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Variance stabilization and calibration for microarray data
Variance stabilization and calibration for microarray data
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The package implements a method for normalising microarray intensities from single- and multiple-color arrays. It can also be used for data from other technologies, as long as they have similar format. The method uses a robust variant of the maximum-likelihood estimator for an additive-multiplicative error model and affine calibration. The model incorporates data calibration step (a.k.a. normalization), a model for the dependence of the variance on the mean intensity and a variance stabilizing data transformation. Differences between transformed intensities are analogous to "normalized log-ratios". However, in contrast to the latter, their variance is independent of the mean, and they are usually more sensitive and specific in detecting differential transcription.
Summary
Variance stabilization and calibration for microarray data
Last Updated
Dec 16, 2024 at 23:40
License
Artistic-2.0
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95.5K
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