Application of random matrix theory to microarray data for discovering functional gene modules

Feng Luo, Jianxin Zhong, Yunfeng Yang, and Jizhong Zhou

Phys. Rev. E 73, 031924 – Published 29 March 2006

Abstract

We show that spectral fluctuation of coexpression correlation matrices of yeast gene microarray profiles follows the description of the Gaussian orthogonal ensemble (GOE) of the random matrix theory (RMT) and removal of small values of the correlation coefficients results in a transition from the GOE statistics to the Poisson statistics of the RMT. This transition is directly related to the structural change of the gene expression network from a global network to a network of isolated modules.

Received 9 June 2005

DOI:https://doi.org/10.1103/PhysRevE.73.031924

Authors & Affiliations

Feng Luo¹, Jianxin Zhong^2,3,*, Yunfeng Yang⁴, and Jizhong Zhou^4,5,†

¹Department of Computer Science, Clemson University, 100 McAdams Hall, Clemson, South Carolina 29634, USA
²Department of Physics, Xiangtan University, Hunan 411105, China
³Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, USA
⁴Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, USA
⁵Department of Botany and Microbiology, University of Oklahoma, Norman, Oklahoma 73019, USA

^*Corresponding authors. Electronic address: zhongjn@ornl.gov
^†Electronic address: zhouj@ornl.gov

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Vol. 73, Iss. 3 — March 2006

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Physical Review E

covering statistical, nonlinear, biological, and soft matter physics