Biomedical Engineering Reference
In-Depth Information
CHAPTER 7
MICROARRAY DATA ANALYSIS IN AFFYMETRIX
GENE CHIP
Dung-Tsa Chen a and James J. Chen b
a Department of Medicine, School of Medicine,
University of Alabama at Birmingham, Birmingham, AL, USA
b Division of Biometry and Risk Assessment,
National Center for Toxicological Research, Food and Drug Administration,
Jeerson, AR, USA
Microarray technology has advanced genomic research. Among various
platforms, Aymetrix gene chips have been the most widely used to
study thousands of genes simultaneously through mRNA expression.
Analysis of Aymetrix gene expression data requires multiple steps, in-
cluding data quality assessment, gene selection, and gene function classi-
cation. We describe a 2D image plot approach to assess data quality by
examining array comparability. This approach uses a percentile method
to group data, and then applies the 2D image plot to display the grouped
microarray data with an invariant band to quantify degrees of array com-
parability. The method provides an ecient way of visually identifying
incomparable arrays. Next, we describe a probe rank approach to select-
ing dierentially-expressed genes. The probe rank approach uses rank
scores to normalize and analyze probe intensity to control for probe ef-
fect, and uses a lter of percentage of probe fold change to account for
cross-hybridization and alternative splicing. In the gene function clas-
sication, we describe an integrated bioinformatics tool to organize the
genomic information of selected genes systematically so that their func-
tional information is readily available for search objectives. The tool
integrates a series of major genomic databases, such as Aymetrix's
NetAx Analysis center and Entrez Gene database. The tool classies
genes and generates readable web-based outputs for investigators to eas-
ily associate signicant genes with biological pathways.
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