TraceMetrix: a traceable metabolomics interactive analysis platform.

Chen, W; An, Y; Chen, Z; Luo, R; Lu, Q; Li, C; Zhang, C; Huang, Q; Chen, Q; Zhang, L; Yi, X; Li, Y; Tang, H; Zhang, G

TraceMetrix: a traceable metabolomics interactive analysis platform.

Chen, W An, Y Chen, Z Luo, R Lu, Q Li, C Zhang, C

Huang, Q Chen, Q Zhang, L Yi, X Li, Y Tang, H Zhang, G

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Publisher:: BMC
Publication Type:: Journal Article
Citation:: J Cheminform, 2025, 17, (1), pp. 148
Issue Date:: 2025-09-29

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Field	Value	Language
dc.contributor.author	Chen, W
dc.contributor.author	An, Y
dc.contributor.author	Chen, Z
dc.contributor.author	Luo, R
dc.contributor.author	Lu, Q
dc.contributor.author	Li, C
dc.contributor.author	Zhang, C https://orcid.org/0000-0002-2352-0485
dc.contributor.author	Huang, Q
dc.contributor.author	Chen, Q
dc.contributor.author	Zhang, L
dc.contributor.author	Yi, X
dc.contributor.author	Li, Y
dc.contributor.author	Tang, H
dc.contributor.author	Zhang, G
dc.date.accessioned	2025-12-18T23:59:34Z
dc.date.available	2025-09-08
dc.date.available	2025-12-18T23:59:34Z
dc.date.issued	2025-09-29
dc.identifier.citation	J Cheminform, 2025, 17, (1), pp. 148
dc.identifier.issn	1758-2946
dc.identifier.issn	1758-2946
dc.identifier.uri	http://hdl.handle.net/10453/191005
dc.description.abstract	Metabolomics data analysis is a multifaceted process often constrained by limited data sharing and a lack of transparency, which hinders reproducibility of results. While existing bioinformatics tools address some of these challenges, achieving greater simplicity and operational clarity remains essential for fully leveraging the potential of metabolomics. Here, we introduce TraceMetrix, a web-based platform designed for interactive traceability in metabolomics data analysis. TraceMetrix provides a flexible management system for both raw and derived data, enabling comprehensive tracking of file origins and destinations throughout the whole analysis pipeline. The platform documents the software and parameters used across four key modules, from raw data preprocessing, data cleaning, statistical analysis to functional analysis, enabling users to easily track critical factors influencing result accuracy. By mapping upstream and downstream relationships for nearly 19 analytical functions, TraceMetrix ensures end-to-end traceability, viewable interactively online or exportable as detailed reports. To address the limitations of single-machine environments in processing large-scale datasets, TraceMetrix is deployed on a high-performance computing cluster for efficient batch processing. Using a non-targeted metabolomics dataset, we demonstrated its traceability function to optimize parameter selection, successfully reproducing the analysis process and validating the original study's findings. TraceMetrix integrates traceability across data, software, and processes, significantly enhancing reproducibility in metabolomics research. The platform supports diverse applications and is freely available at https://www.biosino.org/tracemetrix .
dc.format	Electronic
dc.language	eng
dc.publisher	BMC
dc.relation.ispartof	J Cheminform
dc.relation.isbasedon	10.1186/s13321-025-01095-0
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	0303 Macromolecular and Materials Chemistry
dc.subject.classification	3401 Analytical chemistry
dc.subject.classification	3403 Macromolecular and materials chemistry
dc.title	TraceMetrix: a traceable metabolomics interactive analysis platform.
dc.type	Journal Article
utslib.citation.volume	17
utslib.location.activity	England
utslib.for	0303 Macromolecular and Materials Chemistry
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
utslib.copyright.status	open_access	*
dc.rights.license	This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0). To view a copy of this license, visit https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.date.updated	2025-12-18T23:59:31Z
pubs.issue	1
pubs.publication-status	Published online
pubs.volume	17
utslib.citation.issue	1

Abstract:

Metabolomics data analysis is a multifaceted process often constrained by limited data sharing and a lack of transparency, which hinders reproducibility of results. While existing bioinformatics tools address some of these challenges, achieving greater simplicity and operational clarity remains essential for fully leveraging the potential of metabolomics. Here, we introduce TraceMetrix, a web-based platform designed for interactive traceability in metabolomics data analysis. TraceMetrix provides a flexible management system for both raw and derived data, enabling comprehensive tracking of file origins and destinations throughout the whole analysis pipeline. The platform documents the software and parameters used across four key modules, from raw data preprocessing, data cleaning, statistical analysis to functional analysis, enabling users to easily track critical factors influencing result accuracy. By mapping upstream and downstream relationships for nearly 19 analytical functions, TraceMetrix ensures end-to-end traceability, viewable interactively online or exportable as detailed reports. To address the limitations of single-machine environments in processing large-scale datasets, TraceMetrix is deployed on a high-performance computing cluster for efficient batch processing. Using a non-targeted metabolomics dataset, we demonstrated its traceability function to optimize parameter selection, successfully reproducing the analysis process and validating the original study's findings. TraceMetrix integrates traceability across data, software, and processes, significantly enhancing reproducibility in metabolomics research. The platform supports diverse applications and is freely available at https://www.biosino.org/tracemetrix .

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http://hdl.handle.net/10453/191005