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The analysis of an NMR spectrum invariably involves some or all of the following steps: (i) identification of the complete set of cross-peaks, known as peak picking (ii) assignment of each cross-peak to the atoms it belongs to and (iii) quantification of each cross-peak by the determination of the peak amplitude or volume. Despite many years of progress, the above steps can only be partially automated. This applies in particular to spectra of large molecular systems or complex mixtures containing many cross-peaks that tend to overlap, which makes their spectral deconvolution challenging without expert human assistance. However, due to the large number of cross-peaks, such work can be tedious, time-consuming, and subjective with results differing between experts and labs, thereby limiting the transferability of the analysis within the research community. This makes the availability of an approach necessary that accomplishes the above tasks both with high accuracy and high reproducibility.ĭifferent methods have been proposed for peak picking and spectral deconvolution. The simplest approach is to select local maxima as peak positions. However, because of spectral noise, not all local maxima belong to true peaks. Moreover, in crowded regions, some peaks may not correspond to maxima because of the close vicinity of larger peak(s) with which such shoulder peaks overlap. To address these formidable challenges, numerous approaches have been developed in the past. Early methods focused on criteria based on signal intensity, volume, signal-to-noise ratios, and peak symmetry 3, 4, 5, 6, 7, 8, 9, 10, 11.

Other peak picking methods exploit various forms of matrix factorization 12, 13, 14, or singular value decomposition 15. Another approach models spectra as multivariate Gaussian densities followed by filtering with respect to peak intensities and widths 16, 17, 18. In these methods, certain spectral features are extracted after pre-processing and assessed following a set of rules to determine whether a data point is considered as a peak or not.