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Current data processing methods and reporting standards for untargeted analysis of volatile organic compounds using direct mass spectrometry: a systematic review

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journal contribution
posted on 2024-04-09, 12:55 authored by Kerry Rosenthal, MR Lindley, Matthew TurnerMatthew Turner, Elizabeth RatcliffeElizabeth Ratcliffe, Eugenie Hunsicker

Introduction

Untargeted direct mass spectrometric analysis of volatile organic compounds has many potential applications across fields such as healthcare and food safety. However, robust data processing protocols must be employed to ensure that research is replicable and practical applications can be realised. User-friendly data processing and statistical tools are becoming increasingly available; however, the use of these tools have neither been analysed, nor are they necessarily suited for every data type.

Objectives

This review aims to analyse data processing and analytic workflows currently in use and examine whether methodological reporting is sufficient to enable replication.

Methods

Studies identified from Web of Science and Scopus databases were systematically examined against the inclusion criteria. The experimental, data processing, and data analysis workflows were reviewed for the relevant studies.

Results

From 459 studies identified from the databases, a total of 110 met the inclusion criteria. Very few papers provided enough detail to allow all aspects of the methodology to be replicated accurately, with only three meeting previous guidelines for reporting experimental methods. A wide range of data processing methods were used, with only eight papers (7.3%) employing a largely similar workflow where direct comparability was achievable.

Conclusions

Standardised workflows and reporting systems need to be developed to ensure research in this area is replicable, comparable, and held to a high standard. Thus, allowing the wide-ranging potential applications to be realised.

History

School

  • Sport, Exercise and Health Sciences
  • Science
  • Aeronautical, Automotive, Chemical and Materials Engineering

Department

  • Chemistry
  • Mathematical Sciences
  • Chemical Engineering

Published in

Metabolomics

Volume

20

Issue

2

Publisher

Springer Nature

Version

  • VoR (Version of Record)

Rights holder

© The Author(s)

Publisher statement

This Open Access article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Acceptance date

2024-02-16

Publication date

2024-03-16

Copyright date

2024

ISSN

1573-3882

eISSN

1573-3890

Language

  • en

Depositor

Kerry Rosenthal. Deposit date: 5 April 2024

Article number

42