Incorporating measurement variability when comparing sets of high-resolution mass spectra.

Mass spectra are an important signature by which compounds can be identified. We recently formulated a mathematical approach for incorporating measurement variability when comparing sets of high-resolution mass spectra. Leveraging replicate mass spectra, we construct high-dimensional consensus mass spectra-representing each of the compared analytes-and compute the similarity between these data structures. In this paper, we present this approach and discuss its applications and limitations when trying to discriminate methamphetamine and phentermine using in-source collision induced dissociation mass spectra collected with direct analysis in real time mass spectrometry.