structure factor labels in phenix.refine
I have two questions about which structure factor amplitudes are refined against in phenix.refine. 1. Which structure factor amplitude is used in refinement when the labels in the .def file are the following? labels = "F-obs(+),SIGF-obs(+),F-obs(-),SIGF-obs(-)" 2. Is anomalous data used in the refinement when the labels are as follows? labels = "F,SIGF,DANO,SIGDANO,ISYM" I ask these questions because I am wondering which structure factor amplitudes to deposit, and I am trying to rationalize differences between R-factors from refinement and Generate Table 1. Thanks. Jack Tanner John J. Tanner Professor of Biochemistry and Chemistry University of Missouri-Columbia 125 Chemistry Building Columbia, MO 65211 Phone: 573-884-1280 Fax: 573-882-2754 Email: [email protected]mailto:[email protected] http://faculty.missouri.edu/~tannerjj/tannergroup/tanner.html
1. Which structure factor amplitude is used in refinement when the labels in the .def file are the following?
labels = "F-obs(+),SIGF-obs(+),F-obs(-),SIGF-obs(-)"
If input file actually has these labels (it should!) then this is what was used in refinement. Note, MTZ file out of any phenix.refine run contains four blocks of information: 1) Copy of original data (Fobs or Iobs, flags, etc); 2) Data actually used in refinement (F-obs-filtered). This may be slightly different from input data by a handful of outliers not used in refinement or if input was Iobs (phenix.refine always uses F, so it will convert Iobs to Fobs using F&W method). 3) Total model structure factors, Fmodel, that includes all scales: Fmodel = k_total * (Fcalc + Fbulk) 4) Various Fourier map coefficients, such as 2mFo-DFc, mFo-DFc, anomalous difference map coefficients. So you can always take MTZ file generated by phenix.refine and know exactly what was used.
2. Is anomalous data used in the refinement when the labels are as follows?
labels = "F,SIGF,DANO,SIGDANO,ISYM"
Yes.
I ask these questions because I am wondering which structure factor amplitudes to deposit,
You need to deposit the original ones, that is from "1)" above. Ideally, "2)" should also go there along with "1)" (but not instead!) because this is what was actually used to obtain reported statistics, such as R-factors.
and I am trying to rationalize differences between R-factors from refinement and Generate Table 1.
Depending which kind of differences you mean (magnitude). Ideally, R-factors should be identical. If it's like 0.1856 vs 0.1858, then it's fine, if larger then some of us here need to investigate what's going on. Pavel
On Thu, Nov 7, 2013 at 12:57 PM, Pavel Afonine
Depending which kind of differences you mean (magnitude). Ideally, R-factors should be identical. If it's like 0.1856 vs 0.1858, then it's fine, if larger then some of us here need to investigate what's going on.
Agreed, since the Table 1 program is using phenix.model_vs_data internally, which was designed to reproduce the R-factors from phenix.refine, any major discrepancy is cause for concern. We have seen a handful of cases where they deviate significantly, but it's been very difficult to isolate the cause, so data is always helpful. (Of course this doesn't rule out the possibility that there's simply a bug in my code somewhere, but I don't think the program is doing anything fancy.) -Nat
Hi Nat,
I have found that phenix.model_vs_data does not deal well with a perfect
twin data set. The refined data is:
r_work=0.2013 r_free=0.2298 (in PDB file)
r_work=0.2815 r_free=0.3006 (from phenix.model_vs_data)
There is one merohedral twin operator: -h-k,k,-l (48%) and 6 very small
(<1.0%) pseudo-merohedral twin operators.
Ryan Spencer
From: [email protected]
[mailto:[email protected]] On Behalf Of Nathaniel Echols
Sent: Thursday, November 07, 2013 2:52 PM
To: PHENIX user mailing list
Subject: Re: [phenixbb] structure factor labels in phenix.refine
On Thu, Nov 7, 2013 at 12:57 PM, Pavel Afonine
On Thu, Nov 7, 2013 at 3:50 PM, Ryan Spencer
I have found that phenix.model_vs_data does not deal well with a perfect twin data set. The refined data is:
r_work=0.2013 r_free=0.2298 (in PDB file)
r_work=0.2815 r_free=0.3006 (from phenix.model_vs_data)
There is one merohedral twin operator: -h-k,k,-l (48%) and 6 very small (<1.0%) pseudo-merohedral twin operators.
Yes, the automatic twinning detection is one of the weak points of the current Table 1 program (and the enhanced MolProbity validation in Phenix); a more flexible approach will be available soon. However, if you have a case where you're certain the structure is twinned (and these R-factors do support that hypothesis) but Phenix is missing it, we'd be interested in seeing the model and data. It may just be a limitation of the twinning, but occasionally our code trips on corner cases, or it could be something stranger misdiagnosed as twinning. -Nat
participants (4)
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Nathaniel Echols
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Pavel Afonine
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Ryan Spencer
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Tanner, John J.