1D NMR metabolomics query and quantification based on global spectral deconvolution

Your name and institute*:

1D fid file (required, usually called fid or ser in Bruker instrument):
acqus file (required, usually called acqus in Bruker instrument):

Note (optional):

Bruker fid data format information

• You can find raw fid data in the experimental folder, such as your_exp_name/2, where 2 is EXP ID. The file is usually named fid (or ser)
• The acquisition status file is usually called acqus (not acqu) in the same folder as the FID data file.
• You can also drag and drop fid and/or acqus file, or their parent folder to the box above.
• The server will run automatic phase correction, after ZF and FF.

Your name and institute*:
1D spectrum file in ft1 format (required):
Note (optional):

Spectrum processing requirements, please read carefully.

• Please apply zero filling in your processing using nmrPipe command "-zf 2"
• Please use the 2PI-Kaiser window function for apodization in the NMRPipe software with the command “SP -off 0.5 -end 0.896 -pow 3.684” to achieve desired peak shape (Voigt).
• Beside nmrPipe .ft1 format, you can also use Topspin text file generated using command "totxt".
• You need to keep the imaginary part if you want to run manual phase correction.

Phase correction (coarse):

Phase correction ( fine ):

P0 (degree) 0
Anchor (ppm) 0.0
Fix P0 and work on P1

You can adjust 1st order phase correction here.

Phase correction (coarse):

Phase correction ( fine ):

P1 (degree) 0
Apply P1

Please adjust P0 first, then P1. Anchor point will be set to center of the visible region of the spectrum. Click on "Apply P1" to actually apply the phase correction.

Baseline smoothness parameter
Positive spectrum parameter

A appreciate baseline correction can only be defined by the user, based on the experimental conditions. That is, the user need to define the smoothness parameter and positive spectrum parameter then apply the baseline correction after satisfying result.

The smoothness parameter is the weight of the smoothness constraint in the baseline estimation. The larger the value, the smoother the baseline. Typical values are from 1e8 to 1e13

The positive spectrum parameter is the weight of the constraint that the baseline should be below the spectrum. The larger the value, the less the baseline will be allowed above the spectrum (to accommodate noise). Typical values are from 1.0 to 2.0

Important: phase correction is no longer allowed after baseline correction.

Reference: Baseline Correction for NMR Spectroscopic Metabolomics Data Analysis (Yuanxin Xi and David M Rocke); BMC Bioinformatics 2008, 9:324

Choose DEEP Picker model for peak picking

Deep Picker user defined interpolation step
Deep Picker auto
Deep Picker model 1 Deep Picker model 2

Choose line shape for peak fitting

Gaussian Lorentzian Voigt

Minimal peak height cutoff as times of noise-level
Maximal round in peak fitting:

DEEP Picker model selection

• Model 1 was optimized for peak width (defined as Full Width as Half Height) from 8 to 20, with 12 points as optimal value
• Model 2 was optimized for peak width from 4 to 12, with 8 points as optimal value
• The default model, DEEP Auto, will estimate median peak width, then run cubic spline interpolation to adjust it to 6.0 and apply model 2.
• For spectrum with very heterogeneous peak width, set a compromise interpolation step (for model 2). A step of 0.5 means spectral size will be doubled.

Calibration ppm

Chemical shift match cutoff (ppm)
Chemical shift match cutoff within J-splitted peaks (ppm)
Size of water suppression region (+- this value around 4.7 ppm)

Choose field strength

80 MHz 400 MHz 500 MHz 600 MHz 850 MHz 1.2 GHz

Choose subset

Human serum Mouse serum
DMEM Wine Synovial-fluid

Load pre-defined set


Run database query

Allow overall peak width rescale for all peaks from one compound
Apply peak width rescale factor before optimization
Maximal round in global optimization:

Instructions

• Ideally the theoretical spectrum should have the same the peak widths (and shapes) as the experimental spectrum because theoretical spectra of matched compounds are generated at specified the experimental condition. But there are generally small differences because R2 is uniformly set to 3.0 Hz for all peaks of all compounds in the spin simulation step. In addition, when the experiment is not optimal, experimental peaks will become wider to create a discrepancy.
• The COLMAR1d server can adjust peak width and shape individually in this final optimization step. But it still needs to know an “overall” rescaling factor to account for experimental misbehavior, to be filled into "Apply peak width rescale factor before optimization" field. When the experiment is perfect, this number will be near 1.0.
• If there are some compounds with very wide peaks (because of exchange, etc). Allow overall peak width rescale in this step might help those compounds