Univariate Statistical Analysis as a Guide to 1H-NMR Spectra Signal Assignment by Visual Inspection
Department of Agri-Food Science and Technology, University of Bologna, 40126 Bologna, Italy
Department of Pharmacy and Biotechnology, University of Bologna, 40126 Bologna, Italy
Department of Obstetrics and Gynaecology, General Hospital Heilig Hart, 3000 Tienen, Belgium
Department of Obstetrics and Gynecology, Antwerp University, 2000 Antwerp, Belgium
Author to whom correspondence should be addressed.
Metabolites 2019, 9(1), 15; https://doi.org/10.3390/metabo9010015
Received: 20 December 2018 / Revised: 8 January 2019 / Accepted: 10 January 2019 / Published: 15 January 2019
(This article belongs to the Special Issue NMR-based Metabolomics and Its Applications Volume 2)
In Proton Nuclear Magnetic Resonance (1H-NMR) spectroscopy, the signals assignment procedure is normally conducted by visual inspection of the spectra, by taking advantage of the innate predisposition of human eye for pattern recognition. In the case of untargeted metabolomics investigations on food and body fluids, the complexity of the spectra may lead the user to overlook signals, independently from their biological relevance. Here, we describe a four steps procedure that is designed to guide signals assignment task by visual inspection. The procedure can be employed whenever an experimental plan allows for the application of a univariate statistical analysis on a point-by-point basis, which is commonly the case. By comparing, as a proof of concept, 1H-NMR spectra of vaginal fluids of healthy and bacterial vaginosis (BV) affected women, we show that the procedure is also readily usable by non-experts in three particularly challenging cases: overlapping multiplets, poorly aligned signals, and signals with very poor signal-to-noise ratio. The paper is accompanied by the necessary codes and examples written in R computational language to allow the interested user gaining a hands-on impression of the procedure’s strengths and weaknesses.