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 <[email protected]> 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: [email protected]
Phone: 972-8-647-2220 Skype: boaz.shaanan
Fax: 972-8-647-2992 or 972-8-646-1710
________________________________________
From: CCP4 bulletin board [[email protected]] on behalf of Douglas Theobald
[[email protected]]
Sent: Friday, December 07, 2012 1:05 AM
To: [email protected]
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
[email protected]
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: [email protected]
