mailRe: Support for SQ and MQ dispersion data in relax.


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Posted by Paul Schanda on September 11, 2013 - 08:26:
Hi Edward,

Yes, the data I got from Remco are the ones on ClpP.
The fact that the dw values were obtained by other means (low T) is probably not a fundamental problem, and I think we can nevertheless check the algorithm with these data. It may actually be a useful feature if relax allowed to set some values (such as dw) to fixed values that are not fitted. We talked about this at some point, and you were not so much favoring such a solution, because you were afraid that this would allow users to make unreasonable assumptions, as I understood you.

But I agree, if we had the synthetic data from Korzhnev, it might be a good additional test, and would allow to see whether the algorithm finds the dw. I know you don't favor such a solution, but in my opinion we could also make such synthetic data, make sure they are the same as the Korzhnev data (as good as we can tell by comparing to Korzhnev graphs), and fit them.

best -

Paul

On 10.09.13 09:19, Edward d'Auvergne wrote:
Hi,

Is this the paper at http://dx.doi.org/10.1073%2Fpnas.0507370102 ?  If
so, do you know if the data for methyl group protons needs to be
treated differently?  Or does the TROSY data need a special treatment?
  Are a different set of Bloch-McConnell equations used?  For the data
analysis, the key sentences are:

"Chemical shift differences were initially estimated from spectra
recorded at 0.5°C and then optimized based on the extracted exchange
parameters from fits of the dispersion data. This optimization is
accomplished in an iterative manner whereby the fitted exchange
parameters are used, along with estimated shift differences, to obtain
the true shift differences from the eigenvalues of the free precession
evolution matrix."

It sounds like Remco used a numeric model.  I do not know why he did
not perform a standard optimisation - that is not explained in the
paper.  With relax we would perform a direct optimisation - first the
standard grid search to find a rough initial position followed by the
Nelder-Mead simplex optimisation (which requires no expensive
gradients or Hessians to be derived or numerically approximated,
http://en.wikipedia.org/wiki/Nelder%E2%80%93Mead_method).  The low
temperature shifts are only used as a starting estimate of dw.  I
think that with relax using a grid search for determining the initial
parameter values prior to optimisation that this initial estimate is
not necessary.  Maybe they found it necessary due to the prohibitive
amount of time required for a comprehensive grid search.  This is
where the trick used in the auto-analysis in relax would be very
powerful - these initial parameter estimates could come from the
analytic MQ CR72 model (the multiple quantum Carver and Richards 1972
model) rather than from a grid search.

Maybe the synthetic Korzhnev data would be a better match for your
aims (http://dx.doi.org/10.1021/ja049968b), as the dw value
measurements/assumptions are not there.  If we know that we can
optimise both the dwH and dwN (or dwC) correctly, that might be of
higher value.  The lower temperature assumptions for an initial
parameter estimate are not needed.  But we could try to perform a
direct optimisation of the Sprangers data and see what happens.

Regards,

Edward


P. S.  I will be on holidays for 3 weeks starting from this weekend,
possibly with no internet access for most of the time, so I will not
be able to respond to emails very quickly during that time.


On 6 September 2013 17:00, Paul Schanda <paul.schanda@xxxxxx> wrote:
Hi Edward,

I got some data from Remco Sprangers, a PNAS paper with Lewis Kay.
The fit seems to take the delta-omega values from direct observation of the
peaks at lower temperature (slow exchange).

Paul


On 06.09.13 16:57, Edward d'Auvergne wrote:
Hi Paul,

For the literature data, which paper did you choose?  Are you asking
Dmitry Korzhnev about his 2004 JACS paper
(http://dx.doi.org/10.1021/ja049968b)?  Having both the base data,
ideally in peak list form, together with the fitted parameters or
original parameters for simulated data would be great.  I would like
to create a relax system test which analyses the SQ + MQ CPMG data
simultaneously, and then I would write the code to make the test pass.

Cheers,

Edward



On 4 September 2013 20:30, Paul Schanda <paul.schanda@xxxxxx> wrote:
Hi Edward,

I managed to find some literature data that are probably suitable. I will
get them from the authors in a week or so.
So that probably solves point 3).

I agree that the infrastructure needs to be revised for MQ data. This
might
in fact be the opportunity to re-think the structure. One might want to
jointly fit all kinds of data, e.g. SQ+MQ, or CPMG+R1rho. You should also
think of the possibility of adding in the future EXSY data. In the slow
to
intermediate exchange, one might have EXSY + CPMG to be fit together.
If relax would be designed now in a way that is sufficiently flexible to
handle all this, it would be great.

