[phenixbb] phenix and weak data

[Randy Read]

On 12 Dec 2012, at 15:04, Douglas Theobald wrote:

> On Dec 12, 2012, at 4:00 AM, Randy Read <rjr27 at CAM.AC.UK> wrote:
> 
>> Dear Ed,
>> 
>> I've been reading this thread for a while, wondering if I should say anything.  As Pavel knows, I've been suggesting that phenix.refine should include the experimental errors in the variance term ever since I realised they were being left out.  On the other hand, Pavel has been asking (quite reasonably) for some evidence that it makes any difference.  I feel that there ought to be circumstances where it does make a difference, but my attempts over the last few days to find a convincing test case have failed.  Like you, I tried running Refmac with and without experimental sigmas, in my case on a structure where I know that we pushed the resolution limits (1bos), and I can't see any significant difference in the model or the resulting phases.  Gabor Bunkoczi has suggested that it might be more relevant for highly anisotropic structures, so we'll probably look for a good example along those lines.
>> 
>> In principle it should make a difference, but I think there's one point missing from your discussion below.  If you leave out the experimental sigmas, then the refinement of sigmaA (or, equivalently, the alpha and beta parameters in phenix.refine) will lead to variances that already incorporate the average effect of experimental measurement error in each resolution shell.  So if all reflections were measured to the same precision, it shouldn't matter at all to the likelihood target whether you add them explicitly or absorb them implicitly into the variances.  The potential problems come when different reflections are measured with different levels of precision, e.g. because the data collection strategy gave widely varying redundancies for different reflections.
>> 
>> In the statistics you give below, the key statistic is probably the standard deviation of sigf/sqrt(beta), which is actually quite small.  So after absorbing the average effect of measurement error into the beta values, the residual variation is even less important to the total variance than you would think from the total value of sigf.
> 
> So, IIUC, what you're suggesting is that the great majority of the variance of F/sigF can simply be explained by resolution, and that phenix betas (as currently implemented) already account for that.  

I guess, to be more precise, I'm suggesting that this is probably true for my 1bos test case and the one Ed looked at, and maybe for lots of other examples.  But I don't think it should cost much effort to avoid having to make this assumption, and there might be cases where it's not true, e.g. Gabor's example of highly anisotropic data.

Randy

------
Randy J. Read
Department of Haematology, University of Cambridge
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