Identification of sample component using a mass sensor system

A method for identification of an anomalous sample component in a complex sample, wherein the complex sample is provided in a group of complex samples, comprising the steps of:

• providing the group of complex samples to a sampler;
• sampling a quantity of each of the complex samples so as to provide a respective quantity of vapor phase molecules of the respective complex sample to a mass sensor;
• deriving a mass spectrum representative of the masses in each of the quantities of complex samples analyzed by the mass sensor, so as to generate a plurality of mass spectra;
• providing the plurality of mass spectra to a computer in a data matrix;
• performing an exploratory data analysis of the data matrix using at least one set of principal components;
• performing a classification method analysis of the data matrix using a soft independent modeling of class analogy (SIMCA) technique, wherein the masses exhibiting a high discriminating power are selected;
• performing, with use of each of the selected masses that exhibit a high discrimination power, a mass correlation analysis with respect to each selected mass so as to determine a set of at least three correlated masses;
• comparing each of the three correlated masses to mass spectra in a mass spectra library so as to identify at least one candidate mass spectrum that is associated with the correlated masses and which is potentially indicative of a respective anomalous sample component;
• reviewing the candidate mass spectrum to select the anomalous sample component that is associated with the correlated masses;
• and
• identifying the selected anomalous sample component.