A Practical Guide to Metabolomics Software Development

Hui-Yin Chang^{1

2}, Sean M Colby³, Xiuxia Du⁴, Javier D Gomez⁵, Maximilian J Helf⁶, Katerina Kechris⁷, Christine R Kirkpatrick⁸, Shuzhao Li⁹, Gary J Patti¹⁰, Ryan S Renslow^{3

11}, Shankar Subramaniam^{8

12}, Mukesh Verma¹³, Jianguo Xia¹⁴, Jamey D Young^{5

15}

Affiliations

¹ Department of Pathology, University of Michigan, 1301 Catherine Street, Ann Arbor, Michigan 48109, United States.
² Department of Biomedical Sciences and Engineering, National Central University, No. 300, Zhongda Road, Zhongli District, Taoyuan City 320, Taiwan.
³ Biological Sciences Division, Pacific Northwest National Laboratory, P.O. Box 999, MSIN: K8-98, Richland, Washington 99352, United States.
⁴ Department of Bioinformatics & Genomics, University of North Carolina at Charlotte, 9201 University City Boulevard, Charlotte, North Carolina 28223, United States.
⁵ Department of Chemical and Biomolecular Engineering, Vanderbilt University, PMB 351604, 2301 Vanderbilt Place, Nashville, Tennessee 37235, United States.
⁶ Boyce Thompson Institute and Department of Chemistry and Chemical Biology, Cornell University, 533 Tower Road, Ithaca, New York 14853, United States.
⁷ Department of Biostatistics and Informatics, University of Colorado Anschutz Medical Campus, 13001 East 17th Place B119, Aurora, Colorado 80045, United States.
⁸ San Diego Supercomputer Center, University of California San Diego, MC 0505, 9500 Gilman Drive, La Jolla, California 92093, United States.
⁹ The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, Connecticut 06032, United States.
¹⁰ Department of Chemistry, Department of Medicine, and Siteman Cancer Center, Washington University in St. Louis, CB 1134, One Brookings Drive, St. Louis, Missouri 63130, United States.
¹¹ Gene and Linda Voiland School of Chemical Engineering and Bioengineering, Washington State University, P.O. Box 646515, Pullman, Washington 99164, United States.
¹² Department of Bioengineering, Department of Computer Science and Engineering, Department of Cellular and Molecular Medicine, and Department of Chemistry and Biochemistry, University of California San Diego, 9500 Gilman Drive #0412, La Jolla, California 92093, United States.
¹³ Epidemiology and Genomics Research Program, National Cancer Institute, National Institutes of Health, Suite 4E102, 9609 Medical Center Drive, MSC 9763, Rockville, Maryland 20850, United States.
¹⁴ Faculty of Agricultural and Environmental Sciences, McGill University, 21111 Lakeshore Road, Ste. Anne de Bellevue, Quebec H9X 3 V9, Canada.
¹⁵ Department of Molecular Physiology and Biophysics, Vanderbilt University, PMB 351604, 2301 Vanderbilt Place, Nashville, Tennessee 37235, United States.

PMID: 33467846
PMCID: PMC7859930
DOI: 10.1021/acs.analchem.0c03581

A Practical Guide to Metabolomics Software Development

Hui-Yin Chang et al. Anal Chem. 2021.

. 2021 Feb 2;93(4):1912-1923.

doi: 10.1021/acs.analchem.0c03581. Epub 2021 Jan 19.

Authors

Affiliations

¹ Department of Pathology, University of Michigan, 1301 Catherine Street, Ann Arbor, Michigan 48109, United States.
² Department of Biomedical Sciences and Engineering, National Central University, No. 300, Zhongda Road, Zhongli District, Taoyuan City 320, Taiwan.
³ Biological Sciences Division, Pacific Northwest National Laboratory, P.O. Box 999, MSIN: K8-98, Richland, Washington 99352, United States.
⁴ Department of Bioinformatics & Genomics, University of North Carolina at Charlotte, 9201 University City Boulevard, Charlotte, North Carolina 28223, United States.
⁵ Department of Chemical and Biomolecular Engineering, Vanderbilt University, PMB 351604, 2301 Vanderbilt Place, Nashville, Tennessee 37235, United States.
⁶ Boyce Thompson Institute and Department of Chemistry and Chemical Biology, Cornell University, 533 Tower Road, Ithaca, New York 14853, United States.
⁷ Department of Biostatistics and Informatics, University of Colorado Anschutz Medical Campus, 13001 East 17th Place B119, Aurora, Colorado 80045, United States.
⁸ San Diego Supercomputer Center, University of California San Diego, MC 0505, 9500 Gilman Drive, La Jolla, California 92093, United States.
⁹ The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, Connecticut 06032, United States.
¹⁰ Department of Chemistry, Department of Medicine, and Siteman Cancer Center, Washington University in St. Louis, CB 1134, One Brookings Drive, St. Louis, Missouri 63130, United States.
¹¹ Gene and Linda Voiland School of Chemical Engineering and Bioengineering, Washington State University, P.O. Box 646515, Pullman, Washington 99164, United States.
¹² Department of Bioengineering, Department of Computer Science and Engineering, Department of Cellular and Molecular Medicine, and Department of Chemistry and Biochemistry, University of California San Diego, 9500 Gilman Drive #0412, La Jolla, California 92093, United States.
¹³ Epidemiology and Genomics Research Program, National Cancer Institute, National Institutes of Health, Suite 4E102, 9609 Medical Center Drive, MSC 9763, Rockville, Maryland 20850, United States.
¹⁴ Faculty of Agricultural and Environmental Sciences, McGill University, 21111 Lakeshore Road, Ste. Anne de Bellevue, Quebec H9X 3 V9, Canada.
¹⁵ Department of Molecular Physiology and Biophysics, Vanderbilt University, PMB 351604, 2301 Vanderbilt Place, Nashville, Tennessee 37235, United States.

PMID: 33467846
PMCID: PMC7859930
DOI: 10.1021/acs.analchem.0c03581

Abstract

A growing number of software tools have been developed for metabolomics data processing and analysis. Many new tools are contributed by metabolomics practitioners who have limited prior experience with software development, and the tools are subsequently implemented by users with expertise that ranges from basic point-and-click data analysis to advanced coding. This Perspective is intended to introduce metabolomics software users and developers to important considerations that determine the overall impact of a publicly available tool within the scientific community. The recommendations reflect the collective experience of an NIH-sponsored Metabolomics Consortium working group that was formed with the goal of researching guidelines and best practices for metabolomics tool development. The recommendations are aimed at metabolomics researchers with little formal background in programming and are organized into three stages: (i) preparation, (ii) tool development, and (iii) distribution and maintenance.

PubMed Disclaimer

Conflict of interest statement

The authors declare the following competing financial interest(s): J.D.Y. is a co-founder, shareholder, and director of Metalytics, Inc.

Figures

**Figure 1**
Recommended guidelines at each stage of the software development pipeline.

**Figure 2**
Overview of a typical metabolomics workflow for analysis of MS datasets.

See this image and copyright information in PMC

References

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A Practical Guide to Metabolomics Software Development

Affiliations

A Practical Guide to Metabolomics Software Development

Authors

Affiliations

Abstract

Conflict of interest statement

Figures

References

Publication types

MeSH terms

Grants and funding

LinkOut - more resources

Full Text Sources

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