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A PLSPM-Based Test Statistic for Detecting Gene-Gene Co-Association in Genome-Wide Association Study with Case-Control Design

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  • Xiaoshuai Zhang
  • Xiaowei Yang
  • Zhongshang Yuan
  • Yanxun Liu
  • Fangyu Li
  • Bin Peng
  • Dianwen Zhu
  • Jinghua Zhao
  • Fuzhong Xue

Abstract

: For genome-wide association data analysis, two genes in any pathway, two SNPs in the two linked gene regions respectively or in the two linked exons respectively within one gene are often correlated with each other. We therefore proposed the concept of gene-gene co-association, which refers to the effects not only due to the traditional interaction under nearly independent condition but the correlation between two genes. Furthermore, we constructed a novel statistic for detecting gene-gene co-association based on Partial Least Squares Path Modeling (PLSPM). Through simulation, the relationship between traditional interaction and co-association was highlighted under three different types of co-association. Both simulation and real data analysis demonstrated that the proposed PLSPM-based statistic has better performance than single SNP-based logistic model, PCA-based logistic model, and other gene-based methods.

Suggested Citation

  • Xiaoshuai Zhang & Xiaowei Yang & Zhongshang Yuan & Yanxun Liu & Fangyu Li & Bin Peng & Dianwen Zhu & Jinghua Zhao & Fuzhong Xue, 2013. "A PLSPM-Based Test Statistic for Detecting Gene-Gene Co-Association in Genome-Wide Association Study with Case-Control Design," PLOS ONE, Public Library of Science, vol. 8(4), pages 1-8, April.
    • Handle: RePEc:plo:pone00:0062129
    DOI: 10.1371/journal.pone.0062129
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    References listed on IDEAS

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    1. David E. Reich & Michele Cargill & Stacey Bolk & James Ireland & Pardis C. Sabeti & Daniel J. Richter & Thomas Lavery & Rose Kouyoumjian & Shelli F. Farhadian & Ryk Ward & Eric S. Lander, 2001. "Linkage disequilibrium in the human genome," Nature, Nature, vol. 411(6834), pages 199-204, May.
    2. Fuzhong Xue & Shengxu Li & Jian'an Luan & Zhongshang Yuan & Robert N Luben & Kay-Tee Khaw & Nicholas J Wareham & Ruth J F Loos & Jing Hua Zhao, 2012. "A Latent Variable Partial Least Squares Path Modeling Approach to Regional Association and Polygenic Effect with Applications to a Human Obesity Study," PLOS ONE, Public Library of Science, vol. 7(2), pages 1-10, February.
    3. Tenenhaus, Michel & Vinzi, Vincenzo Esposito & Chatelin, Yves-Marie & Lauro, Carlo, 2005. "PLS path modeling," Computational Statistics & Data Analysis, Elsevier, vol. 48(1), pages 159-205, January.
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    Cited by:

    1. Emily Mathieu, 2016. "AGGrEGATOr: A Gene-based GEne-Gene interActTiOn test for case-control association studies," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 15(2), pages 151-171, April.

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