ArticleStatistics in medicine2021
Pathway testing for longitudinal metabolomics.
Article in Statistics in medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Bayesian functional analysis for untargeted metabolomics data with matching uncertainty and small sample sizes.Briefings in bioinformatics · 2024Article
- Article
- Metapone: a Bioconductor package for joint pathway testing for untargeted metabolomics data.Bioinformatics (Oxford, England) · 2022Article
- Penalized regression calibration: A method for the prediction of survival outcomes using complex longitudinal and high-dimensional data.Statistics in medicine · 2021Observational
- Pathway testing for longitudinal metabolomics.Statistics in medicine · 2021Article
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Authors and funding
4 authors.
Funding
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Abstract
We propose a top-down approach for pathway analysis of longitudinal metabolite data. We apply a score test based on a shared latent process mixed model which can identify pathways with differentially progressing metabolites. The strength of our approach is that it can handle unbalanced designs, deals with potential missing values in the longitudinal markers, and gives valid results even with small sample sizes. Contrary to bottom-up approaches, correlations between metabolites are explicitly modeled leveraging power gains. For large pathway sizes, a computationally efficient solution is proposed based on pseudo-likelihood methodology. We demonstrate the advantages of the proposed method in identification of differentially expressed pathways through simulation studies. Finally, longitudinal metabolite data from a mice experiment is analyzed to demonstrate our methodology.
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Registered trials
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