Cross phenotype normalization of microarray data.

Abstract excerpt

Normalization is a prerequisite for almost all follow-up steps in microarray data analysis. Accurate normalization across different experiments and phenotypes assures a common base for comparative yet quantitative studies using gene expression data. In this paper, we report a comparison study of four normalization approaches, namely, linear regression (LR), Loess regression, invariant ranking (IR) and iterative...

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