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International Workshop on Health Intelligence

W3PHAI 2019: Precision Health and Medicine pp 193–197Cite as

Practical Evaluation of Different Omics Data Integration Methods

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 843))

Abstract

Identification of meaningful connections from different types of omics data sets is extremely important in computational biology and system biology. Integration of multi-omics data is the first essential step for data analysis, but it is also challenging for the systems biologists to correctly integrate different data together. Practical comparison of different omics data integration methods can provide biomedical researchers a clear view of how to select appropriate methods and tools to integrate and analyze different multi-omics datasets. Here we illustrate two widely used R-based omic data integration tools: mixOmics and STATegRa, to analyze different types of omics data sets and evaluate their performance.

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Acknowledgements

H.G. is partially supported by the NIH grant 1R15GM129696-01A1 and Australian National University; T.-H.A is supported by NSF CRII-156629, NSF-1564894, and Saint Louis University President’s Research Fund (PRF).

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Authors and Affiliations

  1. Program in Bioinformatics and Computational Biology, Saint Louis University, St. Louis, MO, 63103, USA

    Wenjia Feng, Haijun Gong & Tae-Hyuk Ahn

  2. Research School of Finance, Actuarial Studies and Statistics, Australian National University, Acton, ACT, 2601, Australia

    Zekun Yu & Haijun Gong

  3. Department of Computer Science, Kennesaw State University, Marietta, GA, USA

    Mingon Kang

  4. Department of Mathematics and Statistics, Saint Louis University, St. Louis, MO, 63103, USA

    Haijun Gong

  5. Department of Computer Science, Saint Louis University, St. Louis, MO, 63103, USA

    Tae-Hyuk Ahn

Authors
  1. Wenjia Feng
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  2. Zekun Yu
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  3. Mingon Kang
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  4. Haijun Gong
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  5. Tae-Hyuk Ahn
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Corresponding author

Correspondence to Tae-Hyuk Ahn .

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Editors and Affiliations

  1. Department of Pediatrics, The University of Tennessee Health Science Center – Oak-Ridge National Lab (UTHSC-ORNL) Center for Biomedical Informatics, Memphis, TN, USA

    Arash Shaban-Nejad

  2. School of Nursing, University of Minnesota, Minneapolis, MN, USA

    Martin Michalowski

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Feng, W., Yu, Z., Kang, M., Gong, H., Ahn, TH. (2020). Practical Evaluation of Different Omics Data Integration Methods. In: Shaban-Nejad, A., Michalowski, M. (eds) Precision Health and Medicine. W3PHAI 2019. Studies in Computational Intelligence, vol 843. Springer, Cham. https://doi.org/10.1007/978-3-030-24409-5_20

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