Evaluating LC-HRMS metabolomics data processing software using FAIR principles for research software.

Metabolomics / methods Chromatography, Liquid / methods Mass Spectrometry / methods Software Data Management
FAIR principles Liquid chromatography-mass spectrometry Metabolomics Open science Reproducibility Research software

Journal

Metabolomics : Official journal of the Metabolomic Society
ISSN: 1573-3890
Titre abrégé: Metabolomics
Pays: United States
ID NLM: 101274889

Informations de publication

Date de publication:
06 02 2023
Historique:
received: 08 12 2022
accepted: 20 01 2023
entrez: 6 2 2023
pubmed: 7 2 2023
medline: 9 2 2023
Statut: epublish

Résumé

Liquid chromatography-high resolution mass spectrometry (LC-HRMS) is a popular approach for metabolomics data acquisition and requires many data processing software tools. The FAIR Principles - Findability, Accessibility, Interoperability, and Reusability - were proposed to promote open science and reusable data management, and to maximize the benefit obtained from contemporary and formal scholarly digital publishing. More recently, the FAIR principles were extended to include Research Software (FAIR4RS). This study facilitates open science in metabolomics by providing an implementation solution for adopting FAIR4RS in the LC-HRMS metabolomics data processing software. We believe our evaluation guidelines and results can help improve the FAIRness of research software. We evaluated 124 LC-HRMS metabolomics data processing software obtained from a systematic review and selected 61 software for detailed evaluation using FAIR4RS-related criteria, which were extracted from the literature along with internal discussions. We assigned each criterion one or more FAIR4RS categories through discussion. The minimum, median, and maximum percentages of criteria fulfillment of software were 21.6%, 47.7%, and 71.8%. Statistical analysis revealed no significant improvement in FAIRness over time. We identified four criteria covering multiple FAIR4RS categories but had a low %fulfillment: (1) No software had semantic annotation of key information; (2) only 6.3% of evaluated software were registered to Zenodo and received DOIs; (3) only 14.5% of selected software had official software containerization or virtual machine; (4) only 16.7% of evaluated software had a fully documented functions in code. According to the results, we discussed improvement strategies and future directions.

Sections du résumé

BACKGROUND
Liquid chromatography-high resolution mass spectrometry (LC-HRMS) is a popular approach for metabolomics data acquisition and requires many data processing software tools. The FAIR Principles - Findability, Accessibility, Interoperability, and Reusability - were proposed to promote open science and reusable data management, and to maximize the benefit obtained from contemporary and formal scholarly digital publishing. More recently, the FAIR principles were extended to include Research Software (FAIR4RS).
AIM OF REVIEW
This study facilitates open science in metabolomics by providing an implementation solution for adopting FAIR4RS in the LC-HRMS metabolomics data processing software. We believe our evaluation guidelines and results can help improve the FAIRness of research software.
KEY SCIENTIFIC CONCEPTS OF REVIEW
We evaluated 124 LC-HRMS metabolomics data processing software obtained from a systematic review and selected 61 software for detailed evaluation using FAIR4RS-related criteria, which were extracted from the literature along with internal discussions. We assigned each criterion one or more FAIR4RS categories through discussion. The minimum, median, and maximum percentages of criteria fulfillment of software were 21.6%, 47.7%, and 71.8%. Statistical analysis revealed no significant improvement in FAIRness over time. We identified four criteria covering multiple FAIR4RS categories but had a low %fulfillment: (1) No software had semantic annotation of key information; (2) only 6.3% of evaluated software were registered to Zenodo and received DOIs; (3) only 14.5% of selected software had official software containerization or virtual machine; (4) only 16.7% of evaluated software had a fully documented functions in code. According to the results, we discussed improvement strategies and future directions.

Identifiants

DOI: 10.1007/s11306-023-01974-3 PMID: 36745241
pubmed: 36745241
doi: 10.1007/s11306-023-01974-3
pii: 10.1007/s11306-023-01974-3
doi:

Types de publication

Systematic Review Journal Article Review Research Support, Non-U.S. Gov't Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

11

Subventions

Organisme : NIDDK NIH HHS
ID : K01DK115632
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1TR001427
Pays : United States

Informations de copyright

© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

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Auteurs

Xinsong Du (X)

Department of Health Outcomes and Biomedical Informatics, University of Florida College of Medicine, Gainesville, FL, USA.

Farhad Dastmalchi (F)

Department of Health Outcomes and Biomedical Informatics, University of Florida College of Medicine, Gainesville, FL, USA.

Hao Ye (H)

Health Science Center Libraries, University of Florida, Florida, USA.

Timothy J Garrett (TJ)

Department of Pathology, Immunology and Laboratory Medicine, College of Medicine, University of Florida, Florida, USA.

Matthew A Diller (MA)

Department of Health Outcomes and Biomedical Informatics, University of Florida College of Medicine, Gainesville, FL, USA.

Mei Liu (M)

Department of Health Outcomes and Biomedical Informatics, University of Florida College of Medicine, Gainesville, FL, USA.

William R Hogan (WR)

Department of Health Outcomes and Biomedical Informatics, University of Florida College of Medicine, Gainesville, FL, USA.

Mathias Brochhausen (M)

Department of Biomedical Informatics, College of Medicine, University of Arkansas for Medical Sciences, Little Rock, USA.

Dominick J Lemas (DJ)

Department of Health Outcomes and Biomedical Informatics, University of Florida College of Medicine, Gainesville, FL, USA. djlemas@ufl.edu.
Department of Obstetrics and Gynecology, University of Florida College of Medicine, Florida, Gainesville, United States. djlemas@ufl.edu.
Center for Perinatal Outcomes Research, University of Florida College of Medicine, Gainesville, United States. djlemas@ufl.edu.

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questionsmedicales.fr › Disciplines des sciences naturelles › Chimie › Biochimie › Métabolomique › Evaluating LC-HRMS metabolomics data...
questionsmedicales.fr › Techniques d'investigation › Techniques de chimie analytique › Chromatographie › Chromatographie en phase liquide › Evaluating LC-HRMS metabolomics data...
questionsmedicales.fr › Techniques d'investigation › Techniques de chimie analytique › Spectrométrie de masse › Evaluating LC-HRMS metabolomics data...
questionsmedicales.fr › Sciences de l'information › Méthodologies informatiques › Logiciel › Evaluating LC-HRMS metabolomics data...
questionsmedicales.fr › Sciences de l'information › Mémorisation et recherche des informations › Gestion des données › Evaluating LC-HRMS metabolomics data...