A Review on Differential Abundance Analysis Methods for Mass Spectrometry-Based Metabolomic Data

Zhengyan Huang, Chi Wang

Research output: Contribution to journalReview articlepeer-review

3 Scopus citations

Abstract

This review presents an overview of the statistical methods on differential abundance (DA) analysis for mass spectrometry (MS)-based metabolomic data. MS has been widely used for metabolomic abundance profiling in biological samples. The high-throughput data produced by MS often contain a large fraction of zero values caused by the absence of certain metabolites and the technical detection limits of MS. Various statistical methods have been developed to characterize the zero-inflated metabolomic data and perform DA analysis, ranging from simple tests to more complex models including parametric, semi-parametric, and non-parametric approaches. In this article, we discuss and compare DA analysis methods regarding their assumptions and statistical modeling techniques.

Original languageEnglish
Article number305
JournalMetabolites
Volume12
Issue number4
DOIs
StatePublished - Apr 2022

Bibliographical note

Publisher Copyright:
© 2022 by the authors. Licensee MDPI, Basel, Switzerland.

Keywords

  • differential abundance
  • mass spectrometry
  • metabolomics
  • zero-inflated data

ASJC Scopus subject areas

  • Endocrinology, Diabetes and Metabolism
  • Biochemistry
  • Molecular Biology

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