Statistical Techniques for Microarray Technology
Bindu Punathumparambath, Sebastian George, V. Kannan
Abstract
Bindu Punathumparambath, Sebastian George, V. Kannan
Abstract
Microarray technology enable researchers to measure the expression levels for thousands of genes simultaneously. This paper describes the microarray technology and general methodology for the analysis of differential gene expression data from microarray experiments. First, we will provide a review of basic microarray concepts and an overview of some of the major statistical developments in microarray data analysis. In this work, we propose the two component Mixed Gaussian distribution as an approximation for the log-ratios of the measured gene expression across genes.
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Microarray technology enable researchers to measure the expression levels for thousands of genes simultaneously. This paper describes the microarray technology and general methodology for the analysis of differential gene expression data from microarray experiments. First, we will provide a review of basic microarray concepts and an overview of some of the major statistical developments in microarray data analysis. In this work, we propose the two component Mixed Gaussian distribution as an approximation for the log-ratios of the measured gene expression across genes.
Key concepts: Microarray databases, Gene chip analysis, Microarray analysis techniques, Microarray, Computer science, Data mining, Gaussian, Expression (computer science)