title: Automated resolution of chromatographic signals by independent component analysis-orthogonal signal deconvolution in comprehensive gas chromatography/mass spectrometry-based metabolomics.
abstract: Comprehensive gas chromatography-mass spectrometry (GC×GC-MS) provides a different perspective in metabolomics profiling of samples. However, algorithms for GC×GC-MS data processing are needed in order to automatically process the data and extract the purest information about the compounds appearing in complex biological samples. This study shows the capability of independent component analysis-orthogonal signal deconvolution (ICA-OSD), an algorithm based on blind source separation and distributed in an R package called osd, to extract the spectra of the compounds appearing in GC×GC-MS chromatograms in an automated manner. We studied the performance of ICA-OSD by the quantification of 38 metabolites through a set of 20 Jurkat cell samples analyzed by GC×GC-MS. The quantification by ICA-OSD was compared with a supervised quantification by selective ions, and most of the R(2) coefficients of determination were in good agreement (R(2)>0.90) while up to 24 cases exhibited an excellent linear relation (R(2)>0.95). We concluded that ICA-OSD can be used to resolve co-eluted compounds in GC×GC-MS.
authors.affiliation: Metabolomics Platform - IISPV, Department of Electrical and Automation Engineering (DEEEA), Universitat Rovira i Virgili, Tarragona, Catalonia, Spain; Biomedical Research Networking Center in Diabetes and Associated Metabolic Disorders (CIBERDEM), Madrid, Spain. Electronic address: xavier.domingo@urv.cat.
authors.forename: Xavier
authors.initials: X
authors.lastname: Domingo-Almenara
authors.affiliation: B2SLAB, Department d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial, Universitat Politècnica de Catalunya, Barcelona, Catalonia, Spain; Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Madrid, Spain.
authors.forename: Alexandre
authors.initials: A
authors.lastname: Perera
authors.affiliation: Metabolomics Platform - IISPV, Department of Electrical and Automation Engineering (DEEEA), Universitat Rovira i Virgili, Tarragona, Catalonia, Spain; Biomedical Research Networking Center in Diabetes and Associated Metabolic Disorders (CIBERDEM), Madrid, Spain.
authors.forename: Noelia
authors.initials: N
authors.lastname: Ramírez
authors.affiliation: Metabolomics Platform - IISPV, Department of Electrical and Automation Engineering (DEEEA), Universitat Rovira i Virgili, Tarragona, Catalonia, Spain; Biomedical Research Networking Center in Diabetes and Associated Metabolic Disorders (CIBERDEM), Madrid, Spain.
authors.forename: Jesus
authors.initials: J
authors.lastname: Brezmes
mesh_terms: D000465:Algorithms; D001331:Automation; D008401:Gas Chromatography-Mass Spectrometry / Q000379:methods*; D055432:Metabolomics
keywords: Compound deconvolution; Comprehensive gas chromatography; Independent component analysis; Multivariate curve resolution; Orthogonal signal deconvolution