Untangling comprehensive two-dimensional liquid chromatography data sets using regions of interest and multivariate curve resolution approaches

Data analysis remains a major challenge in the global application of comprehensive two-dimensional liquid chromatography (LC × LC). Advanced chemometric tools have been proposed to reduce the complexity of LC × LC datasets. In this work, key aspects of LC × LC are summarized from a chemometrics perspective. In particular, the recently developed ROIMCR method is proposed and adapted for LC × LC data analysis. First, this strategy consists of selecting of the Regions of Interest (ROI), in which data are filtered and compressed. Second, the resolution of the elution profiles of the sample constituents using the Multivariate Curve Resolution – Alternating Least Squares (MCR-ALS) method. A detailed overview of this recently developed tool and examples of its application in LC × LC are given, as well as pre-processing and post-processing tools to facilitate and complement the analysis of LC × LC data and the optimal interpretation of results.

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Main Authors: Pérez-Cova, Miriam, Jaumot, Joaquim, Tauler, Romà
Other Authors: Ministerio de Ciencia e Innovación (España)
Format: artículo biblioteca
Language:English
Published: Elsevier 2021-04-01
Subjects:ROIMCR, Chemometrics, Data analysis, LC × LC, MCR-ALS,
Online Access:http://hdl.handle.net/10261/266228
http://dx.doi.org/10.13039/501100004837
https://api.elsevier.com/content/abstract/scopus_id/85101469591
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spelling dig-idaea-es-10261-2662282024-05-16T20:46:18Z Untangling comprehensive two-dimensional liquid chromatography data sets using regions of interest and multivariate curve resolution approaches Pérez-Cova, Miriam Jaumot, Joaquim Tauler, Romà Ministerio de Ciencia e Innovación (España) ROIMCR Chemometrics Data analysis LC × LC MCR-ALS Data analysis remains a major challenge in the global application of comprehensive two-dimensional liquid chromatography (LC × LC). Advanced chemometric tools have been proposed to reduce the complexity of LC × LC datasets. In this work, key aspects of LC × LC are summarized from a chemometrics perspective. In particular, the recently developed ROIMCR method is proposed and adapted for LC × LC data analysis. First, this strategy consists of selecting of the Regions of Interest (ROI), in which data are filtered and compressed. Second, the resolution of the elution profiles of the sample constituents using the Multivariate Curve Resolution – Alternating Least Squares (MCR-ALS) method. A detailed overview of this recently developed tool and examples of its application in LC × LC are given, as well as pre-processing and post-processing tools to facilitate and complement the analysis of LC × LC data and the optimal interpretation of results. The research leading to these results has received funding from the Spanish Ministry of Science and Innovation (MCI, Grants CTQ2017-82598-P and PID2019-105732GB-C21). The authors also want to grant support from the Catalan Agency for Management of University and Research Grants (AGAUR, Grant 2017SGR753) and the Spanish MCI (Severo Ochoa Project CEX2018-000794-S). MPC acknowledges a predoctoral FPU 16/02640 scholarship from the Spanish Ministry of Education and Vocational Training (MEFP). Peer reviewed 2022-04-05T05:52:51Z 2022-04-05T05:52:51Z 2021-04-01 artículo http://purl.org/coar/resource_type/c_6501 TrAC Trends in Analytical Chemistry 137: 116207 (2021) 01659936 http://hdl.handle.net/10261/266228 10.1016/j.trac.2021.116207 http://dx.doi.org/10.13039/501100004837 2-s2.0-85101469591 https://api.elsevier.com/content/abstract/scopus_id/85101469591 en #PLACEHOLDER_PARENT_METADATA_VALUE# #PLACEHOLDER_PARENT_METADATA_VALUE# #PLACEHOLDER_PARENT_METADATA_VALUE# info:eu-repo/grantAgreement/EC/MCIN/ CTQ2017-82598-P info:eu-repo/grantAgreement/EC/MCIN/PID2019-105732GB-C21 info:eu-repo/grantAgreement/EC/MCIN/CEX2018-000794-S TrAC - Trends in Analytical Chemistry Postprint https://doi.org/10.1016/j.trac.2021.116207 Sí open Elsevier
institution IDAEA ES
collection DSpace
country España
countrycode ES
component Bibliográfico
access En linea
databasecode dig-idaea-es
tag biblioteca
region Europa del Sur
libraryname Biblioteca del IDAEA España
language English
topic ROIMCR
Chemometrics
Data analysis
LC × LC
MCR-ALS
ROIMCR
Chemometrics
Data analysis
LC × LC
MCR-ALS
spellingShingle ROIMCR
Chemometrics
Data analysis
LC × LC
MCR-ALS
ROIMCR
Chemometrics
Data analysis
LC × LC
MCR-ALS
Pérez-Cova, Miriam
Jaumot, Joaquim
Tauler, Romà
Untangling comprehensive two-dimensional liquid chromatography data sets using regions of interest and multivariate curve resolution approaches
description Data analysis remains a major challenge in the global application of comprehensive two-dimensional liquid chromatography (LC × LC). Advanced chemometric tools have been proposed to reduce the complexity of LC × LC datasets. In this work, key aspects of LC × LC are summarized from a chemometrics perspective. In particular, the recently developed ROIMCR method is proposed and adapted for LC × LC data analysis. First, this strategy consists of selecting of the Regions of Interest (ROI), in which data are filtered and compressed. Second, the resolution of the elution profiles of the sample constituents using the Multivariate Curve Resolution – Alternating Least Squares (MCR-ALS) method. A detailed overview of this recently developed tool and examples of its application in LC × LC are given, as well as pre-processing and post-processing tools to facilitate and complement the analysis of LC × LC data and the optimal interpretation of results.
author2 Ministerio de Ciencia e Innovación (España)
author_facet Ministerio de Ciencia e Innovación (España)
Pérez-Cova, Miriam
Jaumot, Joaquim
Tauler, Romà
format artículo
topic_facet ROIMCR
Chemometrics
Data analysis
LC × LC
MCR-ALS
author Pérez-Cova, Miriam
Jaumot, Joaquim
Tauler, Romà
author_sort Pérez-Cova, Miriam
title Untangling comprehensive two-dimensional liquid chromatography data sets using regions of interest and multivariate curve resolution approaches
title_short Untangling comprehensive two-dimensional liquid chromatography data sets using regions of interest and multivariate curve resolution approaches
title_full Untangling comprehensive two-dimensional liquid chromatography data sets using regions of interest and multivariate curve resolution approaches
title_fullStr Untangling comprehensive two-dimensional liquid chromatography data sets using regions of interest and multivariate curve resolution approaches
title_full_unstemmed Untangling comprehensive two-dimensional liquid chromatography data sets using regions of interest and multivariate curve resolution approaches
title_sort untangling comprehensive two-dimensional liquid chromatography data sets using regions of interest and multivariate curve resolution approaches
publisher Elsevier
publishDate 2021-04-01
url http://hdl.handle.net/10261/266228
http://dx.doi.org/10.13039/501100004837
https://api.elsevier.com/content/abstract/scopus_id/85101469591
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AT jaumotjoaquim untanglingcomprehensivetwodimensionalliquidchromatographydatasetsusingregionsofinterestandmultivariatecurveresolutionapproaches
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