The mass difference method is a commonly used approach for automated isotopologue detection in LC-HRMS data. This method has already been implemented in different open access algorithms such as CAMERA and MZmine. Here, an "in-house" developed mass difference strategy was employed to benchmark our classification model against. For the mass difference method, to asses if a signal is an isotopologue of a monoisotopic peak, first the mass difference between the signal and monoisotopic ion was calculated. Then, the residue of the division of the mass difference by 1.0033 Da is obtained. For example, if the mass difference is 2.0081 Da, the residue would be 0.0015 Da. In case the residue is lower than the specified mass tolerance, the signal is accepted as an isotopologue of the monoisotopic mass. For the mass difference method, when dealing with the training set a mass tolerance of ± 0.0001 Da was used based on the assumption that the theoretical isotopologues do not contain any mass error. On the other hand for the wastewater samples, this mass tolerance was increased to ± 0.01 Da to better reflect the inherent mass error in such data caused by background signal and instrumental fluctuations.