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Related Experiment Video

Updated: Oct 4, 2025

Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis

Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis

Published on: November 10, 2023

metaboprep: an R package for preanalysis data description and processing.

David A Hughes^1,2, Kurt Taylor^1,2, Nancy McBride^1,2,3

¹MRC Integrative Epidemiology Unit at the University of Bristol, Bristol BS8 1TH, UK.

Bioinformatics (Oxford, England)

|February 8, 2022

Summary

This summary is machine-generated.

This study introduces metaboprep, an R package for standardized metabolomics data processing. It aids researchers in characterizing and cleaning metabolomics datasets for improved health research quality.

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Area of Science:

Biomedical research
Metabolomics
Data science

Background:

Metabolomics is vital in health research but lacks standardized preanalytical data processing.
Current methods for data characterization and error exclusion lack standardization and transparency.

Purpose of the Study:

To introduce metaboprep, a standardized workflow for metabolomics data processing.
To enhance the quality and characterization of metabolomics datasets.
To promote transparency in data preprocessing procedures.

Main Methods:

Development of metaboprep, an open-source R package.
Implementation of a standardized workflow for data extraction and quality assessment.
Generation of reports detailing quality metrics and batch variable influences.

Main Results:

metaboprep facilitates the extraction and characterization of high-quality metabolomics data.
The package enables users to select samples and metabolites based on defined quality metrics.
Standardized reporting of quality metrics and batch effects is generated for transparency.

Conclusions:

metaboprep offers a standardized, transparent, and flexible solution for metabolomics data preprocessing.
The R package improves the reliability and reproducibility of metabolomics studies.
Adoption of metaboprep can advance health research through better data quality.