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MetabNet: An R Package for Metabolic Association Analysis of High-Resolution Metabolomics Data.

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Last modified
  • 02/20/2025
Type of Material
Authors
    Karan Uppal, Emory UniversityQuinlyn A. Soltow, Emory UniversityDaniel E. L. Promislow, University of WashingtonLynn M. Wachtman, Harvard UniversityArshed Ali Quyyumi, Emory UniversityDean P Jones, Emory University
Language
  • English
Date
  • 2015
Publisher
  • Frontiers
Publication Version
Copyright Statement
  • © 2015 Uppal, Soltow, Promislow, Wachtman, Quyyumi and Jones.
License
Final Published Version (URL)
Title of Journal or Parent Work
ISSN
  • 2296-4185
Volume
  • 3
Start Page
  • 87
End Page
  • 87
Grant/Funding Information
  • This research was supported by AG038746, HL113451, ES019116, HHSN272201200031C, NIH R21 ES025632, and additional resources provided by Emory University.
Supplemental Material (URL)
Abstract
  • Liquid-chromatography high-resolution mass spectrometry provides capability to measure >40,000 ions derived from metabolites in biologic samples. This presents challenges to confirm identities of known chemicals and delineate potential metabolic pathway associations of unidentified chemicals. We provide an R package for metabolic network analysis, MetabNet, to perform targeted metabolome-wide association study of specific metabolites to facilitate detection of their related metabolic pathways and network structures.
Author Notes
Keywords
Research Categories
  • Health Sciences, Medicine and Surgery
  • Biology, Biostatistics

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