arrow
Return

TraceMetrix: a traceable metabolomics interactive analysis platform

delete2025-10-01
delete0
delete
OA
AI
谌伟 (Wei Chen)
安艳捧 (Yanpeng An)
Z
Ziru Chen
R
Ruijin Luo
Q
Qinwei Lu
李聪 cover
李聪 (Cong Li)
C
Chenhan Zhang
Q
Qingxia Huang
X
Xiaoxuan Yi
李逸平 (Yixue Li) *
H
Huiru Tang
张国庆 (Guoqing Zhang)
DOI:10.1186/s13321-025-01095-0delete
deleteOriginal
deleteShare
deleteSave
View PDF
Abstract

Abstract

En 中文
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 . TraceMetrix introduces a novel web-based platform for metabolomics data analysis, offering interactive traceability that ensures comprehensive tracking of the entire analysis process. Unlike existing tools, TraceMetrix enables traceability of data files, processes (analysis methods), and parameters through efficient data management, significantly enhancing transparency and reproducibility. Additionally, by deploying on high-performance computing clusters, it addresses the challenges of large-scale metabolomics data analysis.
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Journal of Cheminformatics cover
Journal of Cheminformatics
IF:
5.7
Papers:
1.5K
Citations:
1.1W

Organization

S
shanghai southgene technology co., ltd.
Scholars:
1
Papers: 1
Citations: 0
F
fudan university
Scholars:
11.6W
Papers: 7.7W
Citations: 121
G
guangzhou national laboratory
Scholars:
504
Papers: 192
Citations: 0
C
chinese academy of sciences
Scholars:
55.9W
Papers: 44.7W
Citations: 704
researcher View more organizations