Detailed Information on Publication Record
2024
Harmonized quality assurance/quality control provisions to assess completeness and robustness of MS1 data preprocessing for LC-HRMS-based suspect screening and non-targeted analysis
LENNON, Sarah, Jade CHAKER, Elliott James PRICE, Juliane HOLLENDER, Carolin HUBER et. al.Basic information
Original name
Harmonized quality assurance/quality control provisions to assess completeness and robustness of MS1 data preprocessing for LC-HRMS-based suspect screening and non-targeted analysis
Authors
LENNON, Sarah, Jade CHAKER, Elliott James PRICE (826 United Kingdom of Great Britain and Northern Ireland, guarantor, belonging to the institution), Juliane HOLLENDER, Carolin HUBER, Tobias SCHULZE, Lutz AHRENS, Frederic BEEN, Nicolas CREUSOT, Laurent DEBRAUWER, Gaud DERVILLY, Catherine GABRIEL, Thierry GUERIN, Baninia HABCHI, Emilien L. JAMIN, Jana KLÁNOVÁ (203 Czech Republic, belonging to the institution), Tina KOSJEK, Bruno LE BIZEC, Jeroen MEIJER, Hans MOL, Rosalie NIJSSEN, Herbert OBERACHER, Nafsika PAPAIOANNOU, Julien PARINET, Dimosthenis SARIGIANNIS, Michael A. STRAVS, Žiga TKALEC (705 Slovenia, belonging to the institution), Emma L. SCHYMANSKI, Marja LAMOREE, Jean-Philippe ANTIGNAC and Arthur DAVID
Edition
TrAC Trends in Analytical Chemistry, Oxford, Elsevier, 2024, 0165-9936
Other information
Language
English
Type of outcome
Článek v odborném periodiku
Field of Study
10406 Analytical chemistry
Country of publisher
United Kingdom of Great Britain and Northern Ireland
Confidentiality degree
není předmětem státního či obchodního tajemství
References:
Impact factor
Impact factor: 13.100 in 2022
Organization unit
Faculty of Science
UT WoS
001223574100001
Keywords in English
High-resolution mass spectrometry; Exposomics; Metabolomics; Non-targeted analysis; Suspect screening analysis; Data preprocessing; Contaminants of emerging concern; Chemical exposome; Harmonized QA/QC
Tags
Tags
International impact, Reviewed
Změněno: 5/6/2024 10:41, Mgr. Michaela Hylsová, Ph.D.
Abstract
V originále
Non-targeted and suspect screening analysis using liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS) holds great promise to comprehensively characterize complex chemical mixtures. Data preprocessing is a crucial part of the process, however, some limitations are observed: (i) peak-picking and feature extraction might be incomplete, especially for low abundant compounds, and (ii) limited reproducibility has been observed between laboratories and software for detected features and their relative quantification. We first conducted a critical review of existing solutions that could improve the reproducibility of preprocessing for LC-HRMS. Solutions include providing repositories and reporting guidelines, open and modular processing workflows, public benchmark datasets, tools to optimize the data preprocessing and to filter out false positive detections. We then propose harmonized quality assurance/quality control guidelines that would allow to assess the sensitivity of feature detection, reproducibility, integration accuracy, precision, accuracy, and consistency of data preprocessing for human biomonitoring, food and environmental communities.
Links
EF17_043/0009632, research and development project |
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LM2023069, research and development project |
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101057014, interní kód MU |
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857560, interní kód MU (CEP code: EF17_043/0009632) |
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