| Resumo: | Separation techniques hyphenated with high-resolution mass spectrometry have been a true revolutionin analytical separation techniques. Such instruments not only provide unmatched resolution, but theyalso 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 theaccuracy 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 otherapproach, is used to correct the original dataset with the MS scans recorded as profiles spectrum. Usingurine metabolic studies as examples, we demonstrate that this thorough correction reduces the datacomplexity by more than 90%. Such correction not only permits an improved visualisation of secondarypeaks in the chromatographic domain, but it also facilitates the complete assignment of each MS scanwhich is invaluable to detect possible comigration/coeluting species.
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