We will have a look at the code that Mathilde and Dominique have
implemented; this might also take a few days.

best -


Paul


On 04.09.13 16:47, Edward d'Auvergne wrote:
The following are reference development notes for how to modify relax
to handle multi-quantum (MQ) data.  Currently relax supports
single-quantum (SQ) data but not MQ data.  There are three aspects to
this problem, detailed below.  Note that the changes for part 2) will
likely break the code of the relax_disp branch for a short time.


1)  The MQ models.

Firstly the specific MQ model(s) must be added to relax (following the
steps at

http://wiki.nmr-relax.com/Tutorial_for_adding_relaxation_dispersion_models_to_relax).
    This part is relatively trivial, especially if the code already
exists, a published reference exists, and equations can be copied from
a paper directly into the relax manual.  For example the 'MQ CR72'
model supported by GUARDD (http://dx.doi.org/10.1021/ja049968b).


2) Infrastructure changes.

There is one infrastructure change required to support this.  The
reason is because most people with MQ data will want to analyse it
simultaneously with SQ data (well, that is my guess from the
literature data).  Support for optimising both SQ and MQ data
simultaneously needs to be added.  Currently relax only handles one
type of dispersion data per data pipe.  This should not be too hard to
change.  Such a change could allow CPMG-type and R1rho-type data to be
analysed simultaneously as well.  In each individual data combination
case, a specific combined model such as 'SQ+MQ CR72' would need to be
created.  This model would be independent of the 'CR72' and 'MQ CR72'
models, and the user will have to explicitly select it.

The only change from the perspective of the user would the
relax_disp.exp_type user function.  This user function currently sets
the experiment type for all data in the current data pipe.  This needs
to be changed to be similar to the relax_disp.cpmg_frq,
relax_disp.relax_time, relax_disp.spin_lock_field, etc user functions,
where the experiment type is associated with a spectrum ID.  The GUI
would be changed so that this user function is not presented when
setting up a new analysis, but rather when the peak lists are being
loaded.  The GUI element displaying the experiment type would need to
be removed and the data presented in the peak list GUI element
instead.

The backend changes would be more extensive.  The following generator
functions would need to be added to
specific_analyses.relax_disp.disp_data:

loop_exp() - for new usages.
loop_exp_frq() - to replace calls to loop_frq().
loop_exp_frq_point() - to replace calls to loop_frq_point().
loop_exp_frq_point_time() - to replace calls to loop_frq_point_time().

The the code in specific_analyses.relax_disp and
target_functions.relax_disp need to be modified around this new
concept.  I.e. a new top level looping needs to be inserted.  The
looping hierarchy from highest level to lowest would become:
experiment type, magnetic field strength, dispersion point (CPMG
frequency or spin-lock field strength), and finally relaxation time.
The only difference to now is the highest level experiment type
looping.

The cdp.exp_type data structure will need to be converted into a
dictionary where the keys are the spectrum IDs.


3) Test data.

More of an issue is data!  Test data is essential to be sure that the
code is functional.  And in relax it needs to be incorporated into a
system test.  The most important point is that the data needs to be
independent of relax - the same code for fitting cannot be used to
generate synthetic data.  The more independence between relax and this
test data, the better.

Literature data for MQ data appears not to be available.  It looks
like corresponding authors would need to be emailed for access to the
base data and numerical results.  An alternative is provided by the
Matlab software GUARDD.  It has a module for simulating dispersion
data

(http://code.google.com/p/guardd/#Optimization_and_education_with_RD_Simulator).
    This could be used to generate the test data to be included with
relax.  Some test data is also provided by the program.  This could
also be used, but it suffers from the fact that the real parameter
values are not known.  But it can be used to directly compare relax
and GUARDD.

Regards,

Edawrd

--
Paul Schanda, Ph.D.
Biomolecular NMR group
Institut de Biologie Structurale Jean-Pierre Ebel (IBS)
41, rue Jules Horowitz
F-38027 Grenoble
France
+33 438 78 95 55
paul.schanda@xxxxxx
http://www.ibs.fr/groups/biomolecular-nmr-spectroscopy?lang=en


--
Paul Schanda, Ph.D.
Biomolecular NMR group
Institut de Biologie Structurale Jean-Pierre Ebel (IBS)
41, rue Jules Horowitz
F-38027 Grenoble
France
+33 438 78 95 55
paul.schanda@xxxxxx
http://www.ibs.fr/groups/biomolecular-nmr-spectroscopy?lang=en



--
Paul Schanda, Ph.D.
Biomolecular NMR group
Institut de Biologie Structurale Jean-Pierre Ebel (IBS)
41, rue Jules Horowitz
F-38027 Grenoble
France
+33 438 78 95 55
paul.schanda@xxxxxx
http://www.ibs.fr/groups/biomolecular-nmr-spectroscopy?lang=en




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