Data Processing and Analysis in Liquid Chromatography–Mass Spectrometry-Based Targeted Metabolomics

Masahiro Sugimoto, Yumi Aizawa, Atsumi Tomita

Research output: Chapter in Book/Report/Conference proceedingChapter


Mass spectrometry (MS)-based metabolomics provides high-dimensional datasets; that is, the data include various metabolite features. Data analysis begins by converting the raw data obtained from the MS to produce a data matrix (metabolite × concentrations). This is followed by several steps, such as peak integration, alignment of multiple data, metabolite identification, and calculation of metabolite concentrations. Each step yields the analytical results and the accompanying information used for the quality assessment of the anterior steps. Thus, the measurement quality can be analyzed through data processing. Here, we introduce a typical data processing procedure and describe a method to utilize the intermediate data as quality control. Subsequently, commonly used data analysis methods for metabolomics data, such as statistical analyses, are also introduced.

Original languageEnglish
Title of host publicationMethods in Molecular Biology
PublisherHumana Press Inc.
Number of pages15
Publication statusPublished - 2023
Externally publishedYes

Publication series

NameMethods in Molecular Biology
ISSN (Print)1064-3745
ISSN (Electronic)1940-6029


  • Data processing
  • Mass spectrometry
  • Multivariate analysis
  • Statistical analysis

ASJC Scopus subject areas

  • Molecular Biology
  • Genetics


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