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> -----Original Message-----
> From: Vellieux Frederic [mailto:[log in to unmask]]
> Sent: 19 October 2009 19:31
> To: Ian Tickle
> Cc: [log in to unmask]
> Subject: Re: [ccp4bb] how to improve Rfree?
> 
> Hi Ian (& ccp4bb'ers),
> 
> NCS ties reflections in reciprocal space by the interference
G-function
> effect. Nothing more. So you get an R-free value that is lower than if
> you don't have NCS. One should be aware of that, and referees should
be
> aware of that.

Hi Fred

That may be true (though not always), but I was actually referring to
the problem of 'predicting' (usually after the fact!) what is the
expected value of Rfree for an optimally refined structure, given Rwork
(without knowing Rwork it's impossible!) and basic information about the
data, the structure and the refinement protocol.  This is (partly) a
question of working out the observation/parameter ratio; then the big
question arises as to how you count the NCS restraints.  This
calculation is tricky even in non-NCS cases, but as I said NCS really
fouls things up (and I don't have a satisfactory solution)!  Without
having the expected value of Rfree as a basis for comparison how can you
argue with the referees that the value of Rfree that you actually
observed demonstrates that your model is free of bias or overfitting?

My previous example of model bias in a 1 Ang isotropic B-factor
refinement may have seemed remote and even irrelevant to many people
struggling with 3 Ang data, but I would point out that model bias and
the concomitant higher-than-expected Rfree is ubiquitous.  If that were
not true we wouldn't need to refine or model-build any MR solutions -
just calculate structure factors and publish!  The fact that Rfree never
(well hardly ever) drops immediately to its final value but requires a
lot of work model-building/refining is testament to the model bias still
remaining in all the intermediate models between the initial MR model
and the final refined structuure.

Cheers

-- Ian


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