Exploring Microarray Data with Plots
Di Cook, Department of Statistics, Iowa State University, Ames, IA

Monday, Sept 27, 2004, 4:10 PM
319 Snedecor

This talk describes visual methods for analyzing microarray data, in

the context of general methodology for multivariate data

visualization.  A worked example focusing on an experimental study

containing two factors having two levels, and hence four treatments,

each with two replicates, is described.  We explore variation in gene

expression due to treatment in comparison to variation in replication,

and variation in expression levels amongst all genes. Linked

scatterplots and profile plots are used along with repeated measures

plots. This research describes how to use graphics and numerical

methods for exploratory analysis of gene expression data.

joint work with

Heike Hofmann, Eun-Kyung Lee, Hao Yang, in Statistics

Basil Nikolau, in Biochemistry, Biophysics and Molecular Biology

Eve Wurtele, in Genetics, Development and Cell Biology

Iowa State University, Ames, IA