vsn
Variance stabilization and calibration for microarray data Bioconductor version: Release (2.10) The package implements a method for normalising microarray intensities, both between colours within array, and between arrays. The method uses a robust variant of the maximum-likelihood estimator for the stochastic model of microarray data described in the references (see vignette). The model incorporates data calibration (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.
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References in zbMATH (referenced in 29 articles )
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Sorted by year (- Meijer, Rosa J.; Krebs, Thijmen J. P.; Goeman, Jelle J.: Hommel’s procedure in linear time (2019)
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