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Title:  Normalization for cDNA Microarray Data.

Authors: Yee Hwa Yang, Sandrine Dudoit, Percy Luu and Terry Speed

Abstract:

There are many sources of systematic variation in microarray experiments
which affect the measured gene expression levels. Normalization is the
term used to describe the process of removing such variation, e.g. for
differences in labeling efficiency between the two fluorescent dyes. In
this case, a constant adjustment is commonly used to force the
distribution of the log-ratios to have a median of zero for each
slide. However, such global normalization approaches are not adequate in
situations where dye biases can depend on  spot overall intensity and
location on the array (print-tip effects). This paper describes
normalization methods that account for intensity and spatial dependence
in the dye biases for different types of cDNA microarray experiments,
including dye-swap experiments. In addition, the choice of the subset of
genes to use for normalization is discussed. The subset selected may be
different for experiments where only a few genes are expected to be
differentially expressed and those where a majority of genes are
expected to change. The proposed approaches are illustrated using gene
expression data from a study of lipid metabolism in mice. 
 

Slides: Download power point file [ppt file][jpeg files] 
Full Text: Download [pdf file][ps file]