Sorry for being late on this thread - 

but the completeness myth is one of these conventional wisdoms I am seriously 
questioning and completeness
as a global statistic is almost uninformative, short of telling you 'fewer than 
all recordable reflections up to the reported 
(likely isotropic) resolution limit given whatever (likely isotropic) cutoff 
was applied'. Sounds not very clear to me. 

Kay mentioned already that any information is better than no information, with 
the caveat that you cannot expect
map quality (being an upper limit for model quality - not going into precision 
vs accuracy issue here) corresponding to 
the highest resolution reported, which is in reality frequently anisotropic 
(but not reported or reflected adequately 
in the PDB reports). 
We posted some remarks to this effect recently, pointing out that highly 
incomplete and anisotropic data can still 
yield limited but useful information as long as your claim remains 
correspondingly modest. Section 3.4 in
http://journals.iucr.org/d/issues/2019/12/00/di5032/index.html

Having said that, while random incompleteness is not problematic, systematic 
reciprocal space incompleteness leads
to corresponding systematic real space effects on the map, the simplest being 
anisotropic data reflecting anisotropic
reciprocal map resolution. This is different for example when wedges are 
missing or absence of serial extinctions makes
space group determination more challenging (although we are almost in the age 
where 'record 360 deg of data and 
try every SG' works). James Holton has video examples for incompleteness 
effects and some images are also in my book.
https://bl831.als.lbl.gov/~jamesh/movies/

Cheers & Happy Thanksgiving, BR

PS: A systemic rant regarding data quality representation can be found here
https://www.cell.com/structure/fulltext/S0969-2126(18)30138-2

------------------------------------------------------
Bernhard Rupp
http://www.hofkristallamt.org/
b...@hofkristallamt.org
------------------------------------------------------
All models are wrong
but some are useful.
------------------------------------------------------

-----Original Message-----
From: CCP4 bulletin board <CCP4BB@JISCMAIL.AC.UK> On Behalf Of Kay Diederichs
Sent: Monday, November 25, 2019 08:07
To: CCP4BB@JISCMAIL.AC.UK
Subject: Re: [ccp4bb] Xray-dataset usable despite low completeness ?

Dear Matthias,

Of course, high completeness is better than low completeness.
But as long as your low resolution is pretty much complete, there is no such 
thing as "too low completeness" at high resolution. Each reflection adds 
information to the map, and serves as a restraint in refinement.

best,
Kay 


On Mon, 25 Nov 2019 14:11:52 +0100, Matthias Oebbeke 
<oebbe...@staff.uni-marburg.de> wrote:

>Dear ccp4 Bulletin Board,
>
>I collected a dataset at a synchrotron beamline and got the statistics
>(CORRECT.LP) after processing (using xds) shown in the attached 
>pdf-file.
>
>Do you think this dataset is usable, due to its low completeness? As 
>you can see in the attached file the completeness is just 50% in the 
>highest resolution shell, whereas the I over Sigma is above 2 and also 
>the CC 1/2 (80%) and the R factors (36.8%) have reasonable values.
>Furthermore the overall statistic are good regarding R factor, CC 1/2 
>and I over Sigma. The only problem seems to be the completeness. If I 
>would set the cut-off at a lower resolution to get good completeness, I 
>would throw away nearly half of my reflections.
>
>I'm happy to here your opinion. In Addition to that: The space group is 
>orthorhombic and the dataset was collected over 120° using fine slicing 
>(0.1°).
>
>
>Best regards,
>
>Matthias Oebbeke
>
>
>-- 
>Matthias Oebbeke, M.Sc.
>Research Group of Professor Dr. G. Klebe
>Institute of Pharmaceutical Chemistry
>Philipps-University Marburg
>Marbacher Weg 6, 35032 Marburg, Germany
>Phone: +49-6421-28-21392
>Mail: oebbe...@staff.uni-marburg.de
>www.agklebe.de
>
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