Alternative moving window factor analysis (AMWFA) for resolution of embedded peaks in complex GC-MS dataset of metabonomics/metabolomics study

Abstract

Hyphenated instruments, such as GC-MS, have been being widely used in many studies of metabolomics/metabonomics. With the deepening of research, chromatograms become more and more complex and the problem of embedded peaks seems to be ineluctable. In this paper, alternative moving window factor analysis (AMWFA) method is introduced to resolve this problem occurring in metabolomics/metabonomics research. This new method can extract selective information by alternative scanning and comparing between two analytical systems. On the basis of the selective information obtained from chromatograms and spectra of two systems, the AMWFA approach can resolve the embedded peaks in GC-MS responses matrix into pure chromatograms and spectra without any model assumption on the peak shape. The resolution results obtained from one simulated data and two real metabolomics data demonstrate the performance of the proposed approach and indicate that it may be a promising one for analyzing complex data from metabolomics/metabonomics studies.