Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1181341 | Chemometrics and Intelligent Laboratory Systems | 2014 | 6 Pages |
•Simultaneously corrects coupled phase and dilution errors in 1D 1H NMR datasets.•Improves cluster quality in PCA and PLS scores space.•Outperforms other popular normalization methods in the presence of phase errors.•Requires no tunable parameters and may be completely automated.
Nuclear magnetic resonance (NMR) spectroscopy has proven invaluable in the diverse field of chemometrics due to its ability to deliver information-rich spectral datasets of complex mixtures for analysis by techniques such as principal component analysis (PCA). However, NMR datasets present a unique challenge during preprocessing due to differences in phase offsets between individual spectra, thus complicating the correction of random dilution factors that may also occur. We show that simultaneously correcting phase and dilution errors in NMR datasets representative of metabolomics data yields improved cluster quality in PCA scores space, even with significant initial phase errors in the data.