Selected article for: "isotope peak and ppm window"

Author: Marcus Ludwig; Louis-Félix Nothias; Kai Dührkop; Irina Koester; Markus Fleischauer; Martin A. Hoffmann; Daniel Petras; Fernando Vargas; Mustafa Morsy; Lihini Aluwihare; Pieter C. Dorrestein; Sebastian Böcker
Title: ZODIAC: database-independent molecular formula annotation using Gibbs sampling reveals unknown small molecules
  • Document date: 2019_11_16
  • ID: 03uonbrv_40
    Snippet: The SIRIUSAdapter OpenMS module combines MS/MS which are associated with the same MS1 feature. In addition, complete linkage hierarchical clustering was conducted to merge features over dierent LC-MS/MS runs. Features were merged using 15 ppm mass accuracy and a 15 sec retention time window. Features with dierent adduct annotations or features from the same run were not merged. Feature similarity was computed by the cosine product of the MS/MS (s.....
    Document: The SIRIUSAdapter OpenMS module combines MS/MS which are associated with the same MS1 feature. In addition, complete linkage hierarchical clustering was conducted to merge features over dierent LC-MS/MS runs. Features were merged using 15 ppm mass accuracy and a 15 sec retention time window. Features with dierent adduct annotations or features from the same run were not merged. Feature similarity was computed by the cosine product of the MS/MS (see below), and the similarity threshold for clustering was set to 0.8. When multiple features were merged into a single one, where each feature has an assigned isotope pattern, then the isotope pattern with the highest number of isotope peaks was kept. In case multiple isotope patterns had the same number of isotope peaks, the one with the most intense monoisotopic peak was kept. After merging, features were discarded if the summed MS/MS intensity was below a threshold, see Table 2 . Features with precursor mass above 850 Da are discarded: Whereas ZODIAC is clearly capable of processing such features, we found that there are no spectral library hits above this mass that can be used for evaluation, see below. Only 2.72 % of features across all datasets have m/z above 850 Da, so excluding these cannot have substantial impact on result statistics.

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