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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Format: | Article |
Language: | English |
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MDPI AG
2022-03-01
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Series: | Metabolites |
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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. |
first_indexed | 2024-03-09T13:19:48Z |
format | Article |
id | doaj.art-ca8f5405c58f4c99b37c072dc64e4450 |
institution | Directory Open Access Journal |
issn | 2218-1989 |
language | English |
last_indexed | 2024-03-09T13:19:48Z |
publishDate | 2022-03-01 |
publisher | MDPI AG |
record_format | Article |
series | Metabolites |
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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