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Activity Number:
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283
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Type:
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Contributed
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Date/Time:
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Wednesday, August 14, 2002 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Bayesian Stat. Sciences*
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| Abstract - #301509 |
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Title:
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Bayesian Analysis of cDNA Microarray Data
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Author(s):
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Michael Black*+ and Bruce Craig and John Deely and Rebecca Doerge
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Affiliation(s):
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Purdue University and Purdue University and Purdue University and Purdue University
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Address:
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1399 Mathematical Sciences Building, West Lafayette, Indiana, 47907-1399, USA
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Keywords:
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Bioinformatics ; Microarray ; Differential expression ; Bayesian ; ANOVA ; Multiple comparisons
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Abstract:
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The recent explosion of interest in microarray technology has resulted in this becoming the preferred methodology for conducting gene expression experiments. Although the ability of an array experiment to examine the expression of thousands of genes simultaneously gives a previously unheard of level of insight to researchers, it also raises a plethora of statistical questions regarding both the sheer volume of data being produced, as well as the level of variability inherent in this relatively new technology. We present statistical methods based on Bayesian hierarchical models for detecting genes undergoing differential expression in microarray experiments. These techniques are demonstrated using data from studies conducted in conjunction with the Purdue University Computational Genomics facility.
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