ArticleNature protocols2021
Statistical analysis in metabolic phenotyping.
Article in Nature protocols, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
47 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A priori sample size determination and power analysis in metabolic phenotyping and integrative metabolomics: an application framework based on a systematic review of literature.Metabolomics : Official journal of the Metabolomic Society · 2026Pooled it
- Metabolite Fraction Libraries for Quantitative NMR Metabolomics.Analytical chemistry · 2026Article
- Longitudinal and Stability-Aware Analysis Reveals Treatment-Specific MicroRNA Response Signatures Following Immune-Reconstitution and B-Cell-Targeted Therapies in Multiple Sclerosis.International journal of molecular sciences · 2026Article
- Obesity and insulin resistance trigger the early onset of adolescent-like sexually dimorphic metabotypes in middle childhood.Cardiovascular diabetology · 2026Article
- Responses and adaptations of plants to abiotic stress: transcriptional regulation of secondary metabolic pathways, metabolomics, and nanobiological approaches.Frontiers in genetics · 2026Review
- Applications of Metabolomics in the Development of Biomedicine and Biotechnology.Advances in experimental medicine and biology · 2026Review
- Metabolite Fraction Libraries for Quantitative NMR Metabolomics.bioRxiv : the preprint server for biology · 2025Article
- Insulin resistance as a potential driving force of parental obesity-induced adverse metabolic programming mechanisms in children with obesity.BMC medicine · 2025Article
- COLMAR1d2d: Synergistic Combination of 1D with 2D NMR for Enhanced High-Throughput Identification and Quantification of Metabolites in Complex Mixtures.Analytical chemistry · 2025Article
- Unveiling cellular changes in leukaemia cell lines after cannabidiol treatment through lipidomics.Scientific reports · 2025Article
- Integrated metabolomics and metagenomics reveal plant-microbe interactions driving aroma differentiation in flue-cured tobacco leaves.Frontiers in plant science · 2025Article
- NMR-Based Stable Isotope Tracing of Cancer Metabolism.Methods in molecular biology (Clifton, N.J.) · 2025Article
- A comprehensive review on computational metabolomics: Advancing multiscale analysis throughComputational and structural biotechnology journal · 2025Review
- Longitudinal Metabolomics Data Analysis Informed by Mechanistic Models.Metabolites · 2024Article
- Presenting metabolomics analyses: what's in a number?The EMBO journal · 2024Article
- Probing erythrocytes as sensitive and reliable sensors of metabolic disturbances in the crosstalk between childhood obesity and insulin resistance: findings from an observational study, in vivo challenge tests, and ex vivo incubation assays.Cardiovascular diabetology · 2024Observational
- Using matrix assisted laser desorption ionisation mass spectrometry combined with machine learning for vaccine authenticity screening.NPJ vaccines · 2024Article
- Identifying metabotypes of insulin resistance severity in children with metabolic syndrome.Cardiovascular diabetology · 2024Article
- SERSomes for metabolic phenotyping and prostate cancer diagnosis.Cell reports. Medicine · 2024Article
- Serum Levels of Adiponectin Are Strongly Associated with Lipoprotein Subclasses in Healthy Volunteers but Not in Patients with Metabolic Syndrome.International journal of molecular sciences · 2024Article
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
Metabolic phenotyping is an important tool in translational biomedical research. The advanced analytical technologies commonly used for phenotyping, including mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy, generate complex data requiring tailored statistical analysis methods. Detailed protocols have been published for data acquisition by liquid NMR, solid-state NMR, ultra-performance liquid chromatography (LC-)MS and gas chromatography (GC-)MS on biofluids or tissues and their preprocessing. Here we propose an efficient protocol (guidelines and software) for statistical analysis of metabolic data generated by these methods. Code for all steps is provided, and no prior coding skill is necessary. We offer efficient solutions for the different steps required within the complete phenotyping data analytics workflow: scaling, normalization, outlier detection, multivariate analysis to explore and model study-related effects, selection of candidate biomarkers, validation, multiple testing correction and performance evaluation of statistical models. We also provide a statistical power calculation algorithm and safeguards to ensure robust and meaningful experimental designs that deliver reliable results. We exemplify the protocol with a two-group classification study and data from an epidemiological cohort; however, the protocol can be easily modified to cover a wider range of experimental designs or incorporate different modeling approaches. This protocol describes a minimal set of analyses needed to rigorously investigate typical datasets encountered in metabolic phenotyping.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.