Model-based analysis of microarray data: Exploration of differentially expressed genes between two cell types based on a two-dimensional mixed normal model

Megu Ohtaki; Keiko Otani; Kenichi Satoh; Toshihiko Kawamura; Keiko Hiyama; Masahiko Nishiyama

doi:10.5691/jjb.26.31

Preliminary Report

Model-based analysis of microarray data: Exploration of differentially expressed genes between two cell types based on a two-dimensional mixed normal model

Megu Ohtaki, Keiko Otani, Kenichi Satoh, Toshihiko Kawamura, Keiko Hiyama, Masahiko Nishiyama

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Keywords: cDNA microarray, Empirical Bayes, Gene Expression, Mixed Normal Distribution, Normalization, Oligonucleotide microarray

JOURNAL FREE ACCESS

2005 Volume 26 Issue 1 Pages 31-48

DOI https://doi.org/10.5691/jjb.26.31

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Abstract

Inference on gene expression change between two different samples is considered. We develop a mathematical model assuming that there exist two different functional states of a gene: “ON” and “OFF” . Each measured sample-specific gene expression intensity is described by an additive model, which accounts for fluctuations in absolute gene expression intensity and measurement error, to which a two-dimensional mixed normal model with four components considering the joint distribution of the sample “sum” and “difference” is approximated. We can successfully identify genes that are differentially expressed between two samples using posterior probabilities, while avoiding declaring false differences. The proposed methods are applicable to cDNA microarray data with two fluorescent dyes and to oligonucleotide data.

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