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An Integrated Robust Graph Regularized Non-negative Matrix Factorization for Multi-dimensional Genomic Data Analysis

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Recent Advances in Data Science (IDMB 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1099))

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Abstract

With the generation of “multi-dimensional genomic data”, the multi-platform genomic analysis technology for simultaneous biological samples has been rapidly developed. However, the existing shortcomings of the models for comprehensive analysis of multi-dimensional genomic data are the lack of robustness. We use the integrated matrix factorization model by introducing L2,1-norm to deal with above problem. In this paper, we propose an Integrated Robust Graph Regularization Non-negative Matrix Factorization for multi-dimensional genomic data analysis which named iRGNMF. In the formulation of the objective function, we introduced the local structure to maintain regularization and L2,1-norm to consider the data geometry and model robustness. We also applied this model to three types of data of the same cancer from The Cancer Genome Atlas (TCGA). Experiments shown that iRGNMF has obtained considerable effects in sample clustering, and found suspicious disease genes, which are used to reveal hidden patterns and information of biology in multi-dimensional gene data.

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Acknowledgments

This work was supported in part by the NSFC under grant Nos. 61872220 and 61572284.

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Authors and Affiliations

  1. School of Information Science and Engineering, Qufu Normal University, Rizhao, 276826, China

    Yong-Jing Hao, Mi-Xiao Hou, Rong Zhu & Jin-Xing Liu

Authors
  1. Yong-Jing Hao
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  2. Mi-Xiao Hou
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  3. Rong Zhu
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  4. Jin-Xing Liu
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Corresponding author

Correspondence to Jin-Xing Liu .

Editor information

Editors and Affiliations

  1. Fordham University, New York, NY, USA

    Henry Han

  2. Guangxi University, Nanning, China

    Tie Wei

  3. Guangzhou University, Guangzhou, China

    Wenbin Liu

  4. Jiangsu University, Zhenjiang, China

    Fei Han

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Hao, YJ., Hou, MX., Zhu, R., Liu, JX. (2020). An Integrated Robust Graph Regularized Non-negative Matrix Factorization for Multi-dimensional Genomic Data Analysis. In: Han, H., Wei, T., Liu, W., Han, F. (eds) Recent Advances in Data Science. IDMB 2019. Communications in Computer and Information Science, vol 1099. Springer, Singapore. https://doi.org/10.1007/978-981-15-8760-3_7

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  • DOI: https://doi.org/10.1007/978-981-15-8760-3_7

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  • Print ISBN: 978-981-15-8759-7

  • Online ISBN: 978-981-15-8760-3

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