Noise Analysis of Duplicated Data on Microarrays
Using Mixture Distribution Modeling

Masaru Takeya, Takehiro Matsuda
, Masao Iwamoto,
Norimichi Tsumura, Toshiya Nakaguchi, and Yoichi MiyakeP

Division of Genome and Biodiversity ResearchT,
National Institute of Agrobiological Sciences,
2-1-2 Kannondai, Tsukuba, Ibaraki 305-8602, Japan


Graduate School of Science and Technology, Chiba University,
1-33 Yayoi-cho, Inage-ku, Chiba 263-8522, Japan


Division of Plant SciencesT, National Institute of Agrobiological Sciences,
2-1-2 Kannondai, Tsukuba, Ibaraki 305-8602, Japan

OPTICAL REVIEW Vol.14, No.2, pp.97-104(2007). @

Abstract
We propose a technique for estimating gene expression values for duplicated data on cDNA microarrays. In the scatter plots, the distribution is constructed from a mixture of normal two-dimensional distributions, which represent fluctuations in gene expression values due to noise. An EM algorithm is used for estimating the modeling parameters. The probability that duplicated data is shifted by noise is calculated using Bayesian estimation. Six data sets of rice cDNA microarray assays were used to test the proposed technique. Genes in the data sets were subjected to clustering based on probability of true value. Clustering successfully identified candidate genes regulated by circadian rhythms in rice.

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