticed when scaling data (this with d*trek (Crystal >> Clear) since it's the program I use most) is that I/sigma(I) of >> reflections can change significantly when one changes the high >> resolution cutoff. >> >> If I set the detector so that the edge is about where I stop seeing >> reflections and integrate to the corner of the detector, I'll get a >> dataset where I/sigma(I) is really compressed - there is a lot of >> high resolution data with I/sigma(I) about 1, but for the lowest >> resolution shell, the overall I/sigma(I) will be maybe 8-9. If the >> data set is cutoff at a lower resolution (where I/sigma(I) in the >> shell is about 2) and scaled, I/sigma(I) in the lowest resolution >> shell will be maybe 20 or even higher (OK, there is a different >> resolution cutoff for this shell, but if I look at individual >> reflections, the trend holds). Since the maximum likelihood >> refinements use sigmas for weighting this must affect the >> refinement. My experience is that interpretation of the maps is >> easier when the cut-off datasets are used. (Refinement is via >> refmac5 or shelx). Also, I'm mostly talking about datasets from >> well-diffracting crystals (better than 2 A). >> >> Sue >> >> >> On Mar 22, 2007, at 2:29 AM, Eleanor Dodson wrote: >> >>> I feel that is rather severe for ML refinement - sometimes for >>> instance it helps to use all the data from the images, integrating >>> right into the corners, thus getting a very incomplete set for the >>> highest resolution shell. But for exptl phasing it does not help >>> to have many many weak reflections.. >>> >>> Is there any way of testing this though? Only way I can think of >>> to refine against a poorer set with varying protocols, then >>> improve crystals/data and see which protocol for the poorer data >>> gave the best agreement for the model comparison? >>> >>> And even that is not decisive - presumably the data would have >>> come from different crystals with maybe small diffs between the >>> models.. >>> Eleanor >>> >>> >>> >>> Shane Atwell wrote: >>>> >>>> Could someone point me to some standards for data quality, >>>> especially for publishing structures? I'm wondering in particular >>>> about highest shell completeness, multiplicity, sigma and Rmerge. >>>> >>>> A co-worker pointed me to a '97 article by Kleywegt and Jones: >>>> >>>> _http://xray.bmc.uu.se/gerard/gmrp/gmrp.html_ >>>> >>>> "To decide at which shell to cut off the resolution, we nowadays >>>> tend to use the following criteria for the highest shell: >>>> completeness > 80 %, multiplicity > 2, more than 60 % of the >>>> reflections with I > 3 sigma(I), and Rmerge < 40 %. In our >>>> opinion, it is better to have a good 1.8 Å structure, than a poor >>>> 1.637 Å structure." >>>> >>>> Are these recommendations still valid with maximum likelihood >>>> methods? We tend to use more data, especially in terms of the >>>> Rmerge and sigma cuttoff. >>>> >>>> Thanks in advance, >>>> >>>> *Shane Atwell* >>>> >> >> Sue Roberts >> Biochemistry & Biopphysics >> University of Arizona >> >> [log in to unmask] >