Literature DB >> 33889934

COMETS Analytics: An Online Tool for Analyzing and Meta-Analyzing Metabolomics Data in Large Research Consortia.

Marinella Temprosa, Steven C Moore, Krista A Zanetti, Nathan Appel, David Ruggieri, Kaitlyn M Mazzilli, Kai-Ling Chen, Rachel S Kelly, Jessica A Lasky-Su, Erikka Loftfield, Kathleen McClain, Brian Park, Laura Trijsburg, Oana A Zeleznik, Ewy A Mathé.   

Abstract

Consortium-based research is crucial for producing reliable, high-quality findings, but existing tools for consortium studies have important drawbacks with respect to data protection, ease of deployment, and analytical rigor. To address these concerns, we developed COnsortium of METabolomics Studies (COMETS) Analytics to support and streamline consortium-based analyses of metabolomics and other -omics data. The application requires no specialized expertise and can be run locally to guarantee data protection or through a Web-based server for convenience and speed. Unlike other Web-based tools, COMETS Analytics enables standardized analyses to be run across all cohorts, using an algorithmic, reproducible approach to diagnose, document, and fix model issues. This eliminates the time-consuming and potentially error-prone step of manually customizing models by cohort, helping to accelerate consortium-based projects and enhancing analytical reproducibility. We demonstrated that the application scales well by performing 2 data analyses in 45 cohort studies that together comprised measurements of 4,647 metabolites in up to 134,742 participants. COMETS Analytics performed well in this test, as judged by the minimal errors that analysts had in preparing data inputs and the successful execution of all models attempted. As metabolomics gathers momentum among biomedical and epidemiologic researchers, COMETS Analytics may be a useful tool for facilitating large-scale consortium-based research. © Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health 2021. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Entities:  

Keywords:  bioinformatics; data science; meta-analysis; metabolomics

Mesh:

Year:  2022        PMID: 33889934      PMCID: PMC8897993          DOI: 10.1093/aje/kwab120

Source DB:  PubMed          Journal:  Am J Epidemiol        ISSN: 0002-9262            Impact factor:   4.897


  40 in total

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5.  Metabolomics in epidemiology: sources of variability in metabolite measurements and implications.

Authors:  Joshua N Sampson; Simina M Boca; Xiao Ou Shu; Rachael Z Stolzenberg-Solomon; Charles E Matthews; Ann W Hsing; Yu Ting Tan; Bu-Tian Ji; Wong-Ho Chow; Qiuyin Cai; Da Ke Liu; Gong Yang; Yong Bing Xiang; Wei Zheng; Rashmi Sinha; Amanda J Cross; Steven C Moore
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2013-02-08       Impact factor: 4.254

6.  The Consortium of Metabolomics Studies (COMETS): Metabolomics in 47 Prospective Cohort Studies.

Authors:  Bing Yu; Krista A Zanetti; Marinella Temprosa; Demetrius Albanes; Nathan Appel; Clara Barrios Barrera; Yoav Ben-Shlomo; Eric Boerwinkle; Juan P Casas; Clary Clish; Caroline Dale; Abbas Dehghan; Andriy Derkach; A Heather Eliassen; Paul Elliott; Eoin Fahy; Christian Gieger; Marc J Gunter; Sei Harada; Tamara Harris; Deron R Herr; David Herrington; Joel N Hirschhorn; Elise Hoover; Ann W Hsing; Mattias Johansson; Rachel S Kelly; Chin Meng Khoo; Mika Kivimäki; Bruce S Kristal; Claudia Langenberg; Jessica Lasky-Su; Deborah A Lawlor; Luca A Lotta; Massimo Mangino; Loïc Le Marchand; Ewy Mathé; Charles E Matthews; Cristina Menni; Lorelei A Mucci; Rachel Murphy; Matej Oresic; Eric Orwoll; Jennifer Ose; Alexandre C Pereira; Mary C Playdon; Lucilla Poston; Jackie Price; Qibin Qi; Kathryn Rexrode; Adam Risch; Joshua Sampson; Wei Jie Seow; Howard D Sesso; Svati H Shah; Xiao-Ou Shu; Gordon C S Smith; Ulla Sovio; Victoria L Stevens; Rachael Stolzenberg-Solomon; Toru Takebayashi; Therese Tillin; Ruth Travis; Ioanna Tzoulaki; Cornelia M Ulrich; Ramachandran S Vasan; Mukesh Verma; Ying Wang; Nick J Wareham; Andrew Wong; Naji Younes; Hua Zhao; Wei Zheng; Steven C Moore
Journal:  Am J Epidemiol       Date:  2019-06-01       Impact factor: 4.897

7.  Human metabolic correlates of body mass index.

Authors:  Steven C Moore; Charles E Matthews; Joshua N Sampson; Rachael Z Stolzenberg-Solomon; Wei Zheng; Qiuyin Cai; Yu Ting Tan; Wong-Ho Chow; Bu-Tian Ji; Da Ke Liu; Qian Xiao; Simina M Boca; Michael F Leitzmann; Gong Yang; Yong Bing Xiang; Rashmi Sinha; Xiao Ou Shu; Amanda J Cross
Journal:  Metabolomics       Date:  2014-04-01       Impact factor: 4.290

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Journal:  Nat Med       Date:  2014-09-28       Impact factor: 53.440

9.  Identification of serum metabolites associated with risk of type 2 diabetes using a targeted metabolomic approach.

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Journal:  Diabetes       Date:  2012-10-04       Impact factor: 9.461

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Journal:  PLoS Med       Date:  2005-08-30       Impact factor: 11.613

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  1 in total

1.  Cross-Sectional Blood Metabolite Markers of Hypertension: A Multicohort Analysis of 44,306 Individuals from the COnsortium of METabolomics Studies.

Authors:  Panayiotis Louca; Ana Nogal; Aurélie Moskal; Neil J Goulding; Martin J Shipley; Taryn Alkis; Joni V Lindbohm; Jie Hu; Domagoj Kifer; Ni Wang; Bo Chawes; Kathryn M Rexrode; Yoav Ben-Shlomo; Mika Kivimaki; Rachel A Murphy; Bing Yu; Marc J Gunter; Karsten Suhre; Deborah A Lawlor; Massimo Mangino; Cristina Menni
Journal:  Metabolites       Date:  2022-06-28
  1 in total

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