In this post I will cover some basic concepts on the analysis of a very important class of NMR experiments, the so-called Arrayed NMR spectra. The concept is very simple: an arrayed experiment is basically a set of individual spectra acquired sequentially and related to each other through the variation of one or more parameters and finally grouped together to constitute a composite experiment. These experiments are also known as ‘pseudo-2D’. For example, in the case of Bruker spectra they have the same file name as 2D spectra, that is ser files (ser = serial spectra) . In the case of Varian, the file name is fid (Varian uses the same name for 1D, 2D, 3D, … and arrayed spectra). However, unlike with actual 2D spectra, arrayed spectra are only transformed along the F2 –horizontal or direct- dimension (assuming 1D arrayed spectra only).
The modus operandi is better explained with an example: let’s suppose it is necessary to acquire a pulse field gradient (PFG) experiment. Instead of acquiring independent spectra, it is more convenient to create an array with increasing PFG amplitudes. All resulting spectra are now treated as a single experiment. This grouping greatly facilitates processing as, in general, all subspectra require the same processing operations (apart from some occasional minor adjustments of one or several spectra). More about this in a moment.
Well known examples of NMR arrayed experiments are, among others:
Relaxation (T1, T2)
PFG experiments (DOSY)
Kinetics and reaction monitoring by NMR
Any good NMR processing software should be able to automatically recognize when an NMR spectrum is an arrayed experiment and will setup all processing operations accordingly. For example, the figure below illustrates the results obtained when a Bruker arrayed folder is dragged and dropped into Mnova:
What has happened here are basically 2 things:
First, Mnova detects that the dropped folder contains an arrayed experiment
With that knowledge in hand, Mnova proceeds to process all the individual spectra, one after the other and of course, along the only valid dimension (F2). So for every spectrum, Mnova applies appropriate weighting, zero filling, FT, phase correction, etc and stacks all the spectra as shown in the picture above
As a result, all individual spectra grouped within one composite item (i.e. arrayed item) have been processed in the same way. However, it’s very common that some subspectra might require independent tuning. For example, many PFG NMR experiments present gradient dependent phase shift so that it becomes necessary to adjust the phase of some individual spectra separately. This is very easy to accomplish with Mnova and it will be the subject of my next post.
[Question from NMRWiki Q&A forum] exporting part of data to excel, origin
exporting part of data to excel, origin
Hi,i'm new in TopSpin and i am blocked by a simple (i thinks) problem.I have a 1D specrtrum and i would like to export it to excel or origin but my spectrum have a small S/N so there is to much point --> i want this spectrum with less point but without smoothing (if it's possible).In other word, how can i do to tell TopSpin "get the spectrum but only every 10 points (or X points)" ?
Thank you in advance for those who will have the kindness to answer.
Check if somebody has answered this question on NMRWiki QA forum
[NMR analysis blog] Binning and NMR Data Analysis
Binning and NMR Data Analysis
Yesterday I mentioned that many NMR arrayed experiments suffer from unwanted chemical shift variations due to fluctuations in experimental conditions such as sample temperature, pH, ionic strength, etc. This phenomenon is very common in NMR spectra of e.g. biofluids (metabonomics/metabolomics) but also exists in many other experiments such us Relaxation, Kinetics and PFG NMR spectra (diffusion).
This problem negatively affects the reliability of quantitation using, for instance, peak heights, and for this reason integration is, in general, a more robust...
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08-21-2010 09:12 PM
[NMR analysis blog] Basics on Arrayed-NMR Data Analysis (Part IV)
Basics on Arrayed-NMR Data Analysis (Part IV)
Next up in my survey on analysis of arrayed NMR experiments ( View Parts 1, 2, 3 ) takes me to a quick overview of the different methods of data evaluation, such as the determination of peak heights and peak areas from arrayed experiments. Here you go...
Of the different existing methods for the extraction of peak intensities from arrayed NMR spectra (see ), Mnova provides the following ones:
(1) Peak area integration
This is the default method in Mnova Data Analysis module (see figure below)
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08-21-2010 09:12 PM
[NMR analysis blog] Basics on Arrayed-NMR Data Analysis (Part III): Extracting and calculating useful NMR
Basics on Arrayed-NMR Data Analysis (Part III): Extracting and calculating useful NMR related molecular information
After the basic introductory posts on arrayed NMR experiments, it’s now time to get some action and see how to extract relevant information from these experiments and calculate useful NMR related parameters such as diffusion, relaxation times, kinetics constants, etc.
Actually, in this post I will cover the first case, that is, the analysis of PFG experiments to calculate diffusion coefficients. The reason for this is twofold: (1) I have a nice PFG data set whilst the...
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08-21-2010 09:12 PM
[NMR analysis blog] Basics on Arrayed-NMR Data Analysis (Part II): Practical hints
Basics on Arrayed-NMR Data Analysis (Part II): Practical hints
Further to my previous post, I will cover today some more basic tools available in Mnova for the analysis of NMR arrayed experiments. In particular, I will touch on the following points:
How to use different display modes for 1D arrayed spectra
How to navigate throughout the different subspectra in the arrayed item
How to process individual spectra separately
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08-21-2010 09:12 PM
[NMR analysis blog] Mnova 6.0, at last! GSD, Line Fitting, Data Analysis, handling of LC/GC/MS data and m
Mnova 6.0, at last! GSD, Line Fitting, Data Analysis, handling of LC/GC/MS data and much more!
It's been over 6 weeks since my last post on this blog but don’t worry, I haven’t been idle. On the contrary, I have a very good excuse for this lack of posts: We all at Mestrelab have been working very hard trying to get version 6.0 of Mnova finished. Now I’m delighted to announce that we have done it and version 6.0 is finally available for download from our Web site. This is certainly a major upgrade of the software in which we have put a lot of work and passion. It brings a number of...
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Biomolecular NMR Data Analysis
Biomolecular NMR Data Analysis
Publication year: 2010
Source: Progress in Nuclear Magnetic Resonance Spectroscopy, In Press, Accepted Manuscript, Available online 2 March 2010</br>
Michael R., Gryk , Jay, Vyas , Mark W., Maciejewski</br>
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