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

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 frac...

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Main Authors: Zhengyan Huang, Chi Wang
Format: Article
Language:English
Published: MDPI AG 2022-03-01
Series:Metabolites
Subjects:
Online Access:https://www.mdpi.com/2218-1989/12/4/305
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author Zhengyan Huang
Chi Wang
author_facet Zhengyan Huang
Chi Wang
author_sort Zhengyan Huang
collection DOAJ
description 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.
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spelling doaj.art-ca8f5405c58f4c99b37c072dc64e44502023-11-30T21:31:56ZengMDPI AGMetabolites2218-19892022-03-0112430510.3390/metabo12040305A Review on Differential Abundance Analysis Methods for Mass Spectrometry-Based Metabolomic DataZhengyan Huang0Chi Wang1Everest Clinical Research Corporation, Little Falls, NJ 07424, USAMarkey Cancer Center, Department of Internal Medicine, University of Kentucky, Lexington, KY 40536, USAThis 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.https://www.mdpi.com/2218-1989/12/4/305differential abundancemass spectrometrymetabolomicszero-inflated data
spellingShingle Zhengyan Huang
Chi Wang
A Review on Differential Abundance Analysis Methods for Mass Spectrometry-Based Metabolomic Data
Metabolites
differential abundance
mass spectrometry
metabolomics
zero-inflated data
title A Review on Differential Abundance Analysis Methods for Mass Spectrometry-Based Metabolomic Data
title_full A Review on Differential Abundance Analysis Methods for Mass Spectrometry-Based Metabolomic Data
title_fullStr A Review on Differential Abundance Analysis Methods for Mass Spectrometry-Based Metabolomic Data
title_full_unstemmed A Review on Differential Abundance Analysis Methods for Mass Spectrometry-Based Metabolomic Data
title_short A Review on Differential Abundance Analysis Methods for Mass Spectrometry-Based Metabolomic Data
title_sort review on differential abundance analysis methods for mass spectrometry based metabolomic data
topic differential abundance
mass spectrometry
metabolomics
zero-inflated data
url https://www.mdpi.com/2218-1989/12/4/305
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