A good way to think about it is that if CC1/2=100%, that means you can split the data in half, and use one half to perfectly predict the corresponding values of the other half. So yes, perfect internal consistency.
On Dec 7, 2012, at 11:41 AM, Phil Evans <[log in to unmask]> wrote:
> It is internally consistent, though not necessarily correct
>
>
> On 7 Dec 2012, at 16:23, Alan Cheung wrote:
>
>> Related to this, I've always wondered what CC1/2 values mean for low resolution. Not being mathematically inclined, I'm sure this is a naive question, but i'll ask anyway - what does CC1/2=100 (or 99.9) mean? Does it mean the data is as good as it gets?
>>
>> Alan
>>
>>
>>
>> On 07/12/2012 17:15, Douglas Theobald wrote:
>>> Hi Boaz,
>>>
>>> I read the K&K paper as primarily a justification for including extremely weak data in refinement (and of course introducing a new single statistic that can judge data *and* model quality comparably). Using CC1/2 to gauge resolution seems like a good option, but I never got from the paper exactly how to do that. The resolution bin where CC1/2=0.5 seems natural, but in my (limited) experience that gives almost the same answer as I/sigI=2 (see also K&K fig 3).
>>>
>>>
>>>
>>> On Dec 7, 2012, at 6:21 AM, Boaz Shaanan <[log in to unmask]> wrote:
>>>
>>>> Hi,
>>>>
>>>> I'm sure Kay will have something to say about this but I think the idea of the K & K paper was to introduce new (more objective) standards for deciding on the resolution, so I don't see why another table is needed.
>>>>
>>>> Cheers,
>>>>
>>>>
>>>>
>>>>
>>>> Boaz
>>>>
>>>>
>>>> Boaz Shaanan, Ph.D.
>>>> Dept. of Life Sciences
>>>> Ben-Gurion University of the Negev
>>>> Beer-Sheva 84105
>>>> Israel
>>>>
>>>> E-mail: [log in to unmask]
>>>> Phone: 972-8-647-2220 Skype: boaz.shaanan
>>>> Fax: 972-8-647-2992 or 972-8-646-1710
>>>>
>>>>
>>>>
>>>>
>>>>
>>>> ________________________________________
>>>> From: CCP4 bulletin board [[log in to unmask]] on behalf of Douglas Theobald [[log in to unmask]]
>>>> Sent: Friday, December 07, 2012 1:05 AM
>>>> To: [log in to unmask]
>>>> Subject: [ccp4bb] refining against weak data and Table I stats
>>>>
>>>> Hello all,
>>>>
>>>> I've followed with interest the discussions here about how we should be refining against weak data, e.g. data with I/sigI << 2 (perhaps using all bins that have a "significant" CC1/2 per Karplus and Diederichs 2012). This all makes statistical sense to me, but now I am wondering how I should report data and model stats in Table I.
>>>>
>>>> Here's what I've come up with: report two Table I's. For comparability to legacy structure stats, report a "classic" Table I, where I call the resolution whatever bin I/sigI=2. Use that as my "high res" bin, with high res bin stats reported in parentheses after global stats. Then have another Table (maybe Table I* in supplementary material?) where I report stats for the whole dataset, including the weak data I used in refinement. In both tables report CC1/2 and Rmeas.
>>>>
>>>> This way, I don't redefine the (mostly) conventional usage of "resolution", my Table I can be compared to precedent, I report stats for all the data and for the model against all data, and I take advantage of the information in the weak data during refinement.
>>>>
>>>> Thoughts?
>>>>
>>>> Douglas
>>>>
>>>>
>>>> ^`^`^`^`^`^`^`^`^`^`^`^`^`^`^`^`^`^`^`^`
>>>> Douglas L. Theobald
>>>> Assistant Professor
>>>> Department of Biochemistry
>>>> Brandeis University
>>>> Waltham, MA 02454-9110
>>>>
>>>> [log in to unmask]
>>>> http://theobald.brandeis.edu/
>>>>
>>>> ^\
>>>> /` /^. / /\
>>>> / / /`/ / . /`
>>>> / / ' '
>>>> '
>>>>
>>>
>>>
>>
>> --
>> Alan Cheung
>> Gene Center
>> Ludwig-Maximilians-University
>> Feodor-Lynen-Str. 25
>> 81377 Munich
>> Germany
>> Phone: +49-89-2180-76845
>> Fax: +49-89-2180-76999
>> E-mail: [log in to unmask]
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