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. 2023 Aug 4;22(8):2540-2547.
doi: 10.1021/acs.jproteome.2c00602. Epub 2023 Jul 10.

CloMet: A Novel Open-Source and Modular Software Platform That Connects Established Metabolomics Repositories and Data Analysis Resources

Jordi Rodeiro  1 , Ester Vidaña-Vila  1 , Joan Navarro  2 , Roger Mallol  1
Affiliations

CloMet: A Novel Open-Source and Modular Software Platform That Connects Established Metabolomics Repositories and Data Analysis Resources

Jordi Rodeiro et al. J Proteome Res. .

Abstract

The field of metabolomics has witnessed the development of hundreds of computational tools, but only a few have become cornerstones of this field. While MetaboLights and Metabolomics Workbench are two well-established data repositories for metabolomics data sets, Workflows4Metabolomics and MetaboAnalyst are two well-established web-based data analysis platforms for metabolomics. Yet, the raw data stored in the aforementioned repositories lack standardization in terms of the file system format used to store the associated acquisition files. Consequently, it is not straightforward to reuse available data sets as input data in the above-mentioned data analysis resources, especially for non-expert users. This paper presents CloMet, a novel open-source modular software platform that contributes to standardization, reusability, and reproducibility in the metabolomics field. CloMet, which is available through a Docker file, converts raw and NMR-based metabolomics data from MetaboLights and Metabolomics Workbench to a file format that can be used directly either in MetaboAnalyst or in Workflows4Metabolomics. We validated both CloMet and the output data using data sets from these repositories. Overall, CloMet fills the gap between well-established data repositories and web-based statistical platforms and contributes to the consolidation of a data-driven perspective of the metabolomics field by leveraging and connecting existing data and resources.

Keywords: NMR; data analysis; data mining; data sharing; databases; metabolomics.

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Conflict of interest statement

The authors declare no competing financial interest.

Figures

Figure 1
Figure 1
Untargeted metabolomics workflow.
Figure 2
Figure 2
General scheme of CloMet inputs, processes, and outputs.
Figure 3
Figure 3
Analysis of established metabolomics data repositories.
Figure 4
Figure 4
Custom standard data format. The left diagram shows the general structure of any study. The right diagram shows an example of a processed study with id MTBL326.
Figure 5
Figure 5
(A) MetaboAnalyst and (B) Workflow4Metabolomics csv formats.
Figure 6
Figure 6
Step-by-step guide to install Docker for the first time and run CloMet.
Figure 7
Figure 7
CloMet graphical user interface.
Figure 8
Figure 8
Validation results.
See this image and copyright information in PMC

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