Abstract: In "OMICS" researches, comparison study of components present in different complex systems is very difficult because of the existence of many overlapped peaks. Herein, a new method, named alternative moving window factor analysis(AMWFA), was proposed, which is the combination and development of multicomponent spectral correlative chromatography(MSCC) and subwindow factor analysis(SFA). The method could be utilized to determine the number of common components of different samples and resolve overlapped peaks using the common selective information hiding in two data matrixes. The advantages of AMWFA are its extensive adaptability to the systems with no or only weak selective information, self-verified to the resolution results, no experienced user request. In this paper, the powerful ability of the proposed method has been proved by the group of simulated GC-MS data.

Key words: Alternative moving window factor analysis(AMWFA), Gas chromatography-mass spectrometry(GC-MS), Comparison analysis