Detection of highly overlapping peaks via adaptive apodization.

Accurate peak detection is an essential component of many NMR tasks such as peak alignment, compound identification, and global spectral deconvolution. However, current peak detection approaches are generally limited by their ability to deal with spectral overlap, which has a deleterious effect on downstream data processing. In this work, we present the use of an adaptive apodization strategy that improves the detection of highly overlapping peaks. Sensitivity enhancement is used to identify general regions of interest and resolution enhancement is used to separate overlapping peaks, with parameters for both calculated directly from the data. Further limits on peak width help to reduce false positives. The method proposed in this work has been implemented in an open-source R package called rnmrfind that is available for download on GitHub (https://github.com/ssokolen/rnmrfind). A set of default parameters have been chosen to provide effective peak detection while keeping false positives to a minimum; however, application-specific tuning is possible through the modification of minimum peak width at half height (in Hz) and noise cutoff threshold (as a factor of estimated standard deviation). Comparison to existing packages rNMR and speaq on a series of 1H NMR spectra demonstrates improved peak resolution with little to no apparent drawbacks.