Cited by 30Advanced Proteomics Techniques and ApplicationsMetabolomics and Mass Spectrometry StudiesGene expression and cancer classification

Transformation, normalization, and batch effect in the analysis of mass spectrometry data for omics studies,

Open access
Mertens, Bart J. A.·2017·Statistical Analysis of Proteomics, Metabolomics, and Lipidomics Data Using Mass Spectrometry

Integrity signals

Registry

Crossref · 10.1007/978-3-319-45809-0_1

Cites

21 of 21 references verified0 citation errors · 0 not checkable

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  • Batch effects are common and often much more pronounced in mass spectrometry-based data, even when the same physical instrument is used and the same data type is being generated.

    “For example, batch effects are common and often much more pronounced in mass spectrometry-based data (Mertens, 2016; Phua et al., 2022; e.g., Han and Li, 2020), even when the same physical instrument is used and the same data type is being generated.”

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Authors
Mertens, B. J. A.
Affiliations
Leiden University Medical Center (NL)
Corresponding author
Mertens, Bart J. A.
Venue
Statistical Analysis of Proteomics, Metabolomics, and Lipidomics Data Using Mass Spectrometry
Published
2016-12-16
Pages
1-21
OpenAlex
W2431351132
Cited by
30
References
21
Citations by year
2026: 3 · 2025: 6 · 2023: 4 · 2022: 3 · 2021: 3 · 2020: 5 · 2019: 2 · 2018: 2 · 2016: 2
FWCI
5.66
Type
book chapter
Language
en
Open access
Locations
  • Springer eBooks (publishedVersion)
  • arXiv (Cornell University) (publishedVersion)
  • arXiv (Cornell University)
Topics
  • Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Metabolomics and Mass Spectrometry Studies
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
Keywords
data transformation, normalization, batch effects, mass spectrometry data, omics data analysis, proteomics, metabolomics, data preprocessing

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

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