JOURNAL OF SHANDONG UNIVERSITY (HEALTH SCIENCES) ›› 2013, Vol. 51 ›› Issue (11): 102-106.

• Articles • Previous Articles     Next Articles

Statistical inference for detecting gene-gene interaction on multiple quantitative  traits based on partial least squares path model

LI Fang-yu, YUAN Zhong-shang, ZHANG Xiao-shuai, XUE Fu-zhong   

  1. Department of Epidemiology and Biostatistics, School of Public Health, Shandong University, Jinan 250012, China
  • Received:2012-12-10 Online:2013-11-10 Published:2013-11-10

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Abstract:

Objective  To infer gene-gene interaction on multiple quantitative traits using partial least squares path model (PLSPM).  Methods   Simulation was used to evaluate the stability and power of the PLSPM-based statistic, which was further applied to identify the interaction between FTO gene and NEGR1 gene on related multiple quantitative traits in one real dataset. Results  The proposed PLSPM-based statistic was stable and its power increased with the increasing of sample size and interaction effect. The interaction of gene regions FTO (Chr16:52390317.. 52391106) and NEGR1 (Chr1:71707640.. 71709688) for correlated multiple quantitative traits showed statistical significance (P=0039). Conclusion  The proposed PLSPM-based statistic is powerful to detect gene-gene interaction for multiple quantitative traits.

Key words: Partial least squares path model; Interaction; Multiple quantitative traits

CLC Number: 

  • R195.1
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[2] LI Xiao, XUE Fu-zhong. Application of the geographically weighted regression model in  spatial genetic structure of the human population [J]. JOURNAL OF SHANDONG UNIVERSITY (HEALTH SCIENCES), 2011, 49(2): 119-124.
[3] LIU Baofeng 1， YUAN Changhai1， YU Jingmin2， QIN Jingzhu 1， GUO Li1，GENG Wenge3. Reliability and validity assessment of SF-36 in measuring quality of life of migrants from the Three Gorges Area [J]. JOURNAL OF SHANDONG UNIVERSITY (HEALTH SCIENCES), 2010, 48(7): 129-132.
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