Abstract #300252

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JSM 2002 Abstract #300252
Activity Number: 93
Type: Topic Contributed
Date/Time: Monday, August 12, 2002 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistical Computing*
Abstract - #300252
Title: Mixed Models for Microarrays
Author(s): Russ Wolfinger*+
Affiliation(s): SAS Institute Inc.
Address: SAS Campus Drive R-52, Cary, North Carolina, 27513, USA
Keywords: microarrays ; bioinformatics ; gene expression ; mixed models
Abstract:

The recent flood of microarray data has presented biostatisticians with wonderful opportunities to utilize their training in working with scientists to draw optimal conclusions. It has also spurred a lot of new statistical research with varying degrees of complexity and usefulness. In this talk, we outline a systematic approach to microarray data with a view towards standardized interpretation. The framework centers around tried-and-true mixed linear models, which have proven very useful in numerous other areas of statistics, including clinical trials and quantitative genetics. We consider examples from both oligonucleotide and cDNA arrays.

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