• Corpus ID: 3436138

Statistical Methods and Workflow for Analyzing Human Metabolomics Data.

@article{Antonelli2017StatisticalMA,
  title={Statistical Methods and Workflow for Analyzing Human Metabolomics Data.},
  author={Joseph Antonelli and Brian Lee Claggett and Mir Henglin and Jeramie D. Watrous and Kim Lehmann and Pavel Hushcha and Olga V. Demler and Samia Mora and Teemu J. Niiranen and Alexandre C. Pereira and Mohit M. Jain and Susan Cheng},
  journal={arXiv: Quantitative Methods},
  year={2017}
}
High-throughput metabolomics investigations, when conducted in large human cohorts, represent a potentially powerful tool for elucidating the biochemical diversity and mechanisms underlying human health and disease. Large-scale metabolomics data, generated using targeted or nontargeted platforms, are increasingly more common. Appropriate statistical analysis of these complex high-dimensional data is critical for extracting meaningful results from such large-scale human metabolomics studies… 

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