Statistically Significant Differences in Composition of Petroleum Crude Oils Revealed by Volcano Plots Generated from Ultrahigh Resolution Fourier Transform Ion Cyclotron Resonance Mass Spectra

摘要

A "volcano" plot provides a visual means for identifying statistically significant differences between two populations. Here, we introduce the volcano plot as a means for simple, visual identification and statistical ranking of compositional differences between petroleum crude oils. Ultrahigh-resolution Fourier transform ion cyclotron resonance mass spectrometry yields the relative abundances of ions in each spectrum that contains up to tens of thousands of elemental compositions (CcHhNnOoSs). From that data, a volcano plot may be generated by plotting statistical significance (p-value, obtained from t test) versus log(2)(relative abundance ratio). The volcano plot data may be color-coded to highlight differences in heteroatom class (NnOoSs), double bond equivalents (DBE = number of rings plus double bonds to carbon), and/or carbon number. The volcano plot may be used either directly or as a "filter" for including only the most statistically significant differences for data entered into more conventional analyses based on DBE vs carbon number, van Krevelen diagram, and Kendrick mass defect plots. In each case, the volcano plot provides statistically significant criteria, rather than visual grouping.