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Pre-analytic Considerations for Mass Spectrometry-Based Untargeted Metabolomics Data.

ABSTRACT: Metabolomics is the science of characterizing and quantifying small molecule metabolites in biological systems. These metabolites give organisms their biochemical characteristics, providing a link between genotype, environment, and phenotype. With these opportunities also come data challenges, such as compound annotation, missing values, and batch effects. We present the steps of a general pipeline to process untargeted mass spectrometry data to alleviate the latter two challenges. We assume to have a matrix with metabolite abundances, with metabolites in rows and samples in columns. The steps in the pipeline include summarizing technical replicates (if available), filtering, imputing, transforming, and normalizing the data. In each of these steps, a method and parameters should be chosen based on assumptions one is willing to make, the question of interest, and diagnostic tools. Besides giving a general pipeline that can be adapted by the reader, our goal is to review diagnostic tools and criteria that are helpful when making decisions in each step of the pipeline and assessing the effectiveness of normalization and batch correction. We conclude by giving a list of useful packages and discuss some alternative approaches that might be more appropriate for the reader's data.

SUBMITTER: Reinhold D

PROVIDER: S-EPMC7346099 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Pre-analytic Considerations for Mass Spectrometry-Based Untargeted Metabolomics Data.

Reinhold Dominik D Pielke-Lombardo Harrison H Jacobson Sean S Ghosh Debashis D Kechris Katerina K

Methods in molecular biology (Clifton, N.J.) 20190101

Metabolomics is the science of characterizing and quantifying small molecule metabolites in biological systems. These metabolites give organisms their biochemical characteristics, providing a link between genotype, environment, and phenotype. With these opportunities also come data challenges, such as compound annotation, missing values, and batch effects. We present the steps of a general pipeline to process untargeted mass spectrometry data to alleviate the latter two challenges. We assume to ...[more]

PMID: 31119672

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Pre-analytic Considerations for Mass Spectrometry-Based Untargeted Metabolomics Data.

Publications

Pre-analytic Considerations for Mass Spectrometry-Based Untargeted Metabolomics Data.

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