Articles producció científica> Enginyeria Electrònica, Elèctrica i Automàtica

Automated resolution of chromatographic signals by independent component analysis-orthogonal signal deconvolution in comprehensive gas chromatography/mass spectrometry-based metabolomics

  • Identification data

    Identifier: imarina:9282606
  • Authors:

    Domingo-Almenara X
    Perera A
    Ramírez N
    Brezmes J
  • Others:

    Author, as appears in the article.: Domingo-Almenara X; Perera A; Ramírez N; Brezmes J
    Department: Enginyeria Electrònica, Elèctrica i Automàtica
    URV's Author/s: Brezmes Llecha, Jesús Jorge / Ramírez González, Noelia
    Keywords: Spectrometry Procedures Principal component analysis Phosphoric acid Orthogonal signals Orthogonal signal deconvolution Multivariate curve resolution Multivariant analysis Metabolomics Mass spectrometry Mass fragmentography Lymphatic leukemia Linear relation Lactic acid Jurkat cell line Inositol Independent component analysis Human cell Human Glycerol Gas chromatography/mass spectrometry Gas chromatography-mass spectrometry Gas chromatography Erythritol Data handling Correlation coefficient Controlled study Comprehensive gas chromatography Compound deconvolution Chromatography Chromatographic signals Chromatographic analysis Blind source separation Biological samples Bioinformatics Automation Automated resolution Aspartic acid Article Apoptosis Analytic method Algorithms Algorithm multivariate curve resolution independent component analysis comprehensive gas chromatography compound deconvolution
    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 R2 coefficients of determination were in good agreement (R2>0.90) while up to 24 cases exhibited an excellent linear relation (R2>0.95). We concluded that ICA-OSD can be used to resolve co-eluted compounds in GC×GC-MS. © 2016 Elsevier Ireland Ltd.
    Thematic Areas: Software Saúde coletiva Psicología Odontología Medicina iii Medicina ii Medicina i Medical informatics Matemática / probabilidade e estatística Interdisciplinar Health informatics General medicine Engineering, biomedical Engenharias iv Engenharias iii Engenharias ii Educação física Computer science, theory & methods Computer science, interdisciplinary applications Computer science applications Ciências biológicas ii Ciências biológicas i Ciências ambientais Ciências agrárias i Ciência da computação Biotecnología
    licence for use: https://creativecommons.org/licenses/by/3.0/es/
    Author's mail: noelia.ramirez@urv.cat jesus.brezmes@urv.cat
    Author identifier: 0000-0002-7704-8550
    Record's date: 2024-07-20
    Papper version: info:eu-repo/semantics/acceptedVersion
    Link to the original source: https://www.sciencedirect.com/science/article/abs/pii/S0169260715300511
    Licence document URL: http://repositori.urv.cat/ca/proteccio-de-dades/
    Papper original source: Computer Methods And Programs In Biomedicine. 130 135-141
    APA: Domingo-Almenara X; Perera A; Ramírez N; Brezmes J (2016). Automated resolution of chromatographic signals by independent component analysis-orthogonal signal deconvolution in comprehensive gas chromatography/mass spectrometry-based metabolomics. Computer Methods And Programs In Biomedicine, 130(), 135-141. DOI: 10.1016/j.cmpb.2016.03.007
    Article's DOI: 10.1016/j.cmpb.2016.03.007
    Entity: Universitat Rovira i Virgili
    Journal publication year: 2016
    Publication Type: Journal Publications
  • Keywords:

    Computer Science Applications,Computer Science, Interdisciplinary Applications,Computer Science, Theory & Methods,Engineering, Biomedical,Health Informatics,Medical Informatics,Software
    Spectrometry
    Procedures
    Principal component analysis
    Phosphoric acid
    Orthogonal signals
    Orthogonal signal deconvolution
    Multivariate curve resolution
    Multivariant analysis
    Metabolomics
    Mass spectrometry
    Mass fragmentography
    Lymphatic leukemia
    Linear relation
    Lactic acid
    Jurkat cell line
    Inositol
    Independent component analysis
    Human cell
    Human
    Glycerol
    Gas chromatography/mass spectrometry
    Gas chromatography-mass spectrometry
    Gas chromatography
    Erythritol
    Data handling
    Correlation coefficient
    Controlled study
    Comprehensive gas chromatography
    Compound deconvolution
    Chromatography
    Chromatographic signals
    Chromatographic analysis
    Blind source separation
    Biological samples
    Bioinformatics
    Automation
    Automated resolution
    Aspartic acid
    Article
    Apoptosis
    Analytic method
    Algorithms
    Algorithm
    multivariate curve resolution
    independent component analysis
    comprehensive gas chromatography
    compound deconvolution
    Software
    Saúde coletiva
    Psicología
    Odontología
    Medicina iii
    Medicina ii
    Medicina i
    Medical informatics
    Matemática / probabilidade e estatística
    Interdisciplinar
    Health informatics
    General medicine
    Engineering, biomedical
    Engenharias iv
    Engenharias iii
    Engenharias ii
    Educação física
    Computer science, theory & methods
    Computer science, interdisciplinary applications
    Computer science applications
    Ciências biológicas ii
    Ciências biológicas i
    Ciências ambientais
    Ciências agrárias i
    Ciência da computação
    Biotecnología
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