Currently, the fragment deconvolution approaches (in DIA experiments) that are suitable for NTA, focus heavily on the information presented in the time domain. One of these approaches is the apex retention time matching of the parent features with the potential fragment signals. In addition to this, some algorithms also use peak shape assessment via correlation analysis to group fragments. More decomposition based algorithms (e.g. MCR and/or PARAFAC) are available to perform signal deconvolution. These methods are generally less suitable for NTA due to the requirement of multiple samples, which often means that an analyte needs to be present in more than one sample and at different concentrations for the method to work. However, since it is unknown what is present in the samples to begin with, ensuring the presence of this compound across multiple samples becomes impossible. Even more so if different concentrations of the analyte are required to resolve the mass spectrum. Other reasons could be due to the requirement of retention time alignment, binning, prior knowledge on the number of components, or summation of MS1 and MS2 level information to obtain the fragment signals from the higher energy scan. Typically fragment deconvolution methods for NTA rarely utilize the mass domain information and are often highly field or compound class specific. Furthermore, in some cases (e.g., with data-dependent analysis) there could be a lack of time domain information, due to insufficient MS measuring points across the analyte peak, rendering the deconvolution of noise from the fragments impossible for these methods. Previous studies have shown that the mass domain can provide important information through, for example, neutral losses (NLs), which are defined as the mass differences between two ions, including parent and fragment ions. Previously, NLs have been used for spectral annotation as well as molecular networking. These NLs are generated from the breakage of specific chemical bonds during ionization, hence their use in the reaction pathways for identification. However, if one fragment is missing from the fragment pattern, a different NL is obtained between the surrounding fragments. Hence, we propose the use of cumulative neutral losses (CNLs), which are defined by the difference between the precursor ion and each of the potential fragment ion masses.