Evidence map›Paper›PMID 36745241›Full record

SynthesisMetabolomics : Official journal of the Metabolomic Society2023

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

Abstract readSystematic Review
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in Metabolomics : Official journal of the Metabolomic Society, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

  1. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Xinsong DuDepartment of Health Outcomes and Biomedical Informatics, University of Florida College of Medicine, Gainesville, FL, USA.
Farhad DastmalchiDepartment of Health Outcomes and Biomedical Informatics, University of Florida College of Medicine, Gainesville, FL, USA.
Hao YeHealth Science Center Libraries, University of Florida, Florida, USA.
Timothy J GarrettDepartment of Pathology, Immunology and Laboratory Medicine, College of Medicine, University of Florida, Florida, USA.
Matthew A DillerDepartment of Health Outcomes and Biomedical Informatics, University of Florida College of Medicine, Gainesville, FL, USA.
Mei LiuDepartment of Health Outcomes and Biomedical Informatics, University of Florida College of Medicine, Gainesville, FL, USA.
William R HoganDepartment of Health Outcomes and Biomedical Informatics, University of Florida College of Medicine, Gainesville, FL, USA.
Mathias BrochhausenDepartment of Biomedical Informatics, College of Medicine, University of Arkansas for Medical Sciences, Little Rock, USA.
Dominick J LemasDepartment of Health Outcomes and Biomedical Informatics, University of Florida College of Medicine, Gainesville, FL, USA. djlemas@ufl.edu.

Funding

Using social networks to map and evaluate team science across CTSA hubsUL1TR001427 · NCATS · UNIVERSITY OF FLORIDA · PI MITCHELL, DUANE A. · 2015 to 2024
$37.2M
Human milk metabolomics and microbe-host interactions associated with pediatric obesityK01DK115632 · NIDDK · UNIVERSITY OF FLORIDA · PI LEMAS, DOMINICK JOSEPH · 2019 to 2023
$831k
NCATS NIH HHS UL1 TR001427NCATS NIH HHS UL1TR001427NIDDK NIH HHS K01 DK115632NIDDK NIH HHS K01DK115632
6 · The paper itself

Abstract

backgroundLiquid 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.

Indexed as

MetabolomicsSoftwareChromatography, LiquidData ManagementMass SpectrometryFAIR principlesLiquid chromatography-mass spectrometryMetabolomicsOpen scienceReproducibilityResearch software

Identifiers

PMID36745241
PMCPMC12087353

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.