Measuring peak intensities - is there a "peak" follower?

[Troels Emtekær Linnet]

Dear nmrglue users.

When you do NMR relaxation experiments, you would end up having a

long range of fourier transformed spectres and a peak list (or more), f.ex in SPARKY format.

Due to heating, there can be a minor drift in peak position over the spectra.

Does anyone have a peak "follow" method, so you don't have to open each spectrum

in SPARKY, and align a sparky list, to save it again?

Essentially, I am looking for a smart solution, to the problem described here:

http://www.nmr-relax.com/manual/Measuring_peak_intensities.html

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For the first spectrum in the time series, shift the peak list to the tops of the peaks (for example using ``pc'' in Sparky on subsets of peaks).

Copy this 1 spectrum list onto all spectra, shifting the peaks to the top as in the previous step.

When the peak disappears into the noise, leave it at its current position and do not type ``pc'' or equivalent. 

This will add weight to the first point in the subsequent step.

Once all spectra are shifted, calculate an average peak list.

Copy this average peak list onto fresh copies of all spectra.

Measure peak heights using this averaged peak list.

This will produce the most accurate peak intensity measurements until better, more robust peak shape integration comes along. 

This is a special technique which is designed to minimise the white-noise bias talked about in the Viles et al. (2001) paper. 

http://dx.doi.org/10.1023/A:1011966718826

As the noise often decreases with the decrease in total spectral power, using the tops of the peaks means that you are 

actually measuring the real peak height plus positive noise in all cases. 

This non-constant additional positive noise contribution can result in a double exponential in the measured data. 

The technique above eliminates this as you then measure close to real peak height with the addition of 

white noise centred at zero - it is both negative and positive to equal amounts - rather than the peak high 

with noise contribution strongly biased towards the positive. 

Where the peaks disappear, you then are measuring the pure baseplane noise. 

This is fine as these white-noise data points centred at zero will help in the subsequent exponential fit in relax.

If using Sparky then, to be sure that the peak heights are properly updated, for each spectrum type ``pa'' to select all peaks, 

``ph'' to update all selected peak heights, ``lt'' to show the spectrum peaks window, make sure ``data height'' 

is selected in the options, and then save the peak list.

Thanks

Troels Emtekær Linnet

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