Mixed anova model analysis of microarray experiments with locally polled error

UNCW Author/Contributor (non-UNCW co-authors, if there are any, appear on document)
Yuan Liu (Creator)
The University of North Carolina Wilmington (UNCW )
Web Site: http://library.uncw.edu/

Abstract: The determination of a list of di®erentially expressed genes is a basic objective in many cDNA microarray experiments. Combining information across genes in the statistical analysis of microarray data is desirable because of relatively small number of data points obtained for each individual gene. Our LPE approach ¯nds a middle ground between global F test and gene-speci¯c F test by pooling the information across a group of genes that have similar variance estimates and shrinks the within- gene variance estimate towards an estimate including more genes. This method provides a powerful and robust approach to test di®erential expression of genes but does not su®er from biases of the global F test and low power of gene-speci¯c F test. In our approach the two-stage Mixed ANOVA model provides a conceptually and computationally e±cient means to analyze the microarray data.

Additional Information

A Thesis Submitted to the University of North Carolina at Wilmington in Partial Ful¯llment Of the Requirements for the Degree of Master of Arts
Language: English
Date: 2009
Gene expression--Data processing, Genomics--Data processing, Genomics--Mathematical models
Gene expression -- Data processing
Genomics -- Data processing
Genomics -- Mathematical models

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