A Proposed Statistical Protocol for the Analysis of Metabolic Toxicological Data Derived from NMR Spectroscopy

摘要: Nuclear magnetic resonance (NMR) spectroscopy is a non-invasive method of acquiring metabolic profile from biofluids. This information may provide keys to the early detection exposure toxin. A typical NMR toxicology data set has low sample size and high dimensionality. Thus, traditional pattern recognition techniques are not always feasible. In this paper, we evaluate several common alternatives for isolating these biomarkers. The fold test, unpaired t-test, paired t-test were performed on an NMR-derived toxicological results compared. was preferred, due its ability attribute statistical significance, take into consideration consistency single subject over time course, mitigate sample, dimensionality problem. We then grouped resulting statistically salient potential biomarkers based their significance patterns compared known metabolites affected by tested Based results, present protocol sequential t-tests clustering identifying putative applied specific real world set.