Repositori institucional URV
Español Català English
TITLE:
Automated resolution of chromatographic signals by independent component analysis-orthogonal signal deconvolution in comprehensive gas chromatography/mass spectrometry-based metabolomics - imarina:9282606

URV's Author/s:Brezmes Llecha, Jesús Jorge / Domingo Almenara, Xavier / Ramírez González, Noelia
Author, as appears in the article.:Domingo-Almenara X; Perera A; Ramírez N; Brezmes J
Author's mail:xavier.domingo@urv.cat
noelia.ramirez@urv.cat
jesus.brezmes@urv.cat
Author identifier:0000-0002-7704-8550
Journal publication year:2016
Publication Type:Journal Publications
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
Papper original source:Computer Methods And Programs In Biomedicine. 130 135-141
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.
Article's DOI:10.1016/j.cmpb.2016.03.007
Link to the original source:https://www.sciencedirect.com/science/article/abs/pii/S0169260715300511
Papper version:info:eu-repo/semantics/acceptedVersion
licence for use:https://creativecommons.org/licenses/by/3.0/es/
Department:Enginyeria Electrònica, Elèctrica i Automàtica
Licence document URL:https://repositori.urv.cat/ca/proteccio-de-dades/
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
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
Entity:Universitat Rovira i Virgili
Record's date:2024-11-09
Search your record at:

Available files
FileDescriptionFormat
DocumentPrincipalDocumentPrincipalapplication/pdf

Information

© 2011 Universitat Rovira i Virgili