On Thu, Oct 16, 2008 at 4:30 PM, Tyler Reddy <TREDDY@xxxxxx> wrote:
Hi,
So what I've been doing for NOE data is using the DSN command in vnmrj
(which
gives S/N ratio) and then converting this to the rms value by RMSD = highest
peak/(S/N)
Does this give a S/N ratio for each peak? You could divide this value
by the peak hight and the resultant RMSD values should be the same for
all peaks. I don't know how vnmrj estimates the noise though, so I
can't tell you if this value is reasonable or not. I hope it misses
the solvent signal when calculating this.
If I understand what is planned for the relax program, I would want rms
values
for each of the T1 and T2 spectra at all field strengths, but I'm not sure
if
it would be worthwhile to collect error information for the different delays
within a given spectrum (i.e. rms at 0.01 s and 0.05 s for a single
spectrum).
In principle I would think it should be comparable, and I don't want to make
this unnecessarily complicated.
Actually the noise changes, usually most pronounced in the R2. I'm
not sure why but I think this has something to do with the total power
of the spectrum and Parseval's theorem
(http://en.wikipedia.org/wiki/Parseval's_theorem). My guess would be
that the total power decreases as the relaxation period increases as
this is related to the intensity of the signals. Whether or not this
it the reason, what you usually see is that noise decreases
exponentially - although much less quickly than the signals - with an
increased relaxation period. So having estimates for all spectra is
useful and relax will use that in the Monte Carlo simulation error
analysis. This is not necessary though, but does give you more
accurate error values.
In any case, do you have an estimate for how long it will take to implement
the
base plane rms functionality for the curve-fitting portion of relax? If
there
is something I can do to help feel free to let me know. Ultimately I'd like
to
compare results from a few different programs, so if it will be a few weeks
I
might try an alternate method first and then come back and compare the
results
at various stages with relax. That said, I don't know if base plane rms will
work from the get-go with any other packages, and a lot of the alternatives
may
not be user friendly.
I'm not sure, but this could be very quick or very slow depending on
how complex it ends up. If lucky I can do it in a couple of hours.
If unlucky it could take a couple of weeks. The infrastructure to
support this is already in relax, so I would guess that it will be to
the faster side of things. If it isn't fast enough for you though,
you can use the other programs to get the R1 and R2 and errors and
then use relax to do the model-free analysis. And if you really,
really want, you could always implement this yourself. But then you'd
need lots of time and have to be prepared to learn python and how open
source projects work.
Regards,
Edward
Re: Relax_fit.py problem