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

Xinsong Du; Farhad Dastmalchi; Hao Ye; Timothy J Garrett; Matthew A Diller; Mei Liu; William R Hogan; Mathias Brochhausen; Dominick J Lemas

doi:10.1007/s11306-023-01974-3

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

Metabolomics. 2023 Feb 6;19(2):11. doi: 10.1007/s11306-023-01974-3.

Authors

Affiliations

¹ Department of Health Outcomes and Biomedical Informatics, University of Florida College of Medicine, Gainesville, FL, USA.
² Health Science Center Libraries, University of Florida, Florida, USA.
³ Department of Pathology, Immunology and Laboratory Medicine, College of Medicine, University of Florida, Florida, USA.
⁴ Department of Biomedical Informatics, College of Medicine, University of Arkansas for Medical Sciences, Little Rock, USA.
⁵ Department of Health Outcomes and Biomedical Informatics, University of Florida College of Medicine, Gainesville, FL, USA. djlemas@ufl.edu.
⁶ Department of Obstetrics and Gynecology, University of Florida College of Medicine, Florida, Gainesville, United States. djlemas@ufl.edu.
⁷ Center for Perinatal Outcomes Research, University of Florida College of Medicine, Gainesville, United States. djlemas@ufl.edu.

PMID: 36745241
DOI: 10.1007/s11306-023-01974-3

Abstract

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.

Keywords: FAIR principles; Liquid chromatography-mass spectrometry; Metabolomics; Open science; Reproducibility; Research software.

Publication types

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

MeSH terms

Chromatography, Liquid / methods
Data Management
Mass Spectrometry / methods
Metabolomics* / methods
Software*

Abstract

Publication types

MeSH terms

Grants and funding