Methodology article

Selecting normalization genes for small diagnostic microarrays

Jochen Jaeger^* and Rainer Spang

• * Corresponding author: Jochen Jaeger jaeger@molgen.mpg.de

Author Affiliations

Max Planck Institute for Molecular Genetics, Ihnestrasse 73, 14195 Berlin, Germany

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BMC Bioinformatics 2006, 7:388 doi:10.1186/1471-2105-7-388

Published: 22 August 2006

Abstract

Background

Normalization of gene expression microarrays carrying thousands of genes is based on assumptions that do not hold for diagnostic microarrays carrying only few genes. Thus, applying standard microarray normalization strategies to diagnostic microarrays causes new normalization problems.

Results

In this paper we point out the differences of normalizing large microarrays and small diagnostic microarrays. We suggest to include additional normalization genes on the small diagnostic microarrays and propose two strategies for selecting them from genomewide microarray studies. The first is a data driven univariate selection of normalization genes. The second is multivariate and based on finding a balanced diagnostic signature. Finally, we compare both methods to standard normalization protocols known from large microarrays.

Conclusion

Not including additional genes for normalization on small microarrays leads to a loss of diagnostic information. Using house keeping genes from the literature for normalization fails to work for certain datasets. While a data driven selection of additional normalization genes works well, the best results were obtained using a balanced signature.