STOCSY editing, STOCSY editing scales highly correlated peaks to remove unwanted signals from NMR spectral data
STOCSY editing scales highly correlated peaks to remove unwanted signals (for example, from drug compounds) from NMR spectral data
STOCSY editing scales peaks by their correlation coefficient to the driver_peak.
This allows highly correlated peaks (above a certain threshold) to be removed from the spectrum.
However, where peak overlap results in decreased correlation, after scaling, the remaining peaks can be helpful in deconvolving for example, endogenous from removed exogenous signal
model = csm_stocsye( spectra, driver_peak );
model = csm_stocsye( spectra, driver_peak, 'stocsy_cutoff', stocsy_cutoff, 'correlations', correlations, 'noise_region', noise_region, 'local_baseline_region', local_baseline_region, 'mode', mode );
| Variable | Type | Default Value | Description |
|---|---|---|---|
| *spectra | csm_spectra | None | csm_spectra object containing spectral matrix. |
| *driver_peak | m*1 | None | Chemical shift value of target intensity variable, vector for multiple peaks. |
| stocsy_cutoff | 1*1 | None | Correlation threshold above which( |r| > stocsy_cutoff |
| correlations | str | 'pos' | 'all' to include both positive and negative, 'pos' to only include positive |
| noise_region | 1*2 | [9.5, 10] | Noise region for ppm |
| local_baseline_region | 1*1 | 0.02 | PPM region around peak to find local baseline |
| mode | str | 'by_sample' | 'by_sample' calculates region to scale and replace for each sample, 'by_mean' calculates mean spectrum and uses for all samples |
| Variable | Type | Description |
|---|---|---|
| model | obj | csm_wrapper with some stored inputs, the outputs and auditInfo. |
| model.output.edited_X | m*n | Scaled and background-corrected STOCSYE data. |
| model.output.cor | m*n | Squared correlation vectors for each peak. n = number of driver_peaks |
Caroline J. Sands, Muireann Coen, Anthony D. Maher, Timothy M. D. Ebbels, Elaine Holmes, John C. Lindon and Jeremy Nicholson
Statistical Total Correlation Spectroscopy Editing of 1H NMR Spectra of Biofluids: Application to Drug Metabolite Profile Identification and Enhanced Information Recovery
Analytical Chemistry, 2009, 81 (15), pp 6458?6466
Copyright Imperial College London 2019