Hi all,
Can someone put in links of a few articles relevant to the above
discussion? ie where this kind of strategy was helpful in a specific
practical situation?

Thanks in advance,

Regards,

ARKO

On Tue, Feb 21, 2012 at 4:46 AM, ccp4 <[email protected]> wrote:

> This is a case where it is really helpful to keep some record of the
> unmerged integrated data.
> And again rejecting the odd outlier does no harm to most analyses..
>
> I like to use scala to check for outliers looking at all i+ I-
> measurements; if there is a wild discrepancy for weak anomalous signals you
> have probably found an outlier which is best rejected.
>
> If you have a huge anomalous signal with good redundancy you probably
> shouldnt use Imean and the anomalous difference will be I= -I- with SD =
> sqrt (VarI+ VarI-).
>
> Most software which uses that signal will check for outliers in the Anom
> difference lists too, and it is usually safest to exclude them from anom
> site searches, and phase calculations.
> Eleanor
>
>  On 14.02.2012 06:30, Tim Gruene wrote:
>
>> -----BEGIN PGP SIGNED MESSAGE-----
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>> Dear Markus,
>>
>> why don't you reintegrate the data with hkl2000 telling the program to
>> treat them as non-anomalous data-set? This should give you scalepack
>> output with the Bijvoet pairs merged and overcome the problem you
>> describe.
>>
>> Cheers,
>> Tim
>>
>> On 02/13/2012 06:19 PM, Markus Meier wrote:
>>
>>> On 11/02/12 02:52 PM, Bryan Lepore wrote:
>>>
>>>> did you ever get a response on this? it is interesting but nobody
>>>> posted publicly.
>>>>
>>>> -Bryan
>>>>
>>>>
>>> Dear Bryan,
>>>
>>> so far no one replied ... so please find my answer below. If someone
>>> disagrees, please post.
>>>
>>> None of the methods I have described are appropriate.
>>>
>>> If the negative Bijvoet mates and the positive Bijvoet mates have been
>>> merged separately to one intensity value for each (i.e. I+ or I-) plus
>>> the associated standard deviation (sigI+ or sigI-), any weighted method
>>> to calculate the mean will bias the intensity to either the I+ or the I-.
>>>
>>> Therefore the only appropriate method is to use the unweighted mean:
>>>
>>> Imean = 0.5*( I+ + I- )
>>> sigImean = 0.5 * sqrt( sigI+^2 + sigI-^2 )
>>>
>>> The only CCP4 program I found that actually does this is mtzMADmod. This
>>> method also has the advantage that the original intensity values of I+
>>> and I- can be reconstructed from the mean and the anomalous difference
>>> (albeit with the loss of the original standard deviations).
>>>
>>> Method 1 (scalepack2mtz)
>>> should not be used. The resulting value is not the best estimate
>>> (maximum likelihood)
>>>
>>> Method 2 (in book by B. Rupp)
>>> gives the maximum likelihood average in case that the reflections are
>>> equivalent and is thus appropriate for the merging of the negative (or
>>> positive) set of Bijvoet mates, centric reflections (where the anomalous
>>> differences are zero) or in the case of an non-anomalous dataset the
>>> merging of symmetry equivalent reflections.
>>>
>>> Method 3
>>> gives a more realistic sigma value in the case that the individual
>>> intensity values are far apart and their individual standard deviations
>>> are small. Consider the example I have posted:
>>>
>>> I+: 23841.50 sigI+: 634.01 I-: 9628.57, sigI-: 264.75
>>> Method 2: Imean=11738.95, sigIMean=244.31
>>> Method 3: Imean=11738.95, sigIMean=7106.47
>>>
>>> If the I+ and I- values above actually were symmetry equivalent
>>> reflections in an non-anomalous dataset, the sigImean from method 2 is
>>> ridiculously small and method 3 gives a far more realistic value. If
>>> method 3 is the best mathematical solution to this problem I am not able
>>> to judge and I have to trust the statistician (or programmer) who
>>> implemented this solution.
>>>
>>> Cheers,
>>> Markus
>>>
>>> On 10/02/12 01:47 PM, Markus Meier wrote:
>>>
>>>> Dear all,
>>>> I have a anomalous dataset, processed in HKL2000. Scalepack outputs a
>>>> file containing the separately merged sets of the Friedel pairs I- and
>>>> I+ and their standard deviations sigI+ and sigI-. Scalepack does not
>>>> output the averaged intensities (Imean) and the standard deviations
>>>> (sigIMean).
>>>>
>>>> The CCP4 program truncate that I use to convert the intensities to
>>>> amplitudes requires Imean, I- and I+ and the respective standard
>>>> deviations in its input file.
>>>>
>>>> I have now found at least three different methods to generate the
>>>> averaged intensities from the Friedel pairs:
>>>>
>>>> 1) scalepack2mtz
>>>>
>>>>   uses standard deviations for the weights:
>>>>   weights w = 1/sigI
>>>>
>>>>   Imean = (w+*I+ + w-*I- ) / (w+ + w-)
>>>>   sigImean = 1 / (w+ + w-)
>>>>
>>>> 2) Method described in Biomolecular crystallography by Bernhard Rupp, p.
>>>> 332/333
>>>>   to average symmetry equivalent reflections
>>>>
>>>>   uses variances for the weights:
>>>>   weight w = 1/sigI^2
>>>>
>>>>   Imean = (w+*I+ + w-*I- ) / (w+ + w-)
>>>>   sigImean = 1 / sqrt(w+ + w-)
>>>>
>>>> 3) Method used in cctbx
>>>>   function miller.set.average_bijvoet_**mates() that calls generic
>>>> merge.merge_equivalent_obs():
>>>>
>>>>   same as methods 2, except that
>>>>
>>>>   sigImean is the larger of either
>>>>     a) sigImean = 1 / sqrt(w+ + w-)
>>>>     or
>>>>     b) sigImean = sqrt( wvariance )
>>>>
>>>>   where wvariance =
>>>>     (w+ + w-) / [ (w+ + w-)^2 - (w+^2 + w-^2) ] *
>>>>     [ w+*(F+ - Imean)^2 + w-*(F- - Imean)^2 ]
>>>>
>>>> What are the advantages and disadvantages of each method? Should method
>>>> 1 be used at all?
>>>>
>>>> Some example from my dataset:
>>>> Reflection (1, 1, 0), space group P3 2 1
>>>>
>>>> I+: 23841.50 sigI+: 634.01 I-: 9628.57, sigI-: 264.75
>>>> Method 1: Imean=13815.32, sigImean=186.76
>>>> Method 2: Imean=11738.95, sigIMean=244.31
>>>> Method 3: Imean=11738.95, sigIMean=7106.47
>>>>
>>>> Thanks a lot!
>>>>
>>>> Cheers,
>>>> Markus
>>>>
>>>
>>>
>> - --
>> - --
>> Dr Tim Gruene
>> Institut fuer anorganische Chemie
>> Tammannstr. 4
>> D-37077 Goettingen
>>
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>


-- 

*ARKA CHAKRABORTY*
*CAS in Crystallography and Biophysics*
*University of Madras*
*Chennai,India*

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