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Normalization is essential in dual-labelled microarray data analysis to remove nonbiological variations and systematic biases. Many normalization methods have been used to remove such biases within slides (Global, Lowess) and across slides (Scale, Quantile and VSN). However, all these popular approaches have critical assumptions about data distribution, which is often not valid in practice.doi:10.1186/1471-2105-9-25 pmid:18199333 pmcid:PMC2275243 fatcat:l4lov2ph5bcztpx2r4dh43ayr4