Expression ratio statistics and its applications to microarray data analysis

Yidong Chen; Vishnu G. Kamat; Edward R. Dougherty; Michael L. Bittner; Paul S. Meltzer; Jeffrey M. Trent

doi:10.1117/12.380505

22 March 2000 Expression ratio statistics and its applications to microarray data analysis

Yidong Chen, Vishnu G. Kamat, Edward R. Dougherty, Michael L. Bittner, Paul S. Meltzer, Jeffrey M. Trent

Proceedings Volume 3926, Advances in Nucleic Acid and Protein Analyses, Manipulation, and Sequencing; (2000) https://doi.org/10.1117/12.380505
Event: BiOS 2000 The International Symposium on Biomedical Optics, 2000, San Jose, CA, United States

Abstract

Microarray technology makes it possible to monitor expression levels of thousands of genes simultaneously during single or multiple experiments. Routinely, in order to analyze gene expressions level quantitatively, two fluorescent-labeled RNAs are hybridized to an array of cDNA probes on a glass slide. Ratios of gene expression levels arising from two co-hybridized samples are obtained through image segmentation and signal detection methods. During the past three years, we have developed a gene expression analysis system in which ratio statistics have been applied to expression analysis, and a ratio confidence interval has been established to identify ratio outliers.

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Yidong Chen, Vishnu G. Kamat, Edward R. Dougherty, Michael L. Bittner, Paul S. Meltzer, and Jeffrey M. Trent "Expression ratio statistics and its applications to microarray data analysis", Proc. SPIE 3926, Advances in Nucleic Acid and Protein Analyses, Manipulation, and Sequencing, (22 March 2000); https://doi.org/10.1117/12.380505

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KEYWORDS

Signal to noise ratio

Statistical analysis

Data analysis

Monte Carlo methods

Target detection

Biological research

Glasses

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