ArticleFrontiers in molecular biosciences2022
An anchored experimental design and meta-analysis approach to address batch effects in large-scale metabolomics.
Article in Frontiers in molecular biosciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
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Who cites it
3 citing papers in PubMed, 4 citations in OpenAlex.
- A Taguchi Design of Experiments Approach for Untargeted Metabolomics Sample Preparation Optimization.Journal of biomolecular techniques : JBT · 2025Article
- Multiplatform untargeted metabolomics.Magnetic resonance in chemistry : MRC · 2023Review
- Unknown Metabolite Identification Using Machine Learning Collision Cross-Section Prediction and Tandem Mass Spectrometry.Analytical chemistry · 2023Article
Corrections and comments
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Authors and funding
13 authors at 5 institutions in 2 countries.
Funding
Abstract
Untargeted metabolomics studies are unbiased but identifying the same feature across studies is complicated by environmental variation, batch effects, and instrument variability. Ideally, several studies that assay the same set of metabolic features would be used to select recurring features to pursue for identification. Here, we developed an anchored experimental design. This generalizable approach enabled us to integrate three genetic studies consisting of 14 test strains of
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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 Socratic graph.