Resumo (PT):
Abstract (EN):
Separation techniques hyphenated with high-resolution mass spectrometry have been a true revolution
in analytical separation techniques. Such instruments not only provide unmatched resolution, but they
also allow measuring the peaks accurate masses that permit identifying monoisotopic formulae. However, data files can be large, with a major contribution from background noise and background ions.
Such unnecessary contribution to the overall signal can hide important features as well as decrease the
accuracy of the centroid determination, especially with minor features. Thus, noise and baseline correction can be a valuable pre-processing step. The methodology that is described here, unlike any other
approach, is used to correct the original dataset with the MS scans recorded as profiles spectrum. Using
urine metabolic studies as examples, we demonstrate that this thorough correction reduces the data
complexity by more than 90%. Such correction not only permits an improved visualisation of secondary
peaks in the chromatographic domain, but it also facilitates the complete assignment of each MS scan
which is invaluable to detect possible comigration/coeluting species.
Language:
English
Type (Professor's evaluation):
Scientific
No. of pages:
8