Signal Response Evaluation Applied to Untargeted Mass Spectrometry Data to Improve Data Interpretability.

ABSTRACT: Feature finding is a common way to process untargeted mass spectrometry (MS) data to obtain a list of chemicals present in a sample. Most feature finding algorithms naïvely search for patterns of unique descriptors (e.g., m/z, retention time, and mobility) and provide a list of unannotated features. There is a need for solutions in processing untargeted MS data, independent of chemical or origin, to assess features based on measurement quality with the aim of improving interpretation. Here, we report the signal response evaluation as a method by which to assess the individual features observed in untargeted MS data. The basis of this method is the ubiquitous relationship between the amount and response in all MS measurements. Three different metrics with user-defined p

SUBMITTER: Overdahl KE 

PROVIDER: S-EPMC10485927 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature