Dear Alisia

I assume you have read the documentation at

https://www.ccp4.ac.uk/html/scaleit.html

in particular the comment "Note that there is no unique solution to the problem 
of scaling together two different data sets. “

The program was written (a long time ago) to scale a heavy-atom derivative 
dataset roughly to a native set, with the expectation that the scale (and 
relative B-factor (isotropic or anisotropic)) would be refined during the 
derivative refinement procedure, where the underlying difference between 
datasets can be modelled explicitly

The functions used are described in the documentation 

The underlying assumption of any data scaling is that the true intensities 
which are compared, from different crystals or from different parts of data 
collected from the same crystal, are truly the same, and the observations 
differ only by a scale which can be modelled simply, and by random errors. This 
clearly is not the case if the crystals are different, for whatever reason, eg 
by the addition of a heavy atom or a ligand or indeed by radiation damage. So 
different scaling targets are likely to give (slightly) different results, 
because of different weighting of observations. In Scaleit, the observed 
difference is modelled by a relative scale and a relative B-factor (ie a scale 
dependent on resolution). 

Note also that ideally the scaling should be done on intensities, rather than 
on F^2 where the F has been derived from I by the French & Wilson “truncate” 
procedure or its equivalent. However in practice I’m not sure it makes much 
difference, given the other assumptions

Does this help?
Phil

> On 12 May 2022, at 22:43, Fadini, Alisia <alisia.fadin...@imperial.ac.uk> 
> wrote:
> 
> Dear all,
> 
> I am having trouble following from the documentation what specific functions 
> are minimized in SCALEIT for the different REFINE options and how the 
> Fox&Holmes method is applied. Any insight would be very helpful!
> 
> All the best,
> Alisia
> 
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