A Checklist for Reproducible Computational Analysis in Clinical Metabolomics Research
Clinical metabolomics emerged as a novel approach for biomarker discovery with the translational potential to guide next-generation therapeutics and precision health interventions. However, reproducibility in clinical research employing metabolomics data is challenging. Checklists are a helpful tool...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-01-01
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| Series: | Metabolites |
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| Online Access: | https://www.mdpi.com/2218-1989/12/1/87 |
| _version_ | 1797492008395210752 |
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| author | Xinsong Du Juan J. Aristizabal-Henao Timothy J. Garrett Mathias Brochhausen William R. Hogan Dominick J. Lemas |
| author_facet | Xinsong Du Juan J. Aristizabal-Henao Timothy J. Garrett Mathias Brochhausen William R. Hogan Dominick J. Lemas |
| author_sort | Xinsong Du |
| collection | DOAJ |
| description | Clinical metabolomics emerged as a novel approach for biomarker discovery with the translational potential to guide next-generation therapeutics and precision health interventions. However, reproducibility in clinical research employing metabolomics data is challenging. Checklists are a helpful tool for promoting reproducible research. Existing checklists that promote reproducible metabolomics research primarily focused on metadata and may not be sufficient to ensure reproducible metabolomics data processing. This paper provides a checklist including actions that need to be taken by researchers to make computational steps reproducible for clinical metabolomics studies. We developed an eight-item checklist that includes criteria related to reusable data sharing and reproducible computational workflow development. We also provided recommended tools and resources to complete each item, as well as a GitHub project template to guide the process. The checklist is concise and easy to follow. Studies that follow this checklist and use recommended resources may facilitate other researchers to reproduce metabolomics results easily and efficiently. |
| first_indexed | 2024-03-10T00:57:24Z |
| format | Article |
| id | doaj.art-1e291851eb6547fea294c4a515752ee7 |
| institution | Directory Open Access Journal |
| issn | 2218-1989 |
| language | English |
| last_indexed | 2024-03-10T00:57:24Z |
| publishDate | 2022-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Metabolites |
| spelling | doaj.art-1e291851eb6547fea294c4a515752ee72023-11-23T14:40:48ZengMDPI AGMetabolites2218-19892022-01-011218710.3390/metabo12010087A Checklist for Reproducible Computational Analysis in Clinical Metabolomics ResearchXinsong Du0Juan J. Aristizabal-Henao1Timothy J. Garrett2Mathias Brochhausen3William R. Hogan4Dominick J. Lemas5Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL 32610, USABERG LLC, Framingham, MA 01701, USADepartment of Pathology, Immunology and Laboratory Medicine, College of Medicine, University of Florida, Gainesville, FL 32610, USADepartment of Biomedical Informatics, College of Medicine, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USADepartment of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL 32610, USADepartment of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL 32610, USAClinical metabolomics emerged as a novel approach for biomarker discovery with the translational potential to guide next-generation therapeutics and precision health interventions. However, reproducibility in clinical research employing metabolomics data is challenging. Checklists are a helpful tool for promoting reproducible research. Existing checklists that promote reproducible metabolomics research primarily focused on metadata and may not be sufficient to ensure reproducible metabolomics data processing. This paper provides a checklist including actions that need to be taken by researchers to make computational steps reproducible for clinical metabolomics studies. We developed an eight-item checklist that includes criteria related to reusable data sharing and reproducible computational workflow development. We also provided recommended tools and resources to complete each item, as well as a GitHub project template to guide the process. The checklist is concise and easy to follow. Studies that follow this checklist and use recommended resources may facilitate other researchers to reproduce metabolomics results easily and efficiently.https://www.mdpi.com/2218-1989/12/1/87clinical researchmetabolomicsreproducibilitychecklistreusable datareproducible workflow |
| spellingShingle | Xinsong Du Juan J. Aristizabal-Henao Timothy J. Garrett Mathias Brochhausen William R. Hogan Dominick J. Lemas A Checklist for Reproducible Computational Analysis in Clinical Metabolomics Research Metabolites clinical research metabolomics reproducibility checklist reusable data reproducible workflow |
| title | A Checklist for Reproducible Computational Analysis in Clinical Metabolomics Research |
| title_full | A Checklist for Reproducible Computational Analysis in Clinical Metabolomics Research |
| title_fullStr | A Checklist for Reproducible Computational Analysis in Clinical Metabolomics Research |
| title_full_unstemmed | A Checklist for Reproducible Computational Analysis in Clinical Metabolomics Research |
| title_short | A Checklist for Reproducible Computational Analysis in Clinical Metabolomics Research |
| title_sort | checklist for reproducible computational analysis in clinical metabolomics research |
| topic | clinical research metabolomics reproducibility checklist reusable data reproducible workflow |
| url | https://www.mdpi.com/2218-1989/12/1/87 |
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