Ben Bolstad
Division of Biostatistics
University of California, Berkeley

Title: Low-Level Analysis of High-Density Oligonucleotide Microarray Data

Microarray experiments are becoming widely used for many biomedical
applications. After a brief introduction to the Affymetrix GeneChip
microarray platform, I plan to describe how a gene expression measure 
might be constructed. Specifically, I will discuss a three-stage 
process: Background Adjustment, Normalization and Summarization. 
The focus will be on how each step affects the specificity and 
precision of the computed expression measure, as well as the ability 
to detect differential expression. A great deal of the discussion will 
be in the context of the Robust Multi-chip Average (RMA) expression measure.

If time permits, I will briefly examine some extensions of the RMA
method. In particular, I will present some preliminary results showing how 
probe-level models, rather than expression measures, may be used for 
differential expression detection.