Statistical reporting of metabolomics data: experience from a high-throughput NMR platform and epidemiological applications

Stefan Mutter, Carrie Worden, Kara Paxton, Ville-Petteri Makinen

Research output: Contribution to journalArticle

Abstract

Introduction: Meta-analysis is the cornerstone of robust biomedical evidence. Objectives: We investigated whether statistical reporting practices facilitate metabolomics meta-analyses. Methods: A literature review of 44 studies that used a comparable platform. Results: Non-numeric formats were used in 31 studies. In half of the studies, less than a third of all measures were reported. Unadjusted P-values were missing from 12 studies and exact P-values from 9 studies. Conclusion: Reporting practices can be improved. We recommend (i) publishing all results as numbers, (ii) reporting effect sizes of all measured metabolites and (iii) always reporting unadjusted exact P-values.

LanguageEnglish
Article number5
JournalMetabolomics
Volume16
Issue number1
DOIs
Publication statusPublished - 1 Jan 2020

Keywords

  • Integration
  • Meta analysis
  • Metabolic profiles
  • NMR
  • Reporting
  • Summary statistics

ASJC Scopus subject areas

  • Endocrinology, Diabetes and Metabolism
  • Biochemistry
  • Clinical Biochemistry

Cite this

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Statistical reporting of metabolomics data : experience from a high-throughput NMR platform and epidemiological applications. / Mutter, Stefan; Worden, Carrie; Paxton, Kara; Makinen, Ville-Petteri.

In: Metabolomics, Vol. 16, No. 1, 5, 01.01.2020.

Research output: Contribution to journalArticle

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