Concomitant species that appear at
the same or very similar times
in a mass-spectral analysis can clutter a spectrum because of the
coexistence of many analyte-related ions (e.g., molecular ions, adducts, fragments). One method to extract
ions stemming from the same origin is to exploit the chemical information
encoded in the time domain, where the individual temporal appearances
inside the complex structures of chronograms or chromatograms differ
with respect to analytes. By grouping ions with very similar or identical
time-domain structures, single-component mass spectra can be reconstructed,
which are much easier to interpret and are library-searchable. While
many other approaches address similar objectives through the Pearson’s
correlation coefficient, we explore an alternative method based on
a modified cross-correlation algorithm to compute a metric that describes
the degree of similarity between features inside any two ion chronograms.
Furthermore, an automatic workflow was devised to be capable of categorizing
thousands of mass-spectral peaks into different groups within a few
seconds. This approach was tested with direct mass-spectrometric analyses
as well as with a simple, fast, and poorly resolved LC–MS analysis.
Single-component mass spectra were extracted in both cases and were
identified based on accurate mass and a mass-spectral library search.