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      Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation

      Nucleic Acids Research
      Oxford University Press (OUP)

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          Abstract

          There are many sources of systematic variation in cDNA microarray experiments which affect the measured gene expression levels (e.g. differences in labeling efficiency between the two fluorescent dyes). The term normalization refers to the process of removing such variation. A constant adjustment is often used to force the distribution of the intensity 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/or spatial location within the array. This article proposes normalization methods that are based on robust local regression and account for intensity and spatial dependence in dye biases for different types of cDNA microarray experiments. The selection of appropriate controls for normalization is discussed and a novel set of controls (microarray sample pool, MSP) is introduced to aid in intensity-dependent normalization. Lastly, to allow for comparisons of expression levels across slides, a robust method based on maximum likelihood estimation is proposed to adjust for scale differences among slides.

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          Author and article information

          Journal
          Nucleic Acids Research
          Oxford University Press (OUP)
          13624962
          February 15 2002
          : 30
          : 4
          : 15e-15
          Article
          10.1093/nar/30.4.e15
          100354
          11842121
          aa262513-fbb8-48f1-899c-03b45dccaebf
          © 2002

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