ArticleBioinformatics (Oxford, England)2021
Metabolite-Investigator: an integrated user-friendly workflow for metabolomics multi-study analysis.
Article in Bioinformatics (Oxford, England), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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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
4 citing papers in PubMed.
- EASY-FIA: A Readably Usable Standalone Tool for High-Resolution Mass Spectrometry Metabolomics Data Pre-Processing.Metabolites · 2022Article
- Hopomics:Metabolites · 2022Article
- Whole Blood Metabolite Profiles Reflect Changes in Energy Metabolism in Heart Failure.Metabolites · 2022Article
- New software tools, databases, and resources in metabolomics: updates from 2020.Metabolomics : Official journal of the Metabolomic Society · 2021Review
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
motivationMany diseases have a metabolic background, which is increasingly investigated due to improved measurement techniques allowing high-throughput assessment of metabolic features in several body fluids. Integrating data from multiple cohorts is of high importance to obtain robust and reproducible results. However, considerable variability across studies due to differences in sampling, measurement techniques and study populations needs to be accounted for.
resultsWe present Metabolite-Investigator, a scalable analysis workflow for quantitative metabolomics data from multiple studies. Our tool supports all aspects of data pre-processing including data integration, cleaning, transformation, batch analysis as well as multiple analysis methods including uni- and multivariable factor-metabolite associations, network analysis and factor prioritization in one or more cohorts. Moreover, it allows identifying critical interactions between cohorts and factors affecting metabolite levels and inferring a common covariate model, all via a graphical user interface. AVAILABILITY AND IMPLEMENTATION: We constructed Metabolite-Investigator as a free and open web-tool and stand-alone Shiny-app. It is hosted at https://apps.health-atlas.de/metabolite-investigator/, the source code is freely available at https://github.com/cfbeuchel/Metabolite-Investigator. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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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.