Aimless does indeed calculate the point at which CC1/2 falls below 0.5 but I would not necessarily suggest that as the "best" cutoff" point. Personally I would also look at I/sigI, anisotropy and completeness, but as I said at that point I don't think it makes a huge difference

Phil

On 28 Aug 2013, at 10:00, Arka Chakraborty <[log in to unmask]> wrote:

> Hi all,
>  If I am not wrong, the Karplus & Diederich paper suggests that data is generally meaningful upto CC1/2  value of 0.20 but they suggest a paired refinement technique ( pretty easy to perform) to actually decide on the resolution at which to cut the data. This will be the most prudent thing to do I guess and not follow any arbitrary value, as each data-set is different. But the fact remains that even where I/sigma(I) falls to 0.5 useful information remains which will improve the quality of the maps, and when discarded just leads us a bit further away from  truth. However, as always, Dr Diederich and Karplus will be the best persons to comment on that ( as they have already done in the paper :) )
> 
> best,
> 
> Arka Chakraborty
> 
> p.s. Aimless seems to suggest a resolution limit bases on CC1/2=0.5 criterion ( which I guess is done to be on the safe side- Dr. Phil Evans can explain if there are other or an entirely different reason to it! ). But if we want to squeeze the most from our data-set,  I guess we need to push a bit further sometimes :)
> 
> 
> On Wed, Aug 28, 2013 at 9:21 AM, Bernhard Rupp <[log in to unmask]> wrote:
> >Based on the simulations I've done the data should be "cut" at CC1/2 = 0. Seriously. Problem is figuring out where it hits zero. 
> 
>  
> 
> But the real objective is – where do data stop making an improvement to the model. The categorical statement that all data is good
> 
> is simply not true in practice. It is probably specific to each data set & refinement, and as long as we do not always run paired refinement ala KD
> 
> or similar in order to find out where that point is, the yearning for a simple number will not stop (although I believe automation will make the KD approach or similar eventually routine).
> 
>  
> 
> >As for the "resolution of the structure" I'd say call that where |Fo-Fc| (error in the map) becomes comparable to Sigma(Fo). This is I/Sigma = 2.5 if Rcryst is 20%.  That is: |Fo-Fc| / Fo = 0.2, which implies |Io-Ic|/Io = 0.4 or Io/|Io-Ic| = Io/sigma(Io) = 2.5.
> 
>  
> 
> Makes sense to me...
> 
>  
> 
> As long as it is understood that this ‘model resolution value’ derived via your argument from I/sigI is not the same as a <I/sigI> data cutoff (and that Rcryst and Rmerge have nothing in common)….
> 
>  
> 
> -James Holton
> 
> MAD Scientist
> 
>  
> 
> Best, BR
> 
>  
> 
>  
> 
> 
> On Aug 27, 2013, at 5:29 PM, Jim Pflugrath <[log in to unmask]> wrote:
> 
> I have to ask flamingly: So what about CC1/2 and CC*?  
> 
>  
> 
> Did we not replace an arbitrary resolution cut-off based on a value of Rmerge with an arbitrary resolution cut-off based on a value of Rmeas already?  And now we are going to replace that with an arbitrary resolution cut-off based on a value of CC* or is it CC1/2?
> 
>  
> 
> I am asked often:  What value of CC1/2 should I cut my resolution at?  What should I tell my students?  I've got a course coming up and I am sure they will ask me again.
> 
>  
> 
> Jim
> 
>  
> 
> From: CCP4 bulletin board [[log in to unmask]] on behalf of Arka Chakraborty [[log in to unmask]]
> Sent: Tuesday, August 27, 2013 7:45 AM
> To: [log in to unmask]
> Subject: Re: [ccp4bb] Resolution, R factors and data quality
> 
> Hi all,
> 
> does this not again bring up the still prevailing adherence to R factors and not  a shift to correlation coefficients ( CC1/2 and CC*) ? (as Dr. Phil Evans has indicated).?
> 
> The way we look at data quality ( by "we" I mean the end users ) needs to be altered, I guess.
> 
> best,
> 
>  
> 
> Arka Chakraborty
> 
>  
> 
> On Tue, Aug 27, 2013 at 9:50 AM, Phil Evans <[log in to unmask]> wrote:
> 
> The question you should ask yourself is "why would omitting data improve my model?"
> 
> Phil
> 
> 
> 
> 
> -- 
> Arka Chakraborty
> ibmb (Institut de Biologia Molecular de Barcelona)
> BARCELONA, SPAIN