Mining for peaks in lc-hrms datasets using finnee - a case study with exhaled breath condensates from healthy, asthmatic, and copd patients

Bibliographic Details
Main Author: Erny, Guillaume L.
Publication Date: 2020
Other Authors: Gomes, Ricardo A., Santos, Mónica S.F., Santos, Lúcia, Neuparth, N, Carreiro-Martins, Pedro, Marques, João Gaspar, Guerreiro, Ana C.L., Gomes-Alves, Patrícia
Format: Article
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10362/101581
Summary: This work was financially supported by the projects: (i) UID/ EQU/00511/2019 - Laboratory for Process Engineering, Environment, Biotechnology and Energy − LEPABE funded by national funds through FCT/MCTES (PIDDAC); (ii) POCI-01-0145-FEDER-029702 and POCI-01-0145-FEDER031297 funded by FEDER funds through COMPETE2020 − Programa Operacional Competitividade e Internacionalizaca̧ õ (POCI) and by national funds (PIDDAC) through FCT/ MCTES; (iii) AstraZeneca − Projecto OLDER (CEDOC/ 2015/59); (iv) iNOVA4Health - UID/Multi/04462/2013, financially supported by FCT/Ministerio da Educação e Ciência, and co-funded by FEDER under the PT2020 Partnership Agreement.
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spelling Mining for peaks in lc-hrms datasets using finnee - a case study with exhaled breath condensates from healthy, asthmatic, and copd patientsChemistry(all)Chemical Engineering(all)This work was financially supported by the projects: (i) UID/ EQU/00511/2019 - Laboratory for Process Engineering, Environment, Biotechnology and Energy − LEPABE funded by national funds through FCT/MCTES (PIDDAC); (ii) POCI-01-0145-FEDER-029702 and POCI-01-0145-FEDER031297 funded by FEDER funds through COMPETE2020 − Programa Operacional Competitividade e Internacionalizaca̧ õ (POCI) and by national funds (PIDDAC) through FCT/ MCTES; (iii) AstraZeneca − Projecto OLDER (CEDOC/ 2015/59); (iv) iNOVA4Health - UID/Multi/04462/2013, financially supported by FCT/Ministerio da Educação e Ciência, and co-funded by FEDER under the PT2020 Partnership Agreement.Separation techniques hyphenated to high-resolution mass spectrometry are essential in untargeted metabolomic analyses. Due to the complexity and size of the resulting data, analysts rely on computer-assisted tools to mine for features that may represent a chromatographic signal. However, this step remains problematic, and a high number of false positives are often obtained. This work reports a novel approach where each step is carefully controlled to decrease the likelihood of errors. Datasets are first corrected for baseline drift and background noise before the MS scans are converted from profile to centroid. A new alignment strategy that includes purity control is introduced, and features are quantified using the original data with scans recorded as profile, not the extracted features. All the algorithms used in this work are part of the Finnee Matlab toolbox that is freely available. The approach was validated using metabolites in exhaled breath condensates to differentiate individuals diagnosed with asthma from patients with chronic obstructive pulmonary disease. With this new pipeline, twice as many markers were found with Finnee in comparison to XCMS-online, and nearly 50% more than with MS-Dial, two of the most popular freeware for untargeted metabolomics analysis.NOVA Medical School|Faculdade de Ciências Médicas (NMS|FCM)Centro de Estudos de Doenças Crónicas (CEDOC)Comprehensive Health Research Centre (CHRC) - pólo NMSInstituto de Tecnologia Química e Biológica António Xavier (ITQB)RUNErny, Guillaume L.Gomes, Ricardo A.Santos, Mónica S.F.Santos, LúciaNeuparth, NCarreiro-Martins, PedroMarques, João GasparGuerreiro, Ana C.L.Gomes-Alves, Patrícia2020-07-27T22:45:25Z2020-07-072020-07-07T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10362/101581eng2470-1343PURE: 19218651https://doi.org/10.1021/acsomega.0c01610info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-22T17:46:44Zoai:run.unl.pt:10362/101581Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T17:17:47.113487Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Mining for peaks in lc-hrms datasets using finnee - a case study with exhaled breath condensates from healthy, asthmatic, and copd patients
title Mining for peaks in lc-hrms datasets using finnee - a case study with exhaled breath condensates from healthy, asthmatic, and copd patients
spellingShingle Mining for peaks in lc-hrms datasets using finnee - a case study with exhaled breath condensates from healthy, asthmatic, and copd patients
Erny, Guillaume L.
Chemistry(all)
Chemical Engineering(all)
title_short Mining for peaks in lc-hrms datasets using finnee - a case study with exhaled breath condensates from healthy, asthmatic, and copd patients
title_full Mining for peaks in lc-hrms datasets using finnee - a case study with exhaled breath condensates from healthy, asthmatic, and copd patients
title_fullStr Mining for peaks in lc-hrms datasets using finnee - a case study with exhaled breath condensates from healthy, asthmatic, and copd patients
title_full_unstemmed Mining for peaks in lc-hrms datasets using finnee - a case study with exhaled breath condensates from healthy, asthmatic, and copd patients
title_sort Mining for peaks in lc-hrms datasets using finnee - a case study with exhaled breath condensates from healthy, asthmatic, and copd patients
author Erny, Guillaume L.
author_facet Erny, Guillaume L.
Gomes, Ricardo A.
Santos, Mónica S.F.
Santos, Lúcia
Neuparth, N
Carreiro-Martins, Pedro
Marques, João Gaspar
Guerreiro, Ana C.L.
Gomes-Alves, Patrícia
author_role author
author2 Gomes, Ricardo A.
Santos, Mónica S.F.
Santos, Lúcia
Neuparth, N
Carreiro-Martins, Pedro
Marques, João Gaspar
Guerreiro, Ana C.L.
Gomes-Alves, Patrícia
author2_role author
author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv NOVA Medical School|Faculdade de Ciências Médicas (NMS|FCM)
Centro de Estudos de Doenças Crónicas (CEDOC)
Comprehensive Health Research Centre (CHRC) - pólo NMS
Instituto de Tecnologia Química e Biológica António Xavier (ITQB)
RUN
dc.contributor.author.fl_str_mv Erny, Guillaume L.
Gomes, Ricardo A.
Santos, Mónica S.F.
Santos, Lúcia
Neuparth, N
Carreiro-Martins, Pedro
Marques, João Gaspar
Guerreiro, Ana C.L.
Gomes-Alves, Patrícia
dc.subject.por.fl_str_mv Chemistry(all)
Chemical Engineering(all)
topic Chemistry(all)
Chemical Engineering(all)
description This work was financially supported by the projects: (i) UID/ EQU/00511/2019 - Laboratory for Process Engineering, Environment, Biotechnology and Energy − LEPABE funded by national funds through FCT/MCTES (PIDDAC); (ii) POCI-01-0145-FEDER-029702 and POCI-01-0145-FEDER031297 funded by FEDER funds through COMPETE2020 − Programa Operacional Competitividade e Internacionalizaca̧ õ (POCI) and by national funds (PIDDAC) through FCT/ MCTES; (iii) AstraZeneca − Projecto OLDER (CEDOC/ 2015/59); (iv) iNOVA4Health - UID/Multi/04462/2013, financially supported by FCT/Ministerio da Educação e Ciência, and co-funded by FEDER under the PT2020 Partnership Agreement.
publishDate 2020
dc.date.none.fl_str_mv 2020-07-27T22:45:25Z
2020-07-07
2020-07-07T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/101581
url http://hdl.handle.net/10362/101581
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2470-1343
PURE: 19218651
https://doi.org/10.1021/acsomega.0c01610
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
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