Kemeny–Snell Distance in Nuclear Magnetic Resonance Metabolomics
| Autor: | Ago Samoson, Tarmo Veskioja, Tiina Titma, Min-Ji Shin |
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| Rok vydání: | 2020 |
| Předmět: |
010402 general chemistry
Linear discriminant analysis 01 natural sciences Atomic and Molecular Physics and Optics 030218 nuclear medicine & medical imaging 0104 chemical sciences 03 medical and health sciences 0302 clinical medicine Nuclear magnetic resonance Metabolomics Partial least squares regression Metric (mathematics) Ischemic heart Mathematics |
| Zdroj: | Applied Magnetic Resonance. 51:1637-1645 |
| ISSN: | 1613-7507 0937-9347 |
| DOI: | 10.1007/s00723-020-01282-2 |
| Popis: | We shall introduce Kemeny–Snell distance (KSD) metric on metabolomics and validate results with partial least squares discriminant analysis (PLS-DA). KSD metric allows principally to identify the most relevant chemical shift ranges directly from spectra without metabolite library-limited signature search and quantitation. The one-dimensional proton nuclear magnetic resonance spectra of the serum of ischemic heart disease (IHD) patients (n = 19) and controls (n = 19) showed the statistical significance by the first latent variable (LV1; 35.18%) of PLS-DA. The significance between ischemic heart disease (IHD) patients and controls was tested and confirmed by KSD metric. We used PLS-DA and KSD metric for the interpretation of serum NMR spectra of IHD patients and healthy controls and both methods show a significant deviation from the controls. KSD is a robust to spectral artifacts and potentially useful as a diagnostic tool to assess the likelihood of many pathologies simultaneously. |
| Databáze: | OpenAIRE |
